Inside Copilot’s Researcher and Analyst Agents

TL:DR

Microsoft 365 Copilot now includes two advanced AI agents – Researcher and Analyst that became generally available in this month ( June 2025). These agents use powerful reasoning models (based on OpenAI’s o3-mini and deep research models) to handle complex tasks beyond what the standard Copilot could do.

Researcher is a specialised agent for multi-step research – it can securely comb through your work data (emails, files, meetings, etc.) and the web to gather information, ask clarifying questions, and produce well-structured summaries and insights. It’s ideal for tasks like market research, competitor analysis, or preparing for big meetings – work that used to take hours, now done in minutes with higher accuracy.

Analyst is a virtual data analyst/data scientist built into Copilot. It excels at advanced data analysis, working through messy spreadsheets or databases step-by-step using chain-of-thought reasoning and even running Python code when needed. From identifying sales trends to spotting anomalies in finance data, Analyst gives you in-depth answers and visuals that mirror human analytical thinking.

Compared to the standard Microsoft 365 Copilot, these agents go much further in reasoning and capabilities for these specific tasks. While the native Copilot mod helps draft documents or summarise content, Researcher and Analyst tackle complex reasoning tasks (deep research and data analysis) with a level of thoroughness and skill akin to an expert – essentially “like having a dedicated employee at your side ready to go, 24‑7,” according to Microsoft’s Jared Spataro. They are accessed through the Copilot interface (pinned in the Copilot app and via Copilot Chat) and come with a usage limit of 25 queries per month per user due to their intensive workloads.

Analyst vs. Copilot for Finance:

Analyst is a general-purpose data analysis agent available to any Copilot user, whereas Microsoft 365 Copilot for Finance is a separate, role-based Copilot designed specifically for finance teams. Copilot for Finance connects to financial systems (like Dynamics 365 and SAP) and Microsoft 365 apps (Excel, Outlook) to automate finance workflows (reports, reconciliations, insights). Unlike the Analyst agent which works on data you provide, Copilot for Finance directly taps into live enterprise finance data for real-time insights. Importantly, Copilot for Finance is not limited to Dynamics 365 – it can integrate with various ERPs including Dynamics 365, SAP, etc via connectors though it is deeply optimized for Dynamics 365 Finance.

The Age of AI Specialists in Microsoft 365 Copilot

Microsoft 365 Copilot is evolving from a single assistant into a team of AI specialists. Earlier this year, Microsoft announced two first-of-their-kind “reasoning agents” for work: Researcher and Analyst. After a period in preview (through the Frontier program) for early adopters, these agents are now generally available to all users with a Microsoft 365 Copilot license as of June 2025. This marks a significant expansion of Copilot’s capabilities beyond its initial skill set.

The new Researcher and Analyst are advanced Copilot modes (agents) specialised for particular scenarios – complex research and data analysis. They join other Wave 2 Copilot features (like the new Agent Store, Copilot Search, Memory, Notebooks, and image generation) that Microsoft has been rolling out to enhance the Copilot experience. Jared Spataro, Microsoft’s CMO for AI at Work, describes these agents as delivering “advanced reasoning” and notes “it really is like having a dedicated employee at your side ready to go, 24-7.” In other words, Microsoft 365 Copilot is no longer just a helpful assistant within Office apps – it can now also act as an on-demand subject matter expert that tackles higher-order tasks.

From a technology standpoint, both agents leverage the latest AI models tailored for their specific domains. They use OpenAI’s powerful models (codenamed o3-mini for Analyst, and a deep research model for Researcher) combined with Microsoft’s orchestration, search, Responsible AI, and tool integrations. This means they don’t just generate quick answers; they actually reason through problems in multiple steps, consult various data sources, and produce more comprehensive results. This blog explores each agent in detail:

Microsoft 365 Researcher Agent

Researcher is the new Copilot agent that acts as a highly skilled research assistant. It’s designed to help you tackle complex, multi-step research projects right from your Microsoft 365 environment. Researcher brings together OpenAI’s “deep research model” with Microsoft 365 Copilot’s advanced orchestration and search. In practice, this means it can scour both your organisational data *and* external sources on the web to find the information you need, synthesize it, and present insights in a coherent way.

What can Microsoft 365 Researcher Agent do?

Microsoft describes Researcher as “an agent that can analyse vast amounts of information with secure, compliant access to your work data – your emails, meetings, files, chats, and more – and the web” to deliver expert insights on demand. In simpler terms, Researcher is great at doing all the digging for information, reading it and then summarising the findings for you. Some of its capabilities include:

Multisource Information Gathering: It can search through your files, emails, SharePoint, and external online / Web sources to collect relevant data and. For example, if you’re exploring a new market or analysing a topic, Researcher will pull from both internal documents and credible websites to gather material.
Smart Summaries: After collecting information, Researcher summarises what it finds in plain, easy-to-read language. You get a clear, tailored report instead of a dump of raw data. It will highlight key points, trends, and insights rather than making you sift through hundreds of pages or search results.
Trend and Insight Identification: Researcher uses its AI reasoning to spot patterns, trends, and opportunities in the information. It can draw connections and highlight things that might make a difference for your project or question. For instance, it might notice an emerging customer preference across feedback data or identify a common thread in market research reports.
Interactive Refinement: If your initial query is broad, Researcher often asks clarifying questions to narrow down the scope and ensure it’s on the right track. This interactive back-and-forth helps it deliver more relevant results. You can guide it by answering those questions or giving additional instructions, much like you would with a human researcher.
Citations and Source Transparency: When delivering its findings, Researcher provides well-sourced content. It can include citations or references for where information came from, so you can trust but verify the results. (This is crucial for workplace research, and you can ask it to only use authoritative sources for extra confidence, as in one example prompt Microsoft shared).

Use Cases for Microsoft 365 Researcher Agent

Researcher is great in situations where you need to quickly learn or compile knowledge on a topic or subject area but are not sure where to look. This could be for tasks like assessing the impact of the new Trump tariffs on business lines, preparing for vendor negotiations by gathering supplier intel, and collecting client research before sales pitches.

Researcher Agent Example

In a business context, imagine your sales / marketing team are looking for a fresh perspective on top technology investments organisations are making in the UK based on industry research which needs to be in a report. You could ask Researcher “What are the top technology investments and projects by “small to medium” and enterprise organisations in the UK. Use trusted market data from repuatble sources such as Gartner, IDC, Cisco, Microsoft, Canlays, CRN etc.”

What I love is how you see the deep thinking and reasoning Researcher is using to compile the information and generate your report. This is so much easier than manually searching the web and reading dozens of articles. Instead, Researcher gives you a report in just a few minutes.

Instead of manually having to search the web and read loads and loads of articles, Researcher gives you a report in under ten minutes. You can of course tweak the response by asking more questions or requesting adjustments to ensure it meets you needs. When the report is finished you’ll see how comprehensive and well formatted it is, allowing you to export to, add it to a collaborative Copilot Notebook or leave it as is.

Microsoft 365 Analyst Agent – Data Analyst

If Researcher is your content and knowledge scout, Analyst is your number-crunching, data-savvy AI team member. The Analyst agent is all about diving into data (often numerical or structured data) to extract insights, find patterns, and answer complex analytical questions. Microsoft describes Analyst as “thinking like a skilled data scientist”, using an advanced reasoning approach to tackle data problems step-by-step https://www.microsoft.com/en-us/microsoft-365/blog/2025/06/02/researcher-and-analyst-are-now-generally-available-in-microsoft-365-copilot

What makes Microsoft 365 Copilot Analyst Agent special?

The Analyst agent runs on a finely-tuned AI reasoning model (post-trained on OpenAI’s o3-mini model specifically for analytical tasks). Unlike a standard chatbot that might try to answer a data question in one go (and often make mistakes), the Analyst agent uses a chain-of-thought process to break problems down and solve them iteratively. It can even generate and execute actual code (like Python) in the background to manipulate data, perform calculations, or generate charts. Throughout this, it adjusts to new complexities and can recover from errors autonomously – essentially debugging and refining its approach as it goes, much like a human analyst would. The end result is a thorough analysis with reasoning that is transparent to the user.

Here are some of the key capabilities of the Analyst agent:

Data Analysis Across Formats: Analyst can work with Excel spreadsheets, CSV/TSV files, databases, Power BI reports, and other structured data sources . It can even extract financial data from PDFs. It is possible to upload or point it to a dataset, even if the data is messy or hidden across multiple files. For example, if you have sales data split across a few different Excel sheets and files, you can use Analyst Agent to ingest them all. The agent can also clean up many of the typical issues found in spreadsheets such as wrong delimiters in a CSV, or values buried in an unexpected place before it starts to work. This means that your data does not need to be perfectly prepared beforehand .
Iterative Reasoning and Problem Solving: When you ask Analyst a question, it will hypothesise, test, and refine repeatedly. For instance, you might ask, “What insights can you find about our Q4 sales data, and why did some teams underperform?”. Here, Analyst might break this down into steps: first identifying overall sales by region, then noticing why one sales team is lower, then digging into possible factors (maybe inventory issues or lower marketing spend), then correlating that with other data. It takes as many steps as needed to arrive at a sound answer. This multi-step approach leads to more accurate and nuanced results than a one-shot response.

Code Generation and Execution: A standout feature – Analyst can write and run Python code behind the scenes to perform calculations or data transformations. If your data question requires a formula, statistical analysis, or creating a chart, Analyst will generate the code to do it. Even better, it shows you the code in real time as it works, so you have complete transparency into how it’s reaching its conclusion. You effectively have an AI that can program on the fly to solve your data problem. This is like having a data analyst who is also a programmer working for you instantly.
Insight Generation and Visualisation: Analyst doesn’t just provide text based results – it will also explain the “story” behind the numbers in plain language and can also create simple charts or graphs to illustrate key points. It could, for example, produce a trend line graph of sales over time or a bar chart of top-performing products if those help answer your question. It will highlight findings such as “Sales Team A had a 20% increase in Q4, outpacing their previous year results ,,,, ” By narrating and illustrating the data, it helps you quickly understand the business implications.
Actionable Recommendations: Analyst can often suggest next steps or recommendations based on the data patterns it finds. If it discovers, say, that a certain region’s sales are lagging due to low inventory, it might recommend increasing stock or marketing in that region. Or if a customer segment is showing poor engagement, it could suggest targeted outreach. These suggestions turn raw analysis into useful advice, bridging the gap from insight to action.

Microsoft 365 Analyst Agent Use Cases:

The Analyst agent is useful anywhere you have data and questions about that data. Some real-world examples Microsoft has noted include using Analyst to assess how different discount levels affected customer purchasing behavior to identify the top customers who aren’t fully utilising the products they bought, and to visualise product usage trends and customer sentiment for informing go-to-market.

Analyst Agent Example

In the example below, I took some Customer Support Tickets from an excel (see below).

I then have asked the Analyst Agent to “review the support ticket and create me an exective summary of the tickets, pulling out trends and themes that my team should look at and how they might reduce future support call duration.”

The results below are the first run with data that represeted as I have asked.

How Do Researcher and Analysts Agents Compare to the Standard Microsoft 365 Copilot Experience?

With all the excitement around Researcher and Analyst, you might wonder how they differ from the core Microsoft 365 Copilot Chat experience that users have been trying out in apps like Word, Excel, Teams, and Outlook.

The key difference comes down to depth of reasoning and specialisation. The core Copilot Chat experience is like a well-rounded generalist – great at everyday productivity tasks, such as drafting an email, summarising a document or thread, writing in Word, generating a PowerPoint outline, or pulling insights from a single Excel worksheet. It uses a large language model (LLM) to understand your prompt and the context from the active document, then provides a response.

However, it typically gives a direct answer or action based on available content, without doing prolonged multi-step reasoning. For example, standard Copilot can summarise a document or create a draft from prompts, but if you ask it to perform a very complex analysis that requires digging through multiple files or doing calculations, it may hit its limits. Thats where these specialist agents differ:

Advanced Reasoning vs. Quick Responses: “Standard” Copilot Chat is designed for quick assistance within the flow of work (one-shot answers or short tasks). In contrast, Researcher and Analyst use advanced reasoning algorithms (chain-of-thought) that allow them to work through a problem in multiple steps). They will plan, execute sub-tasks (like searching sources and creating and executing code), and then refining its output. This means they can handle questions or tasks that the regular Copilot would either answer superficially or not manage at all.

Tool Use and Data Access: These specialist agents have access to a much broader set of information and models. Researcher can tap into web search and internal knowledge bases simultaneously, something standard Copilot doesn’t proactively do by itself. Analyst can use the equivalent of a built-in scripting engine (Python) to manipulate data. These abilities let the agents produce more accurate, data-backed results (for instance, Analyst can compute exact figures or generate a pivot table behind the scenes, rather than guessing).

Use Case Focus: Out of the box, Microsoft 365 Copilot has a breadth of capabilities across Word, Excel, PowerPoint, Outlook, Teams, etc., but each in a somewhat scoped way – e.g. helping write, summarise, or create within that app. It is “broad but shallow”. Researcher and Analyst are narrower but much deeper in their domains. If you don’t need multi-step research or advanced data analysis, you might not need to use them and the regular Microsoft 365 Copilot Chat or in app Copilot experience might suffice. But if you do have those needs, these agents provide a level of expertise that feels like a specialist joining your team.

For example, consider interpreting a complex financial report: Standard Copilot in Excel can summarise that report or maybe answer something about it if asked directly, but Analyst could take multiple financial files (ledgers, budgets, forecasts) and do a cross-file analysis, then produce a summary and suggest optimisations – a far more sophisticated outcome.

Interaction Model:Using Researcher/Analyst is a bit like launching a specific mode of Copilot meant for heavy tasks. They’re accessible via the Copilot app’s Agent Store or as pinned which is a different entry point than simply typing to Copilot in Word. This interface guides the user to ask bigger questions (“Help me investigate X” or “Analyse Y data for Z”) rather than the smaller in-app prompts. The agents also tend to show their working process (especially Analyst showing its code or reasoning steps), whereas standard Copilot just delivers the end answer in a friendly tone. This transparency is great for users who want to trust the results – you can literally see how Analyst arrived at an answer, step by step.

Analyst vs. Copilot for Finance – What’s the Difference?

With the introduction of the Analyst agent, you might also hear about Microsoft 365 Copilot for Finance – another AI offering that targets data and analytics, but specifically for finance professionals. It’s important to clarify how the Analyst agent and Copilot for Finance differ, because their names might seem related. In fact, they serve different needs:

Microsoft 365 Copilot for Finance (formerly introduced simply as “Copilot for Finance”, now in preview) is a role-based Copilot experience tailored for finance departments. This was announced in early 2024 as a way to “transform modern finance” by bringing generative AI into the daily workflows of finance teams. Unlike the Analyst agent – which any user with Copilot can use for various kinds of data analysis – Copilot for Finance is a separate add-on Copilot designed to integrate deeply with financial systems and processes. It essentially combines Microsoft 365 Copilot with a specialized finance agent and connectors to your financial data.

From what I have managed to assess these are the main differences between the Analyst agent and Microsoft 365 Copilot for Finance:

Aspect	Analyst Agent (Microsoft 365 Copilot )	Microsoft 365 Copilot for Finance
Purpose & Domain	General-purpose data analysis for any domain or department. Helps users analyse spreadsheets, databases, or other data to get insights.	Designed to work across certified and connected systems such as Microsoft 365 Dynamics, Salesforce and some others
Integration and Data	Works on provided or accessible data in Microsoft 365 (e.g. Excel files, CSVs, SharePoint data). No built-in direct connection to ERP systems – user typically uploads data or points to files for analysis	Connected to enterprise financial systems and data sources. Draws context from ERP systems (like D365 Finance & SAP) and the Microsoft Graph . Integrates in real-time with live finance data, assuming connectors are set up. Optimised for D365 Finance (seamless data access). Can connect other systems via custom or pre-built connectors).
Features and Skills	Uses chain-of-thought AI reasoning and Python code execution to perform analytics. Ideal for ad-hoc data analysis: e.g. combining sales data with customer data to find trends, identifying anomalies in operational data, generating charts from raw data. Acts as AI data analyst for any project.	Uses AI to streamline finance-specific processes and provide insights within finance workflows. For example, can automate variance analysis in Excel, perform reconciliations between systems, generate reports, summaries, and even draft emails for collections with relevant account info. Understands accounting principles and the company’s financial data.
User Experience	Accessed through the Copilot app as one of the agents (no special deployment beyond having Microsoft 365 Copilot license). The user asks questions or tasks in natural language and often provides the data files to analyze. The output is an interactive analysis in Copilot chat with optional visuals and code transparency.	Integrated into the tools finance teams use: primarily Excel, Outlook, and Teams in the context of finance work. For example, in Excel a finance user might invoke Copilot for Finance to run a budget vs. actual report or find anomalies in ledger data. In Outlook, it can summarise a customer’s account status from ERP data to help a collections officer. Works in flow of existing finance tasks, bringing AI where needed.
Availability & Pricing	Included as part of the Microsoft 365 Copilot (the Analyst agent is available to any user who has Copilot enabled). General Availability as of mid-2025. Usage is capped at 25 queries/month for heavy reasoning tasks.	Available as add-on to Copilot targeted at enterprises. Paid offering for organisations that use Microsoft 365 and want AI assistance in finance for supported systems like D365.
Dependencies on Microsoft Dynamics	Not dependent on Dynamics 365 – Analyst can analyse any data you give it. If your financial data is in Excel exports from SAP or Oracle, Analyst can still work with those exports, but it won’t directly pull from those systems on its own.	Deeply integrates with D365 Finance & Operations. Designed to plug into D365 modules so can act within that ecosystem (e.g., directly reading transaction data, posting results back). Through “connectors”, it can interface with other ERP or CRM systems too. Advantage is native use with D365 – without manual data exporting or integrations

To put it simply, the Analyst agent is like an AI data expert you can use for virtually any type of analysis by feeding it data, whereas Copilot for Finance is a comprehensive AI-powered solution built into Microsoft’s ecosystem to assist with a company’s financial operations in real-time. They might overlap in the sense that both can do things like variance analysis or finding trends in financial figures, but the context is different: Analyst would do it when you ask and give it the data (say, a couple of Excel files containing financial info), while Copilot for Finance would do it as part of your normal finance workflow, already knowing where the data is (in your ERP and Excel models) and proactively helping you in that domain.

Does Copilot for Finance only work with Dynamics 365?

No. Copilot for Finance is not limited to Dynamics 365, though that’s a primary integration. It brings together Microsoft 365 Copilot with a finance-focused agent that connects to your existing financial data sources including ERP systems like Dynamics 365 and SAP. So if your company runs SAP for finance, Copilot for Finance can use that data as well. Microsoft has built it to be flexible via connectors, because they know not everyone is on Dynamics. That said, organizations using Dynamics 365 Finance get a more seamless experience – Copilot for Finance can sit right inside the D365 Finance interface and offer insights without any data transfer.

In summary, Copilot for Finance is cross-platform in terms of data sources, but tightly integrated with Microsoft’s own finance solutions for maximum benefit. It’s an example of Microsoft creating role-specific Copilots (others being Copilot for Sales, Copilot for Service) that extend the core Copilot capabilities into specialised business functions.

Further Reading and Sources

As well my own experimentation, the following sources were also inferred and read when writing this blog. I did also use Copilot to help tweak the tone and flow.

https://techcommunity.microsoft.com/blog/microsoft365copilotblog/3-practical-ways-small-businesses-can-use-researcher-and-analyst-agents/4418059

https://techcommunity.microsoft.com/blog/microsoft365copilotblog/analyst-agent-in-microsoft-365-copilot/4397191

https://dynamicscommunities.com/ug/dynamics-fo-ax-ug/microsoft-copilot-vs-microsoft-copilot-for-finance-understanding-key-differences-and-benefits-for-users/

June 11, 2025July 7, 2025

Cisco Live 2025: AI Takes Center Stage and Networking Gets a Boost

Cisco Live 2025 is happening this week in San Diego (after five years in Vegas) with around 22,000 attendees. As you’d image from any tech event at the moment, the focus was very much AI with the theme being summed up as “All AI, all the time”. Throghout the Day 1 keynotes, Cisco’s message was clear: the “agentic AI era” is upon us, and Cisco is positioning itself as the infrastructure backbone to support service providers, cloud providers and enterprises of this new age.

Cisco’s President and Chief Product Officer Jeetu Patel set the tone with a bold analogy: “The way that you should think about us is like the picks and shovels company during the gold rush. We are the infrastructure company that powers AI during the agentic movement,”

…….In other words, while everyone’s chasing AI gold, Cisco’s approach is to providing the bedrock tools to dig for it – unveiling new innovations spanning networking hardware, unified management software, security, and collaboration tools, all infused with AI.

I wasn’t able to attend the event myself, but here’s my break down the top announcements and innovations from the live streams I watched. Let me know what I have missd 🙂

The “Agentic AI” Era

Cisco Live’s buzzword was undoubtedly “Agentic AI.” Cisco sees a shift from basic chatbots to autonomous agents that don’t just answer questions, but perform tasks and jobs on our behalf. As Jeetu Patel said in the keynote “The world is moving from chatbots intelligently answering our questions to agents conducting tasks and jobs fully autonomously. This is the agentic era of AI”.

Like many of the other tech giants, their view is that in this fast moving era, billions of AI agents could be working for us behind the scenes, which “will soar” the demand for high-bandwidth, low-latency and power-efficient networking in Cloud Providers and Private Hosted data centers.

Cisco’s key mesage here is that they are here to help organisations and providers meet this demand. “Cisco is delivering the critical infrastructure for the AI era — secure networks and experiences, optimized for AI that connect the world and power the global economy“.

Cisco CEO Chuck Robbins said that “no organisation can hire limitless people to tackle increasing IT complexity and cyber threats – instead – machines must scale to share the burden”. He went on to say how Automation and AI-driven operations are not just nice-to-haves; they’re becoming essential and every business is looking to invest and build here and it will only accelerate in pace and scale.

Cisco also set out to explain that “generative AI” and “agentic AI” have different effects on the infrastructure needed to support them. Generaive AI creates sporadic spikes in demand, but Agentic AI creates sustained perpetual demand for inferencing capacity. This means that for agentic AI, networks and Cloud data centers need a continuous heavy-duty upgrade to what they run on today. Cisco expect that many will large enterprises, those setting out to build their own “AIs” and of course Service and Cloud Providers will likley need to “re-rack the entire datacenter and rebuild the network” to handle these new AI workloads.

One Unified Plartform to Manage it all

As (a long time ago) IT Sys Admin, I remember how managing networks used to sometimes feel like herding cats – multiple dashboards for switches, routers, security, cloud, etc., all siloed.

Cisco has now announced Cisco Cloud Control, a new unified management console intended to “drive all its networking, security, and observability tools” from one place. In a nutshell, Cloud Control is Cisco’s approach to bring all those separate management tools into a single pane of glass – making it easier for network admins and giving a Cisco Customers a cohesive platform to showcase it’s new AI innovations in one place.

Of course Cloud Control is AI infused too. There is an AI Assistant that lets IT teams query their infrastructure in plain English. Here they could ask (as per their demo) “Hey Cisco, why is the Wi-Fi slow on the 4th floor?” and get a useful answer.

To achieve this, Cisco are using a new custom large language model trained on decades of Cisco networking knowledge (like an AI powered CCIE) to provide expert guidance. Cisco showed off a new AI Canvas (an “agentic” interface) that auto-generates relevant dashboards that work together to help identify issues, suggest fixes, and even implement changes – with human approval gating the final step. In short – you describe a problem, and the system brings forward the relevant controls and data needed to solve it, all guided by Cisco AI.

Cisco’s message is not just about adding AI for AI sake – it is designed to address real IT headache by combining formerly separate mnagement planes and interfaces into one.

Cisco also announced they are unifying management for their Catalyst and Meraki product lines (switching and wireless) into this single console, with common licensing too.

Overall, the message is that whether it’s campus networks, branch, data center, or cloud, Cisco goal is is to centralise control and inject AI assistance across them all, leading to smarter and simpler unified operations.

Splunk also got a mention – with Cisco talking about how ThousandEyes and Splunk analytics will also be able to integrate into this platform to give end-to-end visibility – from user device to application. This is part of a broader “One Cisco” vision of an integrated portfolio for networking, security, collaboration, and observability.

Net Hardware: Faster, Smarter, and Built for AI

It wouldn’t be Cisco Live without new hardware – and this year, Cisco delivered a loads of it. Recognising that AI workloads are putting unprecedented demands on Service provider and Cloud networks, Cisco unveiled a lineup of new switches, routers, and wireless devices which all give higher throughput, low latency, and security by design. This inlcuded:

Campus Switches (C9350 & C9610): Designed for campus networks and powered by its custom Silicon One chips – they boast a huge 51.2 Tbps of throughput and sub-5 microsecond latency, with quantum-resistant security built in. These are designed to handle “high-stakes AI applications” at the network edge.
Secure Branch Routers (8100, 8200, 8300, 8400, 8500 Series): To connect sites and users to AI resources, Cisco have unveiled these new Secure Catalyst Routers for branches. These are all-in-one boxes that combine SD-WAN, SASE (Secure Access Service Edge) connectivity and next-gen firewall. Cisco say they will deliver up to 3× the throughput of the previous generation too. Why? Cisco is converging networking and security at the WAN edge so that adopting AI doesn’t open new holes in your defenses.
Wi-Fi 7 (Cisco Wireless 9179F): – see new APs, tailored for stadiums and large venues. These APs support the latest Wi-Fi 7 standard bringing multi-gig speeds and better reliability and integrate Ultra-Reliable Wireless Backhaul (URWB) technology alongside Wi-Fi in one device. That means an access point can also serve as a highly reliable wireless bridge/mesh link, useful in places where running fiber/cable is hard.
Ruggedised Switches for Industry 4.0: To support AI at the edge – in places like factories, oil rigs, smart cities – Cisco unveiled 19 new rugged switches built to withstand harsh environments. These come in various form factors (tiny DIN-rail mounts, hardened casings, etc.) to fit into industrial sites where conditions are extreme. Interestingly, Cisco integrated that URWB wireless tech here too, meaning you can have a unified wireless fabric that covers both IT and OT (operational tech) environments via a combination of Wi-Fi and wireless backhaul. In plain terms, these rugged switches + wireless combos let factories and outdoor facilities achieve high-density, reliable wireless coverage as part of one unified infrastructure.
Powered by Cisco Silicon One: All Cisco’s hardware announcements reinforced a key point: networking and security are fusing together in Cisco’s strategy. All new switches and routers all come with baked-in security features (from Hypershield to post-quantum crypto) rather than treating security as an add-on. Jeetu Patel emphasised, that the future is about networks that are programmable and adaptable – Cisco’s own Silicon One custom chips are a big part of that story because it means that Cisco can update these devices for new AI workloads via software without needing to build a new chip and device. This is a major compete play and USP for Cisco.

Security in the AI Era: Zero Trust, Everywhere, All at Once

All the AI in the world won’t help if your business if your network isn’t secure. Cisco used this approach to double down on its message that security must be woven into every layer of the network, especially as AI opens new frontiers (and potentially new threats). In the agentic AI era, Cisco said that attackers will leverage AI, meaning threats could become faster and more sophisticated. The answer? “Secure by design” infrastructure and a unified security architecture that can handle the scale of AI-fueled operations.

As a result Cisco introduced a new network security blueprint anchored by what they call the Hybrid Mesh Firewall and Universal ZTNA (Zero Trust Network Access). They represent a concerted effort to integrate security across all users, devices, and applications more seamlessly including:

Hybrid Mesh Firewall: Annouced earlier this year, Cisco’s next-gen firewall for the AI era, acts as a distributed security fabric spanning your whole environment. It brings together Cisco’s own firewalls and even third-party firewall integrations into one cohesive system to to enable zero-trust segmentation everywhere – from your data center core, across clouds, out to branch offices and all the way to IoT devices at the edge. The goal is that every part of the network becomes a security enforcement point, tightly coordinated.
Universal ZTNA: Cisco’s Zero Trust Network Access solution, now branded “Universal” because it aims to cover any user or device, anywhere. Universal ZTNA provides secure, identity-based access to applications, whether users are on the corporate LAN, at home, or on a mobile device. It extends the zero-trust mode to hard-to-manage endpoints and ensures a unified policy follows the user. For example, whether JimBob from accounting logs in from the office or from a coffee shop Wi-Fi, the system continuously verifies his identity and device posture before granting access to the finance app. The synergy here is that integrating ZTNA and the distributed firewall, Cisco can tightly control user-to-app connections and even monitor the traffic between services, all under a zero-trust philosophy.

Beyond hardware, the cloud-based Cisco Security Cloud got enhancements to help secure those emerging AI workflows. Their platform can now better secure interactions involving AI agents, using tools like Cisco AI Defense (which monitors AI model operations for tampering or misuse) as part of a “Secure AI Factory” concept co-developed with NVIDIA.

Their integration of Splunk also got a mention, where they demonstrated deeper Cisco + Splunk integrations for security analytics – such as sending security events and network telemetry into Splunk’s SIEM and using Splunk’s AI-driven insights to automate responses via Cisco’s tools.

Webex: Smarter Meetings, AI Helpers, and Cameras with a Brain

Cisco did also announce a series of Webex updates with more AI coming into Webex in ways that aim to make meetings less of a chore and customer service more efficient.

Jira Workflow Automation in Webex: For native Webex meetings, this can listen for action items discussed in a meeting and automatically create Jira tickets for them. For example, if during a team call someone says “I’ll update the budget doc next week,” the AI will note that and generate a task in Jira , Monday.com or Asana – fill in your project tool) assigned to that person. It will even capture the context by attaching relevant portions of the meeting transcript or recording. Cisco touted, the integration can also update Jira tickets in real-time if status changes are mentioned in meetings – so, if the team says “the server migration is completed,” the AI could move the Jira task to “done” and note the discussion. It’s like having a diligent virtual project manager in every meeting, so humans can focus on discussion rather than note-taking.
Webex AI Agent for Customer Self-Service: They announced enhancements to the Webex AI Agent – to make it easier to deploy and more powerful. Tgherenis a new set of prebuilt, industry-specific templates – out-of-the-box chatbot templates tailored for industries like healthcare, finance, retail, etc. Instead of a generic bot that has to be trained from scratch, Cisco provides a starting knowledge base (e.g., a healthcare template might know common questions about insurance, appointments, privacy rules, etc.). This can significantly speed up creating a virtual agent and leads to more relevant answers since it’s contextually aware of the industry. Cisco are also enabling these AI agents and features for on-premises deployments as well.

Conclusion

Cisco is all-in on AI, not by making its own AI apps, but by supercharging the underlying tech that makes AI possible.

Cisco seem fully aware of the challenges businesses face with emerging technologies. – whether it’s handling the flood of data and compute that AI workloads generate, securing a more complex threat landscape, and having a true end to end view on the user experence – Cisco is positioning itself as the enabler (and problem-solver) and has signaled it’s not sitting on the sidelines of the AI revolution.

The narrative of “One Cisco” came through strongly: networking, security, collaboration, cloud, and services all interlinking to form a complete platform for the AI era. Cisco is offering a very compelling toolkit for enterprises: blazing-fast hardware to move AI bits, smart software to manage it with minimal hassle, and built-in security every step of the way.

Cisco wants to be “the infrastructure company that powers AI” – the dependable partner under the hood while everyone chases AI magic. By unifying its platforms and injecting AI into network operations, Cisco is making a play to stay indispensable in this new era.
Jeetu Patel – Cisco.

June 2, 2025July 7, 2025

Copilot & Teams will finally understand your business jargon!

One of the most frustrating thing about Teams intelligent Recap and Copilot in meetings is in its ability to not understand company acroymns and internal “language” or terms.

Scheduled to rollout in July 2025, tenant administrators will be able to upload a Custom Dictionary through the Microsoft 365 Admin Portal’s Copilot Settings page.

This feature will finally enables organisations to improve transcription accuracy in Copilot and Teams meetings and calls by enabling Microsoft 365 to understand company-specific terminology. This will means that will be able to understand things such as

Industry jargon,
Internal product names and terms
Multilingual terms

This should help ensure conversations are transcribed and interpreted with greater precision.

Why this matters?

Organisations rely on Microsoft Copilot and Teams transcripts for insights, documentation, and knowledge retrieval. However, standard AI transcription can misinterpret niche terms or acronyms, leading to confusion and even sometimes humorous transcriptions.

This new Custom Dictionary feature addresses this by allowing businesses to define key terms their workforce frequently uses.

Real Benefits.

Legal & Compliance Accuracy: Law firms using specialised legal terminology (e.g., “prima facie,” “voir dire”) can ensure precise transcripts without ambiguity.
Enterprise Acronyms & Branding: Technology companies like Cisilion will be able to maintain more accurate documentation of internal project names (e.g., “Project Nebula”) and proprietary solutions.
Global Team Collaboration: Multinational organisations can optimise transcription quality across multiple languages and regional dialects.
Better AI Insights & Search:Copilot will be able to retrieve knowledge more effectively, ensuring summaries, recommendations, and contextual responses align with an organisation’s unique vocabulary.

This update is part of a broader set of Microsoft 365 enhancements including improved accessibility for sign language users in Teams meetings and expanded Copilot capabilities for 1:1 and group calls.

By refining AI-driven language models, Microsoft aims to make workplace collaboration smarter, clearer, and more inclusive.

You can read more and track this features release on the official Microsoft 365 Roadmap.

There’s instructions for enabling and configuring it here.

April 24, 2025April 25, 2025

2025 Work Trend Index Report – AI agents will make every employee an “agent boss”.

Microsoft has just released its annual Work Trend Index report, and as anticipated, its focus is boldly centered on the transformative impact of generative AI in the workplace.

The report reveals that we’re on the brink of a paradigm shift where AI will not only reason but will also solve problems in unprecedented ways. Much like the industrial revolution or the dawn of the Internet, Microsoft suggests that a complete overhaul of work practices may take decades to fully materialise.

The annual Work Trend Index conducts global, industry-spanning surveys as well as observational studies to offer unique insights on the trends reshaping work for every employee and leader across more than data from 31,000 workers across 31 countries, LinkedIn labor market trends, and trillions of Microsoft 365 productivity signals,as well as leading AI-native startups, academics, economists, scientists, and thought leaders.

The full report is in the link below, but I’ve summarised the key insights around how the report claims generative AI is reshaping work and leadership dynamics.

AI’s Transformative Role

AI continues to advance in its reasoning and problem-solving ability, with the potential to revolutionise work.
Major transitions like the industrial revolution and the Internet took decades and view is that full wide scale AI may follow a similar path.

Immediate Impact of AI on work

Key Finding	Stats
AI Adoption	82% of industry leaders acknowledge AI is changing work
New Work Models	The “Frontier Firm” concept describes organisations using AI-powered intelligence on demand.
New emerging roles	The rise of *“agent bosses”*—professionals managing AI agents to enhance productivity.

Productivity Challenges

Challenges from the last 5 years continue to plaugue employees and impact productivity with tech overload and AI is seen as a “potential” to reduce this and bring better focus to information workers.

The report reveals that 80% of the global workforce feels overburdened by constant interruptions—an email, meeting, or ping every two minutes. Consequently, about 82% of leaders plan to harness AI and digital labor within the next 12 to 18 months to alleviate these pressures.

82% of leaders plan to harness AI and digital labor within the next 12 to 18 months to alleviate work and resource pressures.

Bridging Business Needs and Human

AI is making intelligence more accessible, shifting focus from headcount to on-demand expertise.
It helps close gaps between business demands and human workload.

Organisations are urged to invest in adoption training and business process reviews to determine the most optimum areas to leverage AI.

Key Finding	% impact
Executives concerned about productivity	53%
Global workforce feeling overburdened	80%
Average interruption rate	Every 2 minutes
Leaders planning to use AI to improve work	82% (within 12–18 months)

Talent, Hiring and Employment Trends

Addressing common concerns about AI replacing jobs, the report delves into LinkedIn data that indicates that top AI labs are hiring at twice the rate of traditional big tech companies. Interestingly, it says that much of this new talent is transitioning from established tech firms, underscoring a dynamic reshuffling of skills and expertise in the workforce.

The report also underscores the necessity for executives to strike the perfect balance between human talent and AI agents. As these digital assistants become ever more integrated into daily tasks, the role of the “agent boss” is emerging leaders who build, delegate, and manage AI agents to magnify their impact and steer their careers in the age of AI.

The report talks of a future where every worker, from the boardroom to the frontline, must adopt a CEO-like mindset for an agent-powered startup, predicting that within five years, 41% of teams will be actively training and 36% managing AI agents.

AI labs are hiring at 2x the rate of big tech firms.
Many AI hires come directly from established tech companies.

Human vs. AI Balance in Workplaces

Leadership Perspective	Employee Persective
67% of leaders understand AI agents.	40% of employees understand AI agents.
79% of leaders believe AI will accelerate careers.	67% of employees believe the same.

AI’s current and future role in Work Automation

AI Usage	Areas Impacted
46% of leaders use AI agents to fully automate workstreams.	Customer service, marketing, product development.
Organisations evaluating human-to-AI balance	AI integration must match societal expectations and business needs. \|

But…..it states that AI is shifting the global work landscape, demanding strategic adaptation with..

Percentage	Areas Impacted
83% of leaders	believe AI will enable employees to tackle more complex tasks.
78% of leaders	want to recruit for new AI-related roles.

The report highlights that 67% of leaders are familiar with AI agents compared to only 40% of employees, and 79% believe that AI will accelerate their careers, outstripping the 67% noted for the broader workforce.

What other leaders are saying…

Bill Gates (Founder of Microsoft) said publically that AI might eventually perform “most things,”. We have also seen Salesforce CEO Marc Benioff already rethinking his company’s hiring strategies for 2025. This says that as we navigate this transformative wave, company leaders need to carefully consider when and what digital labour can complement, or in some cases, surpass that of human expertise, especially in roles that demand a personal touch or entail significant responsibility.

There is a necessity for executives to strike balance between human talent and AI agents. As these digital assistants become ever more integrated into daily tasks, the role of the “agent boss” is emerging—leaders who build, delegate, and manage AI agents to magnify their impact and steer their careers in the age of AI
Microsoft Work Trend Index Report

Summary

Microsoft’s Work Trend Index report paints a vivid picture of a future in which they show how AI is starting and has the potential to reshape every facet of our professional lives.

It claims that 83% of leaders believing that AI will empower employees to tackle more complex challenges and 78% actively looking to fill new AI roles, the global work landscape is poised for a dramatic evolution—one that necessitates a delicate balance between harnessing digital innovation and preserving the unique value that human insight brings to the table.

March 29, 2025April 29, 2025

Deep research AI models coming to Microsoft 365 Copilot

As March 2025 comes to an end, Microsoft have unveiled several exciting updates across Microsoft 365 Copilot, Copilot Chat, and Copilot Studio.

Copilot announcements this week

1. Updates to Copilot Studio Message Rates

Effective April 2nd, 2025, updated (cheaper) message rates for Copilot Studio will go live. These adjustments cover tenant Microsoft Graph grounding and agent actions (previously known as autonomous actions). The prices of tenant Microsoft Graph grounding and autonomous actions are being reduced from 30 messages and 25 messages to 10 messages and 5 messages respectively, from April 2nd, 2025.

The following table illustrates the differences in the subscription models for the cost of Copilot Studio events.

Copilot Studio feature	Billing rate [non M365 Copilot Licensed users]	Billing rate [M365 Copilot licensed users]	Autonomous triggers¹
Classic answer	1 message	No charge	N/A
Generative answer	2 messages	No charge	2 messages
Agent action	5 messages	No charge	5 messages
Tenant graph grounding for messages	10 messages	No charge	10 messages
Agent flow actions per 100 actions	13 messages	13 messages	13 messages

1 - Autonomous triggers refer to events or conditions that automatically initiate an agent to take action, without requiring a user to manually invoke it.

Also coming is Agent flows which allow agent creators to bring Power Automate automation features directly into Copilot Studio to quickly and consistently automate business processes. There will also be new deep reasoning in agents combines reasoning models including Open AI o1 with the ability to access enterprise data to complete complex tasks.

Microsoft are also updating pricing with a new zero-rating for Microsoft 365 Copilot licensed users in Microsoft 365 apps and services, ensuring inclusive, seamless integration and cost-effective use of these tools. This means licensed Microsoft 365 Copilot users will not be charged for using agents in their organisation

2. Rule-Based Workflows in Copilot Studio

From April 2025, Copilot Studio will introduce structured, rule-based workflows for agents. This aims to simplify process automation, enabling users to create efficient, consistent workflows with minimal manual effort. Usage of this functionality will contribute to the Copilot Studio meter, encouraging innovation while maintaining transparency in resource utilisation.

3. Deep Reasoning in Copilot Studio

So this is a big one – Microsoft have made deep reasoning capabilities available in Copilot Studio’s public preview from today. This will empowers users to address complex, decision-intensive tasks by leveraging advanced reasoning algorithms.

Whether it’s managing intricate processes or solving challenging problems, this tool offers remarkable precision and depth in its execution.

4. Two new Deep Reasoning Agents

Microsoft announced two new deep reasoning agents—Researcher and Analyst—as part of an early preview which will also be coming “soon” with previews coming in April before wider rollout.

Researcher Agent: has been designed for content creation and information synthesis, this agent combines OpenAI’s advanced deep research model with Microsoft Copilot’s orchestration. By integrating Copilot Chat’s web and work grounding capabilities, Researcher enables users to brainstorm ideas, generate high-quality content, and analyze data more effectively.

Analyst Agent: This is powered by a new reasoning model. the Analyst agent will function as a virtual data scientist and will have the ability to process complex datasets and provide real-time code validation (using Python) and will be able to deliver actionable insights and visually compelling representations of data in minutes.

Microsoft say that these agents will be gradually rolled out to Microsoft 365 Copilot licensed users through the Frontier program, an early access programme for customers to test out early and new Copilot innovations.

To dive deeper into these updates, visit Microsoft’s official blog.

March 9, 2025March 11, 2025

Windows 11 finally gets a native Copilot app.

At the end of Feb 2025, Microsoft gave Apple Mac users with a brand-new native Copilot (consumer) app experience and now after a feeble Web app version, Windows 11 is finally getting a proper one too.

This latest update brings a fully native Copilot app to Windows, delivering a faster, smoother, and visually enriched interface that aligns perfectly with the Windows 11 design language. Yay.

It also has a keyboard shortcut that lets you hold the Alt + Spacebar keys for two seconds to start chatting to Copilot via voice.

From Web View to Native App

For those who followed the initial rollout, you’ll remember that the original Copilot for Windows was simply a web view of the Microsoft Copilot website. While functional, it left much to be desired in terms of responsiveness and overall polish.

The new Copilot update transforms that experience completely. By leveraging the native app UI framework, Microsoft has infused the app with features that make the experience feel inherently Windows 11 that is also complete with a sidebar for managing chats, elegant mica blur effects, and native context menus and buttons.

This adherence to the native design not only improves aesthetics but also boosts performance and responsiveness.

What’s New in the Copilot for Windows App?

Enhanced User Interface

Native Design Language: The interface now mirrors the sleek, modern aesthetics of Windows 11.
Smooth Interactions: Launching the app is noticeably quicker, and interactions feel seamless thanks to the native integration.

Intelligent Chat Management

Sidebar for Conversations: All your previous chats are saved and easily accessible in a dedicated sidebar.
Instant New Chat: Starting a new conversation is as simple as hitting the new chat button.

Retained and Expanded Functionality

Text and Voice Chat: Continue to interact with Microsoft’s AI assistant using text, or opt for the Copilot Voice for a more dynamic experience.
Customisable Settings: Options include settings to enable or disable launching the app on Windows boot, as well as toggling the alt+spacebar shortcut for quick access.

In short, there’s no real feature changes here – just a native Windows App, ensuring that the native experience makes no compromises on capability and features along with performance and usability improvements of a native app.

First thoughts on the new version

I have to confess—I wasn’t thrilled with the old web view version of Copilot for Windows. It felt like an afterthought compared to its Mac counterpart. This new native experience, however, is a major improvement. The app now inspires confidence in handling everyday AI tasks and is genuinely enjoyable to use.

Getting the new Copilot App

For Windows Insiders excited to explore this update, the latest version (1.25023.107.0) or higher is now available via the Microsoft Store and should update automatically. The app is rolling out in preview across all Insider channels, inviting users to experience this transformative upgrade first-hand.

As a Microsoft product inside another Microsoft product, the evolution from a mere web view app (which should never have been done in my opinion) to a fully fledged native app that looks and feels like a Windows app not only elevates user interaction but also shows that Microsoft is actually serious about integrating AI seamlessly into everyday computing tasks.

The new Copilot for Windows app also has a keyboard shortcut that lets you hold the Alt + Spacebar keys for two seconds to start chatting to Copilot via your voice.

Microsoft want your feedback

Microsoft would like feedback too, which you can do by filing feedback in the Feedback Hub (WIN + F) under Apps > Copilot or directly within the Copilot app by clicking on your profile icon and choosing “Give feedback”.

This feedback shapes the future. Whether we can expect more iterative updates, possibly with additional features and enhancements will only happen based on the Microsoft collects feedback from Insiders.

Conclusion

The leap to a native interface is more than just a cosmetic upgrade—it represents a thoughtful stride toward a more integrated and responsive Windows experience. I’m excited to see how this native Copilot app will further inspire productivity and innovation as it evolves.

What are your thoughts on this updated native app?

February 25, 2025February 25, 2025

Making IT fAIr

Interesting article I read today about how the UK government is looking to change around the use of creative content without authors permission unless they choose to opt out.

The full article is below but in short it sets out these approaches and goals. https://newsmediauk.org/make-it-fair/

Proposal

The Government’s proposal is to change the laws to favour tech platforms, allowing them to use content without permission or payment unless the authors / creators specifically opt out.

Concerns

Creator and authors are challenging this arguing that this shifts the burden onto them. They believe that tech companies pay for using their content and training models based on their content.

They are urging the government to enforce copyright laws to ensure fair compensation for creators, securing the future of creativity and AI but in a way that protects the authors and creators of content.

The article calls for UK people to back this plan urging the UK government to enforce copyright laws to ensure fair compensation for creators and authors.

Where do you stand?

This is a tricky one for me as today, I feel most content LLMs are trained on are US based data sources and I would love to see more content based on UK data (after all I am British). At the same point, if a levvy is introduced and royalties paid a model for recouping costs is needed which may lead to this content being excluded in LLM training. This could lead to more bias and still leave them “out of pocket”.

Welcome your thoughts?

February 19, 2025February 19, 2025

Copilot in Excel gets new document references features

In an new update announced on the Microsoft 365 Insider blog this week, Microsoft has announced that Copilot in Excel will soon be able to reference documents in Word, Excel, PowerPoint, and PDF formats jyst like the other officee apps can. This enhancement significantly expands the capabilities of Copilot in Excel, making it a more powerful tool for users.

With this update, you can now ask Copilot to perform tasks such as displaying to-do items in a table or organising emails with columns for the sender and subject line. This feature is particularly useful when you need to combine data from various sources, including public statistics from the web, internal documents, organisational details, or tables from another Excel files or contained in Word docs.

Getting Started with the New Feature

To take advantage of this new functionality, you need to meet the following minimum requirements:

Windows: Build 17729.20000 or later
Mac: Build 24053110 or later
Copilot license
Web search enabled
Stable internet connection

Upcoming Web Version and Limitations

Microsoft has announced that this update will soon be available for the web version of Excel. However, there are some limitations to be aware of. For example, refreshable data imports only work for Excel files with tables stored on SharePoint or OneDrive. Additionally, there is limited support for handling workbook and external data simultaneously.

Recent Updates to Copilot in Excel

Copilot in Excel has received several updates in recent months, further enhancing its functionality. One of my favourite features is the Clean Data feature, which addresses issues such as text and number inconsistencies.

Copilot has been integrated into the Excel start up experience, enabling users to use Copilot to explain what they want to create and receive improvement suggestions.

Looking Ahead: More Features on the Horizon

With Microsoft’s global AI tour taking place in cities around the world, including a stop in the UK on March 5th, we can expect even more exciting features to be announced soon. These updates highlight Microsoft’s commitment to continually improving Copilot and making it an indispensable tool for Excel users.

Stay tuned to my blog for more updates in Copilot and bookmark the Microsoft 365 Road map page.

https://www.microsoft.com/en-us/microsoft-365/roadmap?filters=%5B”Microsoft+Copilot+for+Microsoft+365″%5D

February 6, 2025February 6, 2025

Here’s how to save and re-use your Copilot Prompts

Finally, it is here – Microsoft 365 Copilot now lets you save your prompts within Copilot for easy re-use later. Yes – this means you no longer need to save your prompts in separate documents or constantly copying and paste them.

How to save and re-use your prompts in Copilot

Open Copilot chat window in your browser at https://m365.cloud.microsoft/chat/.
Enter your prompt or prompts as usual
When Copilot has completed its response(s), scroll back to your prompt in the chat.
Hover your mouse over the prompt – you’ll see bookmark and link icons appear.

5. Click on the bookmark icon to save the prompt to your library – you can also give it a friendly name to make it easier to find and reuse later.

Accessing Your Saved Prompts

Finding your saved prompts is just as easy.

Click on “View Prompts” above the chat box.
In the prompt library popup window, select “Your Prompts.” where you will be presented with a list of all the prompts you’ve saved.
Click on any saved prompt, and it will automatically paste the text into the chat window, ready for you to use again.

Why this feature matters

The ability to save and easily access prompts directly within Copilot enhances productivity and streamlines your workflow. It’s a small change with a significant impact, making it easier than ever to manage your prompts efficiently.

No more hassle, no more copying and pasting—just seamless, effortless prompt management.

February 2, 2025February 2, 2025

Microsoft makes OpenAI o1 model free for Copilot users.

OpenAI’s most advanced AI model “o1” which is known for its problem solving and deeper thinking has been available behind a $20 per month ChatGPT premium subscription. ChatGPT premium gives limited acess for $20 a month and unlimited access for $200 a month.

Copilot let’s you use it for free.

Microsoft has a tight partnership with OpenAI and is also on a mission to put their AI (Copilot) across every Microsoft Service it offers with huge capability and features even on theor “free” tiers.

Copilot Consumer Pro users have had access to Think Deeper (which uses the o1 model) for the past 12 months, but Microsoft have now made this feature free to everyone including those using the free version of Copilot.

To access it, you need to simply head ovee to Copilot on the web, (or via the mobile app) and ensure you are signed in with a Microsoft account (MSA). You then get completed free access to the Think Deeper search (which uses the o1 model).

How to get Microsoft Copilot

To get Copilot, head to the web (you actually find Copilot in the Edge browser) and go to https://copilot.microsoft.com or head over to you phones app store and search for Copilot and install it.

You need to be signed in with your Microsoft account to use these features.

Using o1 features aka Think Deeper

Once in Copilot, use the AI chat as you would before (or like you did in ChatGPT) and you will see a “think deeper” button inside the text input box.

Using Copilot’s Think Deeper (ChatGPT model o1)

Selecting it activates the o1 reasoning model. As it processed your prompt, you also get a spinning symbol since searches and responses using o1 are more thorough that with GPT 4 and typpically take around 30 secs.

This is Microsoft’s way of letting you know that you’re in for around a 20-30 seconds wait. If you don’t need deep search so for normal use), toggle this back off to go back to the super fast GPT-4o version…

So what can o1 do then?

The deep thinker feature of Microsoft Copilot is much better for more complex tasks and research due to the o1 model ability for in depth reasoning.

As such it is simply better for solving complex issues like math, logic or science, for analysing or creating long or richer documents and reports or for code creation and debug. The best way to test this is to run two Copilot Windows side by side and test out the same prompt with and without Think Deeper enabled.

Content created with o1 is also more “accurate” with far less AI hallucinations (aka, making things up).

Why do many GPTs Hallucinate? In general, GPT models learn by mimicking patterns in their training data (huge amounts of data). The o1 model uses a different technique called reinforcement learning, whereby it's language model works things out (though it's training) by rewarding the right answers and penalising wrong ones. This takes longer through the iterative and testing process. Once done the model  moves through queries in a step-by-step fashion much like human problem  solving.

o1 limitations?

It is worth noting that o1 isn’t quite on the same level as ChatGPT in some areas. It is less effective with factual knowledge and is currently less able to search the Internet and cannot process files and images.

What about DeepSeek?

The big story this week has of course been DeepSeek, a controversial Chinese AI firm that has announced and launched their own GPT-4 and o1 rivals that have been supposedly built at a fraction of the cost of OpenAI, Google and other US models, shaking share prices, disrupting the market and rasing many questions.

What is more is more is that DeepSeek models are claimed to be more advanced and faster than GPT-4o and smarter that o1.

The advent of DeepSeek has sent shockwaves through the tech industry. Global stock markets have reeled, sparking a cascade of investigations and looming threats of bans.

Yet, the bot hasn’t been without its champions. Interestly, Microsoft – OpenAI’s top financial invester and partner – has already embraced the DeepSeek R1 reasoning model, and has integrating it into Azure AI Foundry and also GitHub.

These platforms, beloved by developers for fostering advanced AI projects, now stand as the new playground for DeepSeek’s innovative potential.

Open AI Strikes Back

In the wake of its free mobile app’s viral triumph, OpenAI’s CEO Sam Altman swiftly revealed plans to accelerate the rollout of new releases to keep ahead of its new Chinese competitor.

OpenAI are not standing still either though. Et the end of December 2024, month, they began trialing twin AI models, o3 and o3 mini. Remarkably, the former has surpassed o1 in coding, mathematics, and scientific capabilities, marking a significant advancement in their AI prowess.

There is no doubt this is an area that doesn’t stand still. By the time I click publish this post will likely already be out of date!

DeepSeek has certainly ignited an even greater sense of urgency within the already dynamic AI sector which moves and evolves on an almost daily basis.

January 21, 2025January 20, 2025

Microsoft 365 Copilot Chat: Everything you need to know including features, agents, pricing, and how to access it.

Microsoft announced last week (15th Jan) that Microsoft 365 Copilot Chat is coming to every Microsoft 365 Commercial Customer regardless of whether or not they have paid Microsoft 365 Copilot licenses and what’s more we now get access to use agents with company data grounding support. Along with it comes a new pay-as-you-go tier that allows employees to access everything from chatbots to agents without the need for a Microsoft 365 Copilot license.

While Microsoft is still confident that the full Microsoft 365 Copilot remains “our best in class personal AI assistant for work“, the new pay-as-you-go tier means organisations can start using the technology at a much lower entry point and look to address key business cases rather than going full in on Microsoft 365 Copilot. .

“Copilot Chat enables your entire workforce — from customer service representatives to marketing leads to frontline technicians — to start using Copilot and agents today”.
Jared Spataro | Chief Marketing Officer | AI at Work | Microsoft.

What is Microsoft 365 Copilot Chat?

Microsoft 365 Copilot Chat is Microsoft’s AI-powered chat feature designed to empower every person in every organisation to leverage Generative AI to make their “work lives easier and more efficient”.

For the employee, Microsoft Copilot Chat is a “personal assistant” they can chat with to get get answers, understand things better and get things done faster. Copilot Chat is It’s part of the broader Microsoft 365 Copilot suite but focuses specifically on enhancing communication and collaboration through chat.

How is Copilot Chat Different from Microsoft 365 Copilot?

The main differences between Microsoft 365 Copilot Chat and Microsoft 365 Copilot is three-fold.

Chat within Microsoft 365 Copilot provides work-grounded chat which means that Copilot can reason over data within your Microsoft 365 organisation such as files, SharePoint sites, your OneDrive, people (within Entra ID), your meetings, chat and email etc. Microsoft 365 Copilot Chat cannot access this data unless you “paste” into a chat window.
Copilot within the Office 365 Apps such as Outlook, Teams, Excel, Word etc is only available with Microsoft 365 Copilot.
Microsoft 365 Copilot is a paid add-on, where as Microsoft 365 Copilot Chat is included for free within your core Microsoft 365 licensing.

Microsoft Copilot Chat – Beyond Web Grounded Chat!

I’m personally not a fan of the name Microsoft 365 Copilot Chat because I do think it confuses people. The point I want to bring out here and why this was worthy of a post, is that previously, Copilot Chat (as it was called) only had access to data on the web and did note have the ability to leverage any of the new AI features such as Agents.

This has now changed. As the table above shows, with Microsoft 365 Copilot Chat, organisation will be able to create agents that do have access to data stored or connected to your Microsoft 365 tenant and also (and this is big) the ability for organisations to build and use autonomous agents (agents that can operate independently of a user).

The use of these new AI capabilities are paid for using a PAYG model. This means non Microsoft 365 Copilot users will have access to AI agents (for example in SharePoint) even if they themselves do not have a Microsoft 365 Copilot license.

What does Microsoft 365 Copilot Chat Provide?

Key Features of Microsoft 365 Copilot

Copilot Chat
- Free, secure AI chat powered by GPT-4 and GPT-4o.
- Ability to use Copilot Agents for automating tasks directly in the chat.
- Support for file uploads in chat for summarising documents, analysing data, and suggesting improvements.
Support for Copilot Pages
- Collaborate in real-time with AI and team members.
- Integrate content from Copilot, files, and the web.
- Create AI-generated images for campaigns and social media.
Agents
- Ability to create and use agents using natural language to automate repetitive tasks.
- PAYG / metered pricing for agents with IT control over deployment and management rather than requiring all users to have a Microsoft 365 Copilot license.
Copilot Control System
- Enterprise data protection (EDP) for privacy and security.
- Enables IT to better govern access, usage, and lifecycle of Copilot and agents.
- Allows for measurement and reporting capabilities just like other Copilot Services.

Use Case Examples

A couple of use case scenarios are;

A customer service rep can ask a customer relationship management (CRM) agent for account details before a customer meeting.
A service or field service agent can access step-by-step instructions or real-time product information from information stored in SharePoint or Dynamics 365.
A sales person can get help with positioning a product based on information on solution propositions or marketing collateral.

How much does it cost?

Understanding the charges is not super straight forward to map. For comparison though, a Microsoft 365 Copilot license costs around $30 per user per month, so use this as a basis for comparison.

In another blog post, Richard Riley, General Manager of Power Platform at Microsoft said that “usage of agents is measured in ‘messages’ and the total cost is based on the sum of messages used by your organization.“

So what does that mean? Well, Microsoft now offers two ways for organisations to access the pay-as-you-go version of Microsoft 365 Copilot Chat:

Track each “message” sent to the AI whereby each message costs $0.01, billed monthly.
Pre-buying a pack of messages. This works a bit like a mobile data plan. As an example, you can buy 25,000 messages for $200 a month

The actual cost vary based on the type of response you need with responses that need generative AI costing more than responses that don’t.

Web-based answer: Free / no-cost
Classic answer: 1 message
Generative answer: 2 messages
Answers pulling data from company’s own systems (e.g., SharePoint): 30 messages

This paid capability is of course optional and organisations can decide whether to turn it ‘on’ or ‘off’ in Copilot Studio.”

Riley introduced the concept of “autonomous actions,” describing them as “generatively orchestrated triggers, topics, data connectors, and workflows, visible in the activity map displayed in generative orchestration mode“.

These are also available as pay-as-you-go, with a cost of 25 messages each time they act.

Here’s some costed use examples…

An agent answering customer questions online could use 500 classic answers and 2,000 generative ones, costing $45 for those 4,500 messages.
Another agent answering HR questions internally using Microsoft Graph data might use 200 generative and 200 tenant Graph messages, costing 6,400 messages or $64 for the day.

This approach allows businesses to fine-tune their AI usage to meet their specific needs, addressing concerns about the high costs of deploying these tools across enterprises. It also helps cost modeling certain scenarios much easier and provides an alternative to just giving every person a $30 per month Copilot License.

Using Microsoft 365 Copilot Chat

Assuming IT have enabled this in your environment, you can try this by navigating to https://m365copilot.com or by downloading the Microsoft 365 Copilot App from your preferred app store.

January 19, 2025January 22, 2025

Comparative Analysis of Microsoft Defender for Cloud and AI and Cisco AI Defense

Introduction

The integration of artificial intelligence (AI) into enterprise environments has introduced new security concerns. As adoption of AI continues at “cautious” pace, organisations must ensure the safety of the hundreds of AI apps that employees use (or try to use) sanctioned or unsanctioned as well as any AI applications built or customised by the organisation. This affects both data governance, exposure, and leakage as well as compliance.

Last week, Cisco announced the upcoming availability of their new AI Defense Service. Whilst other provides claim similar protections, Cisco AI Defense is different. This blog aims to provide a comparison between this new service from Cisco and Microsoft’s Defender for Cloud and AI product.

I have aimed to not only compare their key features, similarities, and differences, but also to look at how both offerings can indeed help organisations based on specific business scenarios and needs.

Cisco AI Defense

Overview

Due to be released in March 2025, Cisco’s new AI Defense works slightly differently to Microsoft’s offering and is focused on securing AI applications throughout their entire lifecycle. AI Defense integrates with Cisco’s extensive network infrastructure portfolio providing specialised AI security measures.

Business and technology leaders can't afford to sacrifice safety for speed when embracing AI. In a dynamic landscape where competition is fierce, speed decides the winners. Fused into the fabric of the network, Cisco AI Defense combines the unique ability to detect and protect against threats when developing and accessing AI applications without tradeoffs". Jeetu Patel | Exec VP | Cisco.

Whilst not released yet, it will I have based this product release information I have read.

Cisco AI Defense focused on two primary areas of protection.

Accessing AI Applications: Recognising that whilst third-party AI applications can significantly boost productivity but may pose risks such as data leakage or malicious downloads. Cisco AI Defense is designed to give IT and SecOps full visibility into app usage and can enforce policies to ensure safe, secure access.
Building and Running AI Applications: Cisco acknowledge that developers require the freedom to innovate without worrying about vulnerabilities or safety issues in their AI models. AI Defense discovers your AI footprint, validates models to identify vulnerabilities, and applies guardrails to enforce security measures in real-time across both public and private clouds

Key Features

End-to-End Protection: Protects both the development and use of AI applications, ensuring safety and security throughout the AI lifecycle.
Network-Level Visibility: Leverages Cisco’s unmatched network visibility and control to detect and protect against threats.
AI Model and Application Validation: Identifies potential safety and security risks with automated vulnerability assessments.
Real-Time Protection: Offers robust real-time protection against adversarial attacks, including prompt injections, denial of service, and data leakage.
AI Cloud Visibility: Automatically inventories AI models and connected data sources across distributed environments.

Microsoft Defender for Cloud and AI

Overview

Microsoft Defender for Cloud and AI is designed to offer comprehensive security for AI applications and cloud services. Being a Microsoft product, it integrates seamlessly with Microsoft 365 and their wider cloud ecosystem, providing robust threat protection and security posture management. It also supports multi-cloud environments making it suitable for enterprise organisations.

Microsoft Defender for Cloud and AI’s primary protection areas are based upon:

Threat Protection and Security Posture Management: Microsoft Defender for Cloud and AI provides real-time threat protection for AI workloads and visibility into AI components, identifying vulnerabilities and offering built-in recommendations to strengthen security.
Integration and Continuous Monitoring: It integrates with Defender XDR for centralised alerts and continuous monitoring, ensuring security measures are enforced across hybrid and multicloud environments.

Key Features

AI Threat Protection: Provides real-time threat detection for generative AI applications, including data leakage, data poisoning, jailbreak, and credential theft.Real-time identification and mitigation of threats to generative AI applications.
AI Security Posture Management: Continuous monitoring and management of the security posture of AI applications, with automated vulnerability discovery and remediation recommendations.
Cloud App Security: Protection for SaaS applications, offering visibility into cloud app usage and protection against threats.
Prompt Evidence: Includes suspicious segments from user prompts and model responses in security alerts.
Extended Detection and Response (XDR): Integration with Defender XDR to centralise AI /workload alerts and correlate incidents for efficient incident management.
Integration with Microsoft Ecosystem: Seamlessly integrates with Azure, Microsoft 365, and other Microsoft security solutions and workloads.

Comparative Analysis

In short, both Microsoft and Cisco are providing products which complement their wider security portfolios to help customers better protect their organisations in the rapidly evolving world and adoption of AI technologies.

Similarities

AI Security: Both solutions focus on helping organisations secure AI applications and provide end-to-end visibility into their AI workloads.
Real-Time Threat Detection: Each offers real-time threat detection and protection, ensuring prompt identification and mitigation of security threats.
Integration with respective Ecosystems: Both solutions integrate with their respective broader security ecosystems (Cisco for Cisco products, Microsoft for Microsoft products).

Differences

Whilst both focus on security across the customers domain with a focus on understanding and protecting against (and keeping control of) AI based applications, there are clear, there are some subtle and unique differences.

Scopes of Use

Cisco AI Defense Specialises more in securing AI applications throughout their lifecycle including home grown developed services, where as Microsoft Defender for Cloud and AI is more focused on providing comprehensive security for both AI applications and SaaS applications.

Platform Integration

Cisco AI Defense provides deep integration with Cisco’s network infrastructure and other Cisco security products. Microsoft Defender for Cloud and AI has seamless integration with the wider Microsoft’s ecosystem, including Azure, Microsoft 365, Dynamics, Power Apps as well as being part of the wider Microsoft security solutions.

Capabilities

Cisco AI Defense places a key emphasis on AI-specific security measures that include automated vulnerability assessments and real-time protection against adversarial attacks.

Whilst similar in approach, Microsoft Defender for Cloud and AI offers broader security features, including threat protection for both AI and cloud services, and integrates with Microsoft’s XDR for centralised incident management.

When to choose which?

When to choose Cisco AI Defense

Best For: Organisations with a significant focus on AI development and deployment, particularly those heavily invested in Cisco’s network infrastructure.
Primary Benefits: AI model validation, runtime protection, and extensive integration with Cisco’s network and security products.

When to Choose Microsoft Defender for Cloud and AI

Best For: Organisations utilising a mix of AI and SaaS applications, especially those heavily invested in the Microsoft ecosystem (Azure, Microsoft 365, etc.).
Primary Benefits: Comprehensive threat protection, tight integration with Microsoft 365, Azure, Dynamics 365 and existing Microsoft security solutions.

Case Scenario: Ficticous Enterprise Organisation

Customer Profile: “A large enterprise organisation with a complex infrastructure, several hundred applications (mainly SaaS) as well as in-house and hosted custom applications running in Public Cloud (Azure), mix of productivity tools (Microsoft 365), AI-powered assistants (Microsoft Copilot and Chat GPT), multi-campus network environment (Cisco Meraki), Cloud Voice (Microsoft Teams), Space Management Tools (Cisco Spaces) and network performance monitoring (Cisco ThousandEyes).

Organisation has and uses Microsoft 365 E5. They have a contact centre based on Cisco Webex and use Microsoft Teams Meeting Rooms with Cisco endpoints. User devices as mix of Lenovo and Surface. They also use Cisco Duo. They have a Cisco EA.

They are in the middle of a Microsoft 365 Copilot pilot with around 20% of their organisation but aware that some other departments may have other shadow AI tools. They are also looking at building their own apps that will use a magnitude of AI agents and connectors.”

Cisco AI Defense vs Microsoft Defender for Cloud and AI

Given the complex infrastructure and diverse applications of this large enterprise organisation, the differences, strengths and similarities of each really stand out. Appreciating this a “made up” organisation, you can see where and why each product has its strength and merits.

Microsoft Defender for Cloud and AI

Given the extensive use of Microsoft services and the presence of Microsoft 365 E5, Microsoft Defender for Cloud and AI is highly recommended. It offers comprehensive security coverage for both AI applications and SaaS applications, integrating seamlessly with the existing Microsoft ecosystem. The core services are also included within the Microsoft 365 E5 subscription.

Key Benefits:

Broad Threat Protection: Covers both AI applications and cloud services, ensuring robust security across the organization.
Integration with Microsoft Ecosystem: Seamless integration with Azure, Microsoft 365, and the organisations other Microsoft applications and security solutions.
Centralised Management: Facilitates centralised management and monitoring, improving operational efficiency.

Cisco AI Defense

Considering the organisation’s significant investment in Cisco networking solutions and the presence of Cisco Meraki, Cisco Spaces, and Cisco ThousandEyes, Cisco AI Defense is also recommended. It provides specialised AI security measures and integrates well with Cisco’s network infrastructure.

Key Benefits:

AI-Specific Security: Focuses on securing AI applications throughout their lifecycle, providing tailored protection.
Deep Integration with Cisco Infrastructure: Enhances overall network security by integrating with Cisco’s network and security products.
Real-Time Protection: Offers robust real-time protection against adversarial attacks, ensuring continuous integrity of AI operations.

Combined Approach

Given the organisation’s diverse IT infrastructure and the need for comprehensive security, a combined approach using both Microsoft Defender for Cloud and AI and Cisco AI Defense is advisable. This dual solution ensures that all aspects of the IT infrastructure are covered, from AI applications to cloud services and networking.

By leveraging both solutions, the organization can achieve a robust, integrated security framework that covers all their IT needs, ensuring comprehensive protection and efficient management.

Budget and Management Considerations

Budget: While using both solutions might seem costly, the investment is likely justified by the enhanced security and centralised management capabilities.
Management: Both solutions offer centralised management, making it easier to oversee and control security measures. The tools are managed across the respective product suites which are already in use within the organisation minimising additonal admin / sec ops over head.

Conclusion

Cisco AI Defense and Microsoft Defender for Cloud and AI are both robust solutions tailored to different security needs and infrastructures. Understanding their strengths and integration capabilities allows organisations to make informed decisions, achieving comprehensive and integrated security frameworks.

Cisco AI Defense is new and will be available in March 2025, so please do let me know if I’ve missed anything obvious…

January 18, 2025January 23, 2025

Microsoft 365 Personal, Home and a Family get Copilot for three….

Microsoft 365 Price Rises

In a move that perhaps comes as no surprise, Microsoft has revealed a small $3 price increase per use (the first in 12 years) but is including Microsoft 365 Copilot (previously a $20 add on) to these subscriptions, which enables users to leverage Copilot in Office apps without needing a separate Copilot Pro subscription. But there is catch… See later.

I’ve not seen UK pricing as yet, but starting soon, consumers will soon see a new price of $9.99 per month for Microsoft 365 Personal and $12.99 per month for Microsoft 365 Home.

It’s not actually about Copilot through…

Oddly, Microsoft says the price increase is not actually about Copilot inclusion buy it more about aligning the prices with new features that have been added over the years such Microsoft Designer and Clipchamp, both of which have extensive AI capabilities.

Or is it…

Microsoft are offering anyone who’d rather stick to the old plan the option to buy what they new call their “classic sub tier which won’t include Copilot, but just a limited time. This, I believe will be offered as a downgrade option but will only be available for a limited time.

So… If the classic tier doesn’t include Copilot… Is the price hike about Copilot or not.. What do you think?

So what is included for Copilot in Personal and Home subscriptions?

With the introduction of Copilot, Microsoft 365 apps are getting a significant upgrade. Here’s a breakdown of the new features you will get

Word

Here we get Draft and Chat capability in Word. In draft mode you can create/ generate text from within the Copilot pane directly in Word. This works for new and existing documents and also allows your to rewrite taxt, expand on it, condense it and more. Chat mode on the other hand acts as your Word AI assistant. It can summarise and explain text, paragraphs or whole documents, suggest changes and also. Help you discover Word features such as formatting or just help you to learn new features.

PowerPoint

Here we get similar capabilities to Word. Copilot can create, restructure, change and enhance PowerPoint presentations from scratch based on user-provided criteria. It can also analyse existing Word documents (and other uploaded files) and generate a complete presentation from the information contained within it.

Excel

With most people using just a tiny fraction of what Excel can do, Copilot in Excel will help anyone analyse tables, highlight data correlations, suggest and help with new formulas based on your natural written queries, and can also generate insights to help you better reason over tables data and even entire workbooks. It is also really great for helping you format and organise data, create visualisations, and even teach you (or write) formulas for you.

OneNote

One of my favourite apps, Copilot here can assist in drafting ideas, plans, and organising information within your Notebooks. Copilot can also format content and create lists according to your criteria. What’s great is it can also do the woith your hand written notes (for those like me that use OneNote on my tablet). I find it great for handwritten meeting notes or interviews in that Copilot can then write my notes up professionally for me!

Outlook

Load of useful abilities for Copilot here in Outlook and one I think most people will use alot. Copilot in Outlook can summarise emails from friends, family, and colleagues which is nice for long email chains you have just been forwarded!

It’s also great for helping you to draftnand write an ew email or response to an email based on specific tones, lengths, and formats you set.It can also help coach you by reviewing what you have written and suggesting changes.

Copilot can pull information from other emails to provide context in threads, making it useful for managing multiple email chains.

What about Copilot Pro?

Despite the price increase, Microsoft is limiting Copilot usage under the Home and Personal subscriptions through monthly AI credits which are automatically applied to your account and reset each month (think mobile data tarrifs). They have not yet shared (that I have seen anyway) how many AI credits will be given each month.

Microsoft also offers Copilot Pro which is currently $20 /£19 a month which brings the same features as above but gives unlimited access to Copilot in Office, plus what they call boosts for image creation in tools like Designer.

I’m hoping this also gets a price reduction as it suddenly seems quite pricey for the additional capacity rather than entire features.

Conclusion.. Yes please!

To me I can’t wait to see this come to Family accounts because for me today, if I want Copilot Pro in Office for all 4 members of my family, I need to pay $80 a Month! This makes is so much more affordable and a no brainier.. bringing AI tools to its 84 millions consumer users and at a much more digestable price that with Copilot Pro.

January 13, 2025January 14, 2025

Microsoft 365 Copilot Adoption: Practice Makes Perfect

As we all get back into the flow of work following the Christmas and New Year break, Microsoft continue to announce new features for Microsoft 365 Copilot.

Microsoft 365 Copilot has been available to “everyone” to buy and use now for a year now and it’ actually hard to conceive that it only actually ben 12 months! That said, I know hundreds of organisations that are using it every day and getting a great experience from it. I also know others (and people in my own organisation that have a bit more of a “hmmmmm and it’s ok” mindset to Copilot.

As I head back into my first full week at work with Copilot at my side, it’s worth looking at just how far it has come. From taking notes and summarising content, helping me catch up things I have missed (or forgotten) and evening being my companion to help me thrash out ideas, explain things, get a different opinion – Copilot is by my side.

Copilot is like that tireless colleague who’s always ready to lend a hand, doesn’t get tired, doesn’t take a lunch a break and doesn’t need to pop out for a coffee when I need it! I often describe Copilot as a drunk intern, in that it adds huge amounts of value to my day, but it doesn’t solve every work problem, nor can it assist with every task. It can’t make decisions for me, do my executive reports, remember to do things for me (there’s other tools for that) and can’t actually do my job for me. Microsoft 365 Copilot is a tool, a powerful tool, but like any tool, its effectiveness hinges on how you use it and more importantly how you don’t!

Having helped many customers and seen the results it can have, as well as my own experience of integrating Copilot into my daily work (and personal online life) routine, it takes time. It not as simple as allocating a licensing and clicking the Copilot button. Good adoption and useful results require practice (lots), sharing what works, and an understanding of its capabilities and limitations. In this blog. I share a few little tips we have learned on the way, coupled with some tips to see value every day.

1. Results may not be instant – Practice makes perfect

You may hear people say “it is rubbish” or “it didn’t do what I thought”, or “Copilot can’t help me in my job”.

This is sometimes true, but nearly all of the time, it is simply not! Copilot can certainly help you brainstorm ideas, answer questions, explain content and even get a third person review on something you have created, but it it is not going to transform you into a master mathematician, coder, web designer or salesman overnight.

Like learning a new musical instrument (my son is learning the trumpet at the moment) or a language, it takes time (and patience) to get the hand of pretty much any tool.

Success comes (and I see it every day) by embrace the learning curve, trying new things and giving yourself room to grow alongside this technology which is constantly evolving and improving. Working with Generative AI is a totally different way of working with technology so give yourself time to work with it. There is no AI Natives (yet!).

2. Don’t get fired – Copilot for everyone but not for everything!

Think of Copilot as your co-pilot, not as the captain of your work. Copilot is there to assist you in what you do but not to take over. While it might draft a great email or executive summary, help you expand on a point or explain something, only you (as the Pilot) can ensure it aligns with your objectives and ask and that what it produces resonates with your audience.

Remember you are accountable for what Copilot produces for you – Copilot is the co-pilot. You are always in command. Copilot will remind of this, but do. Check the content, is it what you needed and asked for. Does it seem correct, read well and has it used the right content and context. If Copilot get’s it wrong, its your block on the line not Copilot’s.

Your expertise and personal touch are irreplaceable, and you are still responsible for what it produces. Don’t look silly buy not checking what it produces!

3. Remember you are human – It is not!

The Human Touch is everything. For example, when using Copilot to write or reply to a sensitive email, or when writing a personal response to something, Copilot can absolutely provide you with a solid starting point or provide guidance on how to write it.

We have all read those emails comms that are so obviously written by AI. It’s easy to spot an email from someone you know that has clearly left AI to write for them!

Empathy, nuance, and authenticity and the way in which you communicate is what makes you. It’s important to use what Copilot (or an AI) creates as a draft or a guide and ensure you inject your personality and insights to make your communication truly impactful and truly you.

4. Copilot is not a mind reader – be clear in your asks

Copilot doesn’t inherently understand the nuances of your specific situation, so back to my drunk intern analogy, you need to give it context around what you want your assistant to do.

Copilot can “summarise a report” but won’t know how you would like this summarised, the tone you woudl like, who you are summarising it for and how long you want it unless you tell it. Be explicit about the how you want the output (the goal), the context of what you need, and your expectations for how you want the output to be presented.

Remember the formula for Copilot promoting is G.C.S.E – Goal, Context, Expectations and Source.

5. Don’t leave sensitivity to chance

Microsoft 365 Copilot will adhere to your company identity and access management, respect DLP policies and even understand sensitivity labels if they are used.

Many organisations however do not use these (though are starting too), but regardless, make sure you check that you are not feeding Copilot confidential customer information when creating responses for other customers or sharing internal information that is not supposed to be shared.

People get scared that Copilot may share sensitive information. Since Copilot is the assistant and not the author, you are responsible for checking that the data you have fed it (or referenced) can be used and shared externally.

There are new tools coming to help users better protect privacy and for IT / Sec to control what Copilot accesses, but it’s still “on you”. Remember Copilot can’t get the sack – you can!

6. Copilot will not replace learning but it can help you learn.

Some like to portray that they are an expert over night with AI tools like Copilot. Sure Copilot is great at simplify complex concepts or helping you know how to do something in say Excel or Word. Copilot is also really great at helping you understand seomthing, can explain something complex “as if i am a 10 year old” and so on, but it’s not a substitute for your own learning journey.

That said, I find Copilot is great for helping you to learn something. It can help you “learn” the basics about a topic, put things into different perspectives, and even help map learning paths and helps you find resources. At the end of the day, it is still you that will learn what you are learning, but Copilot is really great at helping you learn in your way…

7. Copilot has an appauling memory

One fo the things Copilot is really bad at (by design currently) uis remembering things. This mean that not only will it not ask you how that report went, or if your customer replied to the email it helped you write.

In fact Copilot cannot (currently) evcen remeber past convrsations or preferences so once you “start a new conversation”, all history of that task you were working are forgotten.

As a tip – I tend to have a couple of chats running in parallel so I can switch between contexts as I need to. ChatGPT now has this capability to imagine* it is only time before this comes to Microsoft 365 Copilot

8. The Roadmap is every changing

The last time I looked, there was 112 new features in development and 18 that are currently “rolling out”. This AI technology is evolving rapidly and Copilot is no exception.

New features and improvements roll out regularly. It’s worth checking on the Microsoft 365 Roadmap from time to time to ensure you stay informed about what is coming. There are also a plethor of blogs like this one, user communities, webinars and formal training to help you stay abreast of the latest innovations and tips.

Knowledge is power – the more you know, the more you can leverage Copilot to your advantage.

9. Integrate Copilot into your daily routine

Consistency is key. Copilot really adds avlue when you use it little and often and when it’s seamlessly woven into your daily workflow. Here are some reaaly simple habits to form:

Start your week with a recap: Use Copilot to remind you of any emails you did not repond to last week from your peers or boss, to prepare you for your upcoming meetings, or to sugegst a date your team (rememeber it knows who works for you) are available for an afternoon off-site.
Start Your Day with Copilot: Use Copilot in the morning to outline your your day, important tasks or get you up-to-date on something. You will soon be able to schedule Copilot to do certain tasks for you.
Catch on and control your meetings: One of Copilot’s hero capabilities is to help ypou catch up on a meeting you missed, take notes for you in a meeting and even help keep the meeting flowing.
Remeber your GCSEs: Before engaging with Copilot, know what the Goal is you are trying to achieve. Give Copilot context on how you wnat it done and ensure it knows what you expect. Clear questions yield better answers.
Share and Collaborate: Encourage your team to adopt Copilot and share tips. Collective learning amplifies benefits.

The true power of Copilot lies in how you incorporate it into your daily routine:

10. Don’t Give up

You may not always get the instant results, don’t give up. Ttry again, ask others what works for them and check out help and guidance. There’s loads.

Stay Curious and ensure you experiment with different prompts and functions. You might discover new ways Copilot can assist you.
Reflect Regularly by taking time to assess how Copilot is impacting your work. Adjust your approach as needed to maximise benefits.
Share your success so other can benefit from what you have learned and what works best for you.

Final Tips

Microsoft 365 Copilot is a remarkable assistant that can amplify your productivity, spark innovation, and even make mundane tasks more manageable. But remember, it’s a tool designed to enhance your capabilities – not replace them. By using it thoughtfully, staying informed about its features, and integrating it into good work habits, you can unlock its full potential.

Technology is a force multiplier, but it’s the human element that truly makes the difference. Copilot offers incredible capabilities, but it’s up to you to wield them effectively. Use it wisely, continue to learn, and keep pushing the boundaries of what’s possible. Your proactive engagement and thoughtful application are what turn a powerful tool into transformative results. So take charge, embrace the technology, and watch how it elevates the work you do every daym, little my little, bit my bit can make a huge difference in a week.

Oh and don’t forget to share your successes with others.

January 8, 2025January 8, 2025

Phi Silica SLM coming to Windows Runtime and Copilot PCs

At CES 2025 in Las Vegas this week, Microsoft’s head of Windows devices, Pavan Davuluri, announced that Phi Silica, a Small Language Model (SLM), will be integrated into the Windows runtime as part of Copilot in the first quarter of 2025 to provide offline use and performance boosts whilst also paving the way for additional features and privacy enhancements made possible through local processing.

What’s a Language Model?

Before diving into the details, it’s important to understand what a language model is. Language models are designed to comprehend, generate, and perform human-like language tasks, having been trained on vast amounts of data. However, not all language models are the same – they come in different sizes, large and small, each with unique strengths and weaknesses tailored to specific requirements.

The main differences between small and large language models lie in their size, capabilities, and resource requirements.

LLMs are ideal for applications needing high accuracy and versatility, such as advanced search, chatbots and content generation.
SLMs are generally more suited for specific, lightweight applications, like mobile apps and edge devices and laptops such which have local NPUs like Copilot+ PCs.

SLMs are coming to Windows 11

The Phi Silica SLM, which was first showcased at Microsoft Build in Seattle in May 2024, is designed to complement the Large Language Model (LLM) that runs in the cloud allowing specific AI workloads and processing to be run locally or handed over and run in parallel with the cloud based LLMs.

Small, but mighty, on-device SLM
Microsoft

Why? Well, whilst LLMs are typically faster and more accurate, they require cloud-based operations and can be costly to run and inflict subscription fees (think Microsoft 365 Copilot). SLMs, on the other hand, can run many and other AI-driven applications and tasks locally on PCs, ensuring privacy and preventing data leakage to the cloud. However, SLMs are less sophisticated and require dedicated Neural Processing Units (NPUs) to provide these local AI capabilities. Hello Copilot+PCs.

Copilot+ PCs and AI PCs

The NPUs (Neural Processing Units) in Copilot+ PCs are designed to be highly power-efficient, capable of performing trillions of operations per second (TOPS) while consuming very little power. Specifically, on devices with Snapdragon X Elite processors, the Phi Silica model’s context processing uses only 4.8 milliwatt-hours (mWh) of energy on the NPU.

Additionally, the token iterator stage of the model shows a 56% improvement in power consumption compared to running on the CPU. This efficiency allows Phi Silica to operate without overloading the CPU and GPU, ensuring smooth performance and minimal impact on other applications.

Microsoft said that features like Windows Recall, Click-to-Do and other AI functionalities will soon be able to leverage these SLMs. Phi Silica uses a 3.3 billion parameter model, fine-tuned by Microsoft for both accuracy and speed and will. Improve performance, enhance privacy and enable more “offline” usage.

January 7, 2025January 7, 2025

The Future of AI Agents and shift to Agentic AI

In a recent podcast episode with Bill Gurley and Brad Gerstner, Satya Nadella – CEO of Microsoft, discussed a wide range of topics related to his role at Microsoft, the state of the technology, business growth and capitalism in this new “AI Era”.

The podcast which you can watch on YouTube here covered some interesting topics including the Future of AI Agents and their potential to transform how we interact with technology. In this blog (worth a listen), Satya gives his predications/insights into the future of AI Agents and emphasises that AI agents will fundamentally change the landscape of software-as-a-service (SaaS) solutions, predicting that the traditional notion of business applications will collapse in the era of agentic AI.

What is Agentic AI?

Agentic AI refers to artificial intelligence systems that can make decisions and take actions autonomously, without direct human intervention. These systems are designed to perceive their environment, reason about the best course of action, and execute tasks independently. In short these agents are designed to function as workplace teammates, capable of handling various tasks across different applications.

As example, in e-commerce platforms, instead of static, rule based chatbots, agentic AI-driven systems can track a customer’s journey, personalised recommendations, and assist with returns seamlessly without user / supervisor input. These agents will be able to actively learn from interactions, optimising the customer journey in real time and learning about user preferences.

Agentic AI typically inhibits the following features:

Autonomy: Agentic AI systems can operate independently, making decisions based on input data and predefined goals.
Adaptability: These systems can adapt to changing circumstances and inputs, adjusting their actions to achieve their objectives.
Proactivity: Agentic AI can anticipate user needs and take actions without explicit instructions, making them more proactive in their behavior.
Collaboration: In the future, agentic AI systems will be able to work together in multi-agent networks, collaborating to handle complex tasks that a single agent cannot manage alone.

Changes Ahead for AI Agents

The video / podcast is an hour and a half (but an enjoyable and informative listen). Reading between the sections, Satya talks extensively about where he sees AI Agents evolving massively through 2025. I have summarised this below.

Increasing Sophistication and Capabilities

AI agents will become increasingly sophisticated and capable, eventually replacing traditional software applications. These agents will be able to understand and anticipate user needs, providing personalised and proactive assistance. They will leverage advanced natural language processing (NLP) and machine learning algorithms to interact with users in a more human-like manner.

Autonomous AI Agents

Through 2025. we will see autonomous AI agents handle more and more complex tasks with minimal human oversight, optimising workflows and enhancing efficiency across industries. These agents will streamline workflows, manage intricate operations, and simplify everyday activities. For example, OpenAI’s “Operator Agents” will autonomously execute multi-step processes, such as scheduling meetings or managing projects.

Multi-Agent Networks

Sayta talks abiut the “future” being a place that is not about singular agents but more about networks or systems of agents where agents can discover and collaborate with other agents. These multi-agent networks will enable agents to handle tasks that they can’t do themselves by invoking other agents (agents talking to other agents). This collaborative approach will enhance the overall capabilities and efficiency of AI agents.

Vertical AI Agents

Vertical AI agents, which are specialised for specific industries, are expected to have their moment in 2025. These agents will dominate their respective fields by offering tailored solutions that address industry-specific challenges. For example, retail AI agents will act as personal shoppers, offering personalised recommendations and optimising inventory management.

Persistent Memory and Personalisation

AI systems with persistent memory will enable highly personalized interactions, transforming AI into long-term companions that adapt to user preferences and habits. This capability will allow AI agents to provide more relevant and context-aware assistance, enhancing user experiences.

Emotional Intelligence

Future AI agents are expected to possess emotional intelligence, allowing them to understand and respond to human emotions. This will enable more empathetic and effective interactions, particularly in customer service and healthcare settings.

Integration with IoT and Personal Devices

AI agents will increasingly integrate with the Internet of Things (IoT) and personal devices. This integration will enable seamless interactions across various platforms and devices, creating a more connected and efficient ecosystem. For example, AI agents in smart homes will manage household tasks, monitor energy usage, and provide personalized recommendations.

Ethical AI and Transparency

As AI agents become more prevalent, there will be a greater emphasis on ethical AI and transparency in decision-making. Ensuring that AI agents operate responsibly and transparently will be crucial for gaining user trust and acceptance. This includes addressing issues related to data privacy, bias, and accountability.

Proactive AI Agents

Proactive AI agents will anticipate user needs and take actions without explicit instructions. For example, an AI assistant might reorganize your day based on traffic updates and weather, reschedule missed appointments, and even draft personalized messages. This proactive approach will make AI agents more valuable and indispensable in daily life.

Enhanced Communication and Collaboration Tools

AI agents will enhance communication and collaboration tools, making it easier for teams to work together. These agents will facilitate real-time collaboration, manage project timelines, and provide insights to improve productivity. They will also assist in content creation, research, and workflow automation.

Shift and the of SaaS apps?

Another interesting section to listen too is at around 31 minutes, where Satya talks about his vision of how AI agents could potentially replace traditional SaaS (Software as a Service) applications. Whilst something that will not happen over night, he talked about the shift from business apps with connectors into other apps, but in an agent to agent and agent to back-end system.

We can already have connectors into applications like SAP, Dynamics etc. A great quote he used was “when was the last time any of us really went to a business application” In the AI age, we access the data in these systems from a mesh of data sources which over time, these back-end SaaS systems would eventually become obsolete as AI agents take over multi-repository CRUD (Create, Read, Update, Delete) operations. This shift would lead to the collapse of conventional business applications, with AI agents handling the core logic.

The idea will be that you simply pull information from systems through AI Agents such as looking up customer details, updating inventories, changing a contact in NetSuite CRM for example or checking delivery status for an order.

Other examples, Sayta talked about with regards AI Agents included:

Infinite Memory: He explained that infinite memory refers to the ability of AI agents to retain and recall information over extended periods, much like a human’s long-term memory. This capability will allows AI agents to build on past interactions and experiences, making them more effective and personalized in their responses and actions.

Proactive Task Management: AI agents are envisioned to operate autonomously, handling complex tasks such as processing customer returns, managing shipping invoices, and optimizing supply chain operations. This proactive approach reduces the reliance on user-initiated interactions, further diminishing the need for traditional SaaS applications.

Automation of Business Logic: Satya explained that AI agents would be able to automate many backend business processes, creating a new tier of multi-agent orchestration. This means that business logic, which is currently hardcoded into individual applications, will be managed by AI agents across multiple apps or databases and will adapt based on useage and need.

Integration with Existing Tools: Nadella highlighted the integration of Python with Excel as an example. AI agents can use Excel’s visualisation capabilities for advanced tasks, transforming it into a more intelligent and autonomous tool. This integration demonstrates how AI agents can enhance existing applications, making them more efficient and reducing the need for traditional SaaS apps.

December 11, 2024December 11, 2024

The Windows Copilot app is now a “real” app

If you are not a fan of PWA (progressive web apps), the Microsoft is bringing good news. Windows Insiders are getting a new version of the Copilot app for Windows 10 and 11 which replaces the web-based application with a new native version.

The old app (or current app if you are not a Windows Insider) is a Progressive Web App which limits some of the Windows control such as quick view that is available in native Windows Apps. recently ChatGPT published their Windows App into the Microsoft Store and this latest update from Microsoft now makes the Copilot a real app too!

In the announcement, Microsoft said that

With this update, the previous Copilot progressive web app (PWA) is replaced with a native version. After installing the Copilot app update, when you run Copilot, you will see it appear in your system tray.
Microsoft Windows Insider Team

Whilst it’s hard to notice immediately differences, after installing the updated version (1.24112.123.0) Copilot on Windows is now a “proper” app rather than a WebApp.

This also means that Quick View can be used now with Copilot which lets you move the quick view window and resize it to suit your workflow. By default, the Copilot app in Windows uses the RegisterHotKey function and sets Alt + Space keyboard shortcut to open Copilot in Quick View mode which can be used to open and close Copilot’s quick view whenever you need it.

If you need to switch / flip back to the main Copilot app window, then this can be done by clicking the icon at the top left corner of the quick view window.

Devices with the dedicated Copilot key will open the Copilot app up the main window.

December 8, 2024December 16, 2024

Streamlining Copilot Adoption: Reducing Data Oversharing in Microsoft 365

One of the concerns I often talk to organisations about, is the fear that Copilot might surface sensitive information that it should not have access to due to IT/Compliance teams not really knowing who has access to what. The phrase “Security through obscurity” is often what we heard being used.

The primary cause of this is the over-permissioning and sharing of files, which is a growing concern for organisations and one of the “blockers” often cited in Copilot Adoption.

The over-sharing problem

The ability to reason over employee data and shared organisational data is one of Microsoft 365 Copilot’s strengths over other Gen AI tools (that need feeding). These responses Copilot gives and the content it creates rely on access to data that the user already has access to across their organisation’s Microsoft 365 environment. And here often lies the problem. If an organisation has low levels of data governance, no data classification and labelling, combined with high levels of over-sharing can create real concerns for IT and Data Compliance teams.

One of the reasons that Copilot often has access to data that it “perhaps” shouldn’t have is not due to security flaw or issue across Copilot or Microsoft 365, but because files or sites have been shared too widely and have no (or the wrong) privacy and sensitivity set. Addressing this is no small task since many organisations will have million of files and tens of thousands of SharePoint and Teams sites.

Organisations and even teams within organisations often operate at various levels of maturity in governing SharePoint data. While some orgaanisations strictly monitor permissions and oversharing of content, others do not. The situation is further complicated because many people, teams and organisations have “legitimate” reasons to share “some” data widely within the organisation. This can mean users in your organisation may make choices that result in the oversharing of SharePoint content. As an example

Users may save critical files in locations accessible to a wider audience than intended.
Users may prefer sharing content with large groups rather than specific individuals.
Users might not pay close attention to permissions when uploading files.
Users may not understand how to use sensitivity labelling (if enabled) to control access.

Services such as Microsoft SharePoint and Microsoft Copilot for Microsoft 365 utilise all data to which individual users have at least View permissions, which might include broadly shared files that the user is unaware of. As a result, users might see these applications as exposing content that was overshared. Oversharing can lead to sensitive information being exposed to unintended recipients. Users, while well intentioned, might not always grasp the implications of their sharing choices. They might overlook permissions or opt for convenience over security.

As a result, it’s important to use the permission models in SharePoint to ensure the right users or groups have the right access to the right content within your organisation. The following sections describe the key steps that administrators can implement to configure their SharePoint permissions model to help prevent data oversharing.

Dealing with Oversharing

The good news is that Microsoft is adding new features to SharePoint and Purview to make it easier to see, understand and control over sharing across Microsoft 365 with a hope to help adoption efforts and wider roll out of Microsoft 365 Copilot. This includes new Data Security Posture Management (DSPM) and enhancements for Data Loss Prevention policies in Microsoft 365 Copilot, and SharePoint Advanced Management. These can help automate site access reviews at scale and add controls to restrict access to sites if they contain highly sensitive information.

Microsoft have also released a blueprint guide for organisations planning to or deploying Copilot. These are nicely tailored to adjust to those with mainly Microsoft 365 E3 and E5 licenses respectively.

These new tools IMO are going to be vital to help organisation understand and address oversharing so they feel more feel confident in their employees adopting AI tools like Microsoft 365 Copilot.

AI is really good at finding information, and it can surface more information than you would have expected. This is why it’s really important to address oversharing. Typically, these issues are a by-product of good collaboration, particularly across Teams, SharePoint sites and OneDrive.
Alex Pozin | Director of Product Marketing | Microsoft

From early 2025, Microsoft will make access to SharePoint Advanced Management (SAM) available at no extra cost to Microsoft 365 Copilot subscriptions. Outside of this, SharePoint premium (which includes SAM ) will be available at a cost of around $3 per user each month.)

New Capabilities in SharePoint Advanced Management

There are also new features for SAM that Microsoft says will provide greater control over access to SharePoint files.

New permission state reports (available now) can identify “overshared” SharePoint sites. The site access review feature can then provide a easy way to ask site owners to review and address permissions.
Restricted Content Discovery – which should start to roll out this month in public preview (December 2024), will allow IT admins to prevent Copilot from searching and processing data in specific sites for content and result generation. This does not prevent direct access to the site meaning that users can access the content directly as normal. This feature builds on the SharePoint Restricted Access Control, which was released last year, and lets IT admins restrict site access to specific sites to just “site owners” only, while also preventing Copilot from indexing and summarising files in these sites.

One of the use cases for this, are for where there are data locations containing information that needs to be contained to a set of people – such as financial reports, M&A planning, amnd other secret stuff. IT need to be confident that these locations and files will not show up in SharePoint searches and will be well out the reach of Copilot or other AI tools, essentially making sure that nobody can accidently or unintentionally be aware of, see or access the content. This is where Restricted Content Discovery comes in – locking down and hiding this information from plain site and from Copilot’s retrieval augmentation and indexing.

New Capabilities in Microsoft Purview

Microsoft are also adding new capabilities in Purview too. Purview is available as standalone or is part of Microsoft 365 E5.

Microsoft Purview is a centralised hub within Microsoft 365 that helps organisations meet regulatory and compliance requirements. It helps organisations manage their compliance obligations, protect sensitive data, and mitigate risks within their Microsoft 365 environment.

Here, there are new tools to help identify “overshared files” that can be accessed by Copilot. These includes oversharing assessments for Microsoft 365 Copilot in the Data Security Posture Management (DPSM) tool which is now in Public Preview (from December 2024) and can be accessed via the newly revamped Purview portal.

The oversharing assessments are designed to highlight data that may present exposure risk by scanning files for sensitive data and identifying data repositories such as SharePoint and Teams sites where access permissions appear to be too wide and broad. The tool will also provide recommendations to admins and site owners for ways to mitigate oversharing risk, such as adding sensitivity labels or restricting access from SharePoint.

For example, DSPM can detect and help you deal with controlling ethical behaviour in AI (example demo environment below). For all the recommendation, Microsoft provides a simple step by step “wizard” to help IT and Compliance add policies.

Microsoft Purview Data Loss Prevention for Microsoft 365 Copilot, also in public preview, enables IT and security admins to create data loss prevention (DLP) policies to exclude certain documents from being processed by Copilot based on a the file or sites sensitivity label. This applies to files held in SharePoint and OneDrive, but can be configured at other levels, such as group, site, and user, to provide more flexibility around who can access what.

Insider Risk Management has also been updated to detect “risky AI usage.” This even includes user prompts that contain sensitive information and attempts by users to access unauthorised sensitive information. What’s key to note here is that this feature is not just limited to Microsoft 365 Copilot and also also covers Copilot Studio, and ChatGPT Enterprise.

Oversharing Blue Prints

I really like this. Microsoft’s new blueprint resource pages on Microsoft Learn provide recommended approaches and guidance for organisations to help them understand, mitigate and manage oversharing during what they define as the three main stages of Microsoft 365 Copilot deployment.

Pilot [Pilot]
Wider Deployment [Deploy at Scale]
Organisational Rollout [Operate]

Microsoft provide two blueprint designs. A “foundational path” and what they call an “optimised path” that uses some of the more Microsoft 365 advanced data security and governance tools found in Microsoft 365 E5 subscriptions.

Is there funding available to help?

It depends – but most likely!

Microsoft have a Cyber Security Investment Program open to select/specialist partners like Cisilion. These provide funded workshops, assessments and proof of value deployments across key Security workloads including Microsoft Purview as well as structured Copilot pilot deployments, vision and value

Organisations should speak to their Microsoft Solutions Partner for more information. You can contact Cisilion here should you need to.

Conclusion

In many of the discussions I and my team at Cisilion have with customers, we see that almost all of the organisations we work still have concerns over data governance in the realm of AI access. Of these most expect Microsoft to help them address these whilst some have already invested in third party tools to help them get a “grip” on their data and sharing.

We have seen a plethora of customers invest/upgrade to high-tier Microsoft 365 plans (including E5 Security and Compliance) or full Microsoft 365 E5 in order to gain access to Microsoft Purview. Some argue these tools should be provided as part of their Copilot investment, so it is great to see Microsoft meeting customers in the middle and at least providing some of these tools as part of this license investment.

The issue is not Copilot per-say, but it is that Copilot with it’s ability to access compnay data is causing more organisations to double down and look at the existing issues they have of too many SharePoint Sites, too much over sharing, orphaned data (data with no owner) inadequate data classification and labeling.

By addressing security and data governance and levering the new tools available, this at least should solve one of the blockers to AI adoption.

The second is Adoption and Change Management – more on that in the next blog post!

Useful links.

Ignite 2024 on demand session. https://ignite.microsoft.com/en-US/sessions/BRK272-R1
Copilot Deployment Blueprint: https://learn.microsoft.com/en-us/copilot/microsoft-365/microsoft-365-copilot-blueprint-oversharing?wt.mc_id=MVP_309187

December 7, 2024December 8, 2024

Microsoft’s Recall hits preview on Qualcomm, Intel and AMD AI and Copilot+ PCs

Microsoft has recently expanded the testing of its innovative Recall AI feature to Intel- and AMD-powered AI and Copilot Plus PCs. Initially available on Qualcomm-powered devices only, this feature is now accessible to a broader range of devices for testing.

What is Recall?

Recall was the keynote Windows feature announced when Microsoft unleashed the Copilot+ PC when they were released in September this year.

Initially recalled due to privacy concerns this is now in Public Preview for Windows Insiders on the Dev Channel.

Recall works by taking screenshots of almost everything you do on your Copilot+ PC, (these are devices with dedicated NPUs that run at 45 Trillion Operations per Second (TOPS) or more). Recall makes it easy to search and recall past activities such as “the train route I was looking at on Tuesday” rather then scanning back through Internet search history.

This feature is entirely optional to use, but when enabled enabled, helps users find previous work, content or Internet data through natural language search or an interactive scrollable timeline.

As the user, you are completely in control of what snapshots are saved and how long for, and have the ability to delete them as needed, ensuring upmost privacy and security. Snaps shots require TPM, secure boot and Windows Hello to be active on the device and Microsoft has not access to the data which is encrypted on your device.

The power of Edge AI

Unlike services like Copilot, Recall and many of the newer Copilot+ PC features leverage local LLM models on the device as well as the NPU’s present on Copilot+ PC devices like the Surface Laptop 7 and Pro 11 range. As such when you install the #WindowsInsider Dev builds, you’ll also notice that Windows Updates installs a number of processing services as well as the Phi Silica LLM.

Recalls’ enhanced security and privacy

Microsoft has implemented many new security updates and controls to address initial concerns raised by security folk and early testers.

As I mentioned, accessing snapshots now requires Windows Hello for authentication, and the feature mandates the use of BitLocker and Secure Boot. Additionally, Recall can now automatically detects and excludes sensitive information like credit card details and passwords from being saved.

Click-to-Do and more AI features

Alongside Recall, Microsoft is also allowing Insiders on Copilot+ PCs to test out Click to Do feature, which recognise text and images in snapshots and content in screen allowing users to perform actions like copying text, invoking Copilot, saving and editing images and more. This functionality extends beyond Recall, enabling users to take actions on images and text with a simple Windows + Q key or Windows Key + mouse click.

In Paint, the new Cocreator top lets you create art and images by simply typing in text prompts. The Photos app has also been updated with new tools including Image Creator, which lets users make images from text prompts, and Restyle Image, which lets users add different artistic styles to their existing photos. You also get powerful generative erase tools which can be accessed directly from the app or from Click-To-Do.

These tools use local AI and analysis models on the Copilot+ PCs to work efficiently on the device itself through the use of the NPU.

Conclusion

Microsoft initially only made these features available for Snapdragon (ARM based) Copilot+ PCs but with this update they are continuing to u lease the new AI features in Windows 11 to more devices. The expansion of Recall to Intel and AMD Copilot+ PCs marks a step forward in enhancing user experience and productivity on this next generarion of devices.

What do you think of Recall and Click-to-Do?

November 28, 2024November 28, 2024

Facilitator agent: Live AI notes in Teams meetings & chat

Microsoft announced at Ignite, the new Facilitator agent – an update to the AI notes in Teams that works inside your meetings and chat and is designed to enhance collaboration and streamline the way teams work. It works similar to the AI generated notes after a meeting, but this works live alongside you and all participants can see it working live in the meeting.

How Facilitator works in Teams Meetings

Facilitator will take real-time notes during Teams meetings (not currently adhoc meetings or Meet Now), enabling everyone to co-author and collaborate seamlessly. This allows meeting participants to focus and engage more deeply in meetings, while ensuring alignment before the meeting concludes.

To enable this feature and use it a meeting, organisers can toggle AI-generated notes setting on or off when setting up a meeting in the Teams calendar or enable it during the meeting via the Notes section in the meeting.

Once enabled, a notification appears in the meeting chat to inform all participants. This also activates meeting transcription, with a notification to users… During the meeting, participants can click on Notes to open a pane where the AI generated live notes are created every few minutes, organised by topics and follow-up tasks.

What is nice about this is that participants can edit the notes inline or assign tasks to users, with attributions indicating whether the content is AI-generated or user-edited making these Co authored notes by humans and AI!

After the meeting ends, notes continue to be accessible in the Recap tab and are stored in the OneDrive of the user who enabled real-time notes. These notes are contextual to the meeting transcript, ensuring relevance and accuracy.

Future Capabilities in Meetings

As the Facilitator agent gets developed futrther, Microsoft say that it will be able to take on more tasks to enhance meeting effectiveness. Soon, it will also manage meetings from end-to-end, including managing agendas, moderating discussions, and handling action items automatically or semi-automatically

In early 2025, the real-time note-taking experience will also expand to Microsoft Teams Rooms. Employees will be able to invite a Teams Room to a meeting, allowing all participants to see real-time notes however, they have joined the meeting. This feature will also be available for ad-hoc meetings, enabling in-office discussions to be captured seamlessly.

How Facilitator works in Teams Chats

As of now (November 2024), the Facilitator Agent creates and maintains up-to-date summaries of what it considers valuable information within Teams chats. This includes key decisions, action items, and open questions, helping groups stay focused, align faster, and resolve issues efficiently.

AI-generated notes are automatically enabled when creating a new chat. For existing chats, users can toggle it on via the Notes icon which is shown at the top right of the chat window as shown below.

When notes are enabled, a notification appears in the group chat to inform everyone that notes are being taken in real time.

To access the notes users simply click on the Notes icon in the top right corner of the chat to show a summary of the chat thread, organised by topics with corresponding decisions, action items, and unanswered questions.

These are continuously updated as the chat conversation progresses.

Availability and access

Facilitator is already in public preview now for desktop (Windows/Mac), web, and iOS/Android. To access the public preview of the new Facilitator agent, meeting hosts need a Microsoft 365 Copilot license.

Facilitator will only be available to users that have app permission policy for Microsoft apps set to “Allow all apps”. The Facilitator App will become available soon for Admins to see and manage in Teams admin center. For more information about app permission policies, see Manage app permission policies in Microsoft Teams – Microsoft Teams | Microsoft Learn

External users cannot access AI-generated notes

Let me know if you find this helpful

TL:DR

Analyst vs. Copilot for Finance:

The Age of AI Specialists in Microsoft 365 Copilot

Microsoft 365 Researcher Agent

What can Microsoft 365 Researcher Agent do?

Use Cases for Microsoft 365 Researcher Agent

Researcher Agent Example

Microsoft 365 Analyst Agent – Data Analyst

What makes Microsoft 365 Copilot Analyst Agent special?

Microsoft 365 Analyst Agent Use Cases:

Analyst Agent Example

How Do Researcher and Analysts Agents Compare to the Standard Microsoft 365 Copilot Experience?

Analyst vs. Copilot for Finance – What’s the Difference?

Does Copilot for Finance only work with Dynamics 365?

Further Reading and Sources

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The “Agentic AI” Era

One Unified Plartform to Manage it all

Net Hardware: Faster, Smarter, and Built for AI

Security in the AI Era: Zero Trust, Everywhere, All at Once

Webex: Smarter Meetings, AI Helpers, and Cameras with a Brain

Conclusion

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Why this matters?

Real Benefits.

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AI’s Transformative Role

Immediate Impact of AI on work

Productivity Challenges

Bridging Business Needs and Human

Talent, Hiring and Employment Trends

AI’s current and future role in Work Automation

What other leaders are saying…

Summary

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Copilot announcements this week

1. Updates to Copilot Studio Message Rates

2. Rule-Based Workflows in Copilot Studio

3. Deep Reasoning in Copilot Studio

4. Two new Deep Reasoning Agents

Read more

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From Web View to Native App

What’s New in the Copilot for Windows App?

Enhanced User Interface

Intelligent Chat Management

Retained and Expanded Functionality

First thoughts on the new version

Getting the new Copilot App

Microsoft want your feedback

Conclusion

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Proposal

Concerns

Where do you stand?

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Getting Started with the New Feature

Upcoming Web Version and Limitations

Recent Updates to Copilot in Excel

Looking Ahead: More Features on the Horizon

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How to save and re-use your prompts in Copilot

Accessing Your Saved Prompts

Why this feature matters

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Copilot let’s you use it for free.

How to get Microsoft Copilot

Using o1 features aka Think Deeper

So what can o1 do then?

o1 limitations?

What about DeepSeek?