Category: Agents

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Microsoft Ignite 2025 – “The Agentic Shift”

Microsoft used Ignite 2025 to tell the world that “agents are now the primary interface for enterprise work“. The focus throughout Ignite was about evolution from chat-bots to multi-discipline teams of agents across organisations and the unlaying architectural envelopments being done to make this work.

Agents are already changing how people work, and IDC predicts there will be 1.3 billion agents by 2028. Agent 365 is the control plane for agents, extending the infrastructure you trust to manage your people to agents.

This was about spelling out the developments across platform and the unifying of intelligence layers so agents can be treated as identity‑bound workers and allow security and governance to be baked in in the same way we manage human workers today. Below is a summary of the key aspects and ingredients of this approach.

For more on the latest developments and Microsoft Research on AI Frontier Firms, check out the WorkLabs

Fabric IQ

What it is: Fabric IQ layers semantic meaning and business ontologies on top of data stores so agents reason in terms of customers, orders, assets, and events rather than raw tables.

Why it matters: Agents that lack consistent business context make brittle or risky decisions. Fabric IQ gives agents a shared vocabulary and entity model, reducing ambiguity across analytics, automation, and agent workflows.

Example: A retail replenishment agent uses Fabric IQ to translate “low stock” signals into SKU hierarchies, supplier lead times, and regional demand forecasts. The agent then creates the correct purchase order, selects the right vendor SLA, and schedules delivery windows – cutting stockouts and manual reconciliation time.

Foundry Control Plane

What it is: Foundry will become the unified platform for building, routing, and operating agents with model selection, versioning, and governance hooks built in. It includes a built‑in control plane that brings security, observability, and cost signals directly into the developer experience. It surfaces alerts, policy violations, performance issues, and budget warnings where teams already build – and exposes Microsoft Entra, Defender, and Purview controls as simple toggles so identity, data protection, and threat detection can be enabled without re‑architecting toolchains.

Why it matters: Foundry reduces model selection risk, standardises deployment patterns, and makes governance a first‑class concern rather than an afterthought. It’s the place teams certify agents, attach policies, and monitor behaviour. It means developers can ship agents that are secure from day one, remain protected through updates, and automatically flow into Agent 365 governance at deployment. By meeting teams in their existing workflows, Microsoft removes much of the friction between building agents and securing them — a much needed “fix” for an area that has tripped up many enterprises and halted mass adoption.

Example: A financial services team certifies an underwriting agent in Foundry. The control plane enforces data access policies, routes sensitive scoring to on‑prem models, and produces audit trails for regulators – enabling faster production rollouts without compromising compliance.

Agent 365

What it is: Agent 365 treats agents like employees: Entra identities, scoped permissions, lifecycle management, and telemetry. It produces a security framework for how agents should be deployed and managed within an organisation. It gives IT and SecOps teams a single, consistent way to discover, manage, and secure agents wherever they’re built.

Agents are already changing how people work, and IDC predicts there will be 1.3 billion agents by 2028. Agent 365 is the control plane for agents, extending the infrastructure you trust to manage your people to agents.

Microsoft Ignite 2025

Agent 365 extends Entra ID with the same controls organisations already use to manage their people into the agent world with a – Entra Agent ID for identity and access, Defender for threat detection and posture, and Purview for data protection and compliance. Rather than new tools, this provides the familiar surface control plane where agents can collaborate and interact with users, keeping behaviour visible inside the tools people already use.


Why it matters: When agents have identity and governance, organisations can scale fleets safely. You can onboard, revoke, and audit agents the same way you manage human users.

IT gets a central registry of every agent across the estate; developers can register third‑party or custom agents via SDKs; and security teams gain continuous monitoring, anomaly detection, and enforcement capabilities such as conditional access.

For organisations wrestling with shadow AI and governance gaps, Agent 365 is a practical answer – it treats agents as first‑class entities that must be onboarded, scoped, audited, and revoked just like human accounts.

Example: An HR department deploys multiple document‑generation agents. Agent 365 ensures each agent only accesses approved templates and employee records, preventing accidental PII exposure and making incident investigations straightforward.

Azure Copilot for Cloud Ops

What it is: Azure Copilot orchestrates specialised cloud agents for migrations, observability, remediation, and optimisation – this can turn runbooks into agent workflows.

Why it matters: Cloud operations shift from manual dashboards to intent‑driven orchestration. Agents can triage, remediate, and coordinate across services faster than human‑only teams.

Example: During a cross‑region outage, Azure Copilot coordinates agents to triage logs, roll back a faulty deployment, and provision temporary capacity – reducing mean time to recovery from hours to minutes.

Conclusion

Ignite 2025 reframeed “AI” from an add‑on to an operational fabric for every organisation as we start to transition into the next phase of AI maturity and adoption.

Microsoft’s combination of Fabric IQ, Foundry and Agent 365 creates a practical path to agentic operations for business, but success still very much depends on the fuel for AI – disciplined data modeling, governance by design, and small, measurable pilots.

Organisations that treat agents as governed, identity‑bound teammates will be the ones that gain speed and resilience fastest – those that don’t face sprawl and risk and stalled or failed initiatives.

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What is Work IQ?


Microsoft Ignite 2025 focus this year saw Microsoft fully committed to Agentic AI as the next platform layer. Across all of the briefings, keynotes, technical sessions, and partner announcements, Microsoft repeatedly emphasised that AI is no longer an add-on – and that is becoming the “operating system” for modern work.

Alongside this was the announcement of Work IQ at Ignite 2025 was probably one of the biggest impact announcements – which was announced during the day 1 keynote – hosted by Judson Althoff (CEO of Commercial Business at Microsoft) and LinkedIn CEO Ryan Roslansky.

What is Work IQ?

Work IQ was positioned as a multi-level intelligence layer that delivers company-specific, job-specific, and user-specific data to inform Microsoft 365 Copilot and agents. This was not about smarter tools, models or even a new first party agent, but instead was about Microsoft playing true to their initial vision of Copilot whereby (unlike other AI tools), about a new layer of contextual intelligence that adapts to how your organisation actually work. 

This layer actually includes Work IQ, Fabric IQ, and Foundry IQ – each designed to accelerate AI innovation and support organisations in becoming Frontier Firms. But Work IQ is the cornerstone of what this all about.

Microsoft positioned Work IQ as being built on three pillars: 

  • Inference – ability to connect dots, predict next actions, and recommend the right agent. 
  • Data – the rich knowledge inside emails, files, meetings, and chats and Entra ID  
  • Memory – your specific preferences, habits, and workflows. 

This framework enables Copilot to access data, retain memory, and understand how tasks and tools interact. Inference helps predict the most suitable action or agent for each job. 

Work IQ is deeply integrated into Microsoft 365 apps like Word and Excel, enabling Copilot to continuously learn through what Microsoft calls an AI-powered feedback loop. This loop far surpasses traditional connectors by retaining context and evolving with your business. 

Instead of reactive assistants waiting for prompts before acting, Work IQ interprets relationships, intent, and context. It connects documents, meetings, and workflows into a living map of organisational knowledge, powered by the Microsoft Graph- a competitive advantage no rival can match.  Whilst other AI’s such as ChatGPT can “plug-in” to Microsoft 365 via APIs, this is nothing compared to the power of the Microsoft Graph (which is what WorkIQ is). Work IQ (the Microsoft Graph) is about value creation inside the governance boundary. Work IQ respects permissions, compliance, and sensitivity labels, making it a trusted foundation for enterprise AI. 

Agents Powered by Work IQ

Work IQ is also the engine of the agent era. Agents can only act independently when they understand environment, history, dependencies, and intent. Without context, an agent is just a reactive assistant with a fancier name. With Work IQ, Microsoft enables true agentic behaviour – agents that can coordinate, reason, and act across the enterprise. 

This aligns with Microsoft’s broader vision of “Frontier Firms” – organisations that are human-led and agent-operated. Microsoft say that, already, more than 90% of the Fortune 500 use Microsoft 365 Copilot, and Work IQ is set to deepen that reliance by embedding intelligence into everyday workflows.  This got huge cheers at Ignite!

With Work IQ, Microsoft are raising the standard of the AI workplace – positioning itself as the core intelligence layer of the modern organisation and building the foundation of the next decade of digital work.   

What about other 3rd Party AIs?

Many of Microsoft’s Competitors are able to “plug in” to either apps though plug ins.  ChatGPT, Gemini, Salesforce, ServiceNow, Atlassian etc can all build smart vertical intelligence inside their own stack or products, but in terms of the wider enterprise context, they operate in silos. Even with APIs, they do not have the awareness, context and breadth of reach that Microsoft has with the connected Microsoft ecosystem and the Graph. They lack a unified fabric, and without it, they cannot deliver the seamless agentic experience Work IQ enables. 

Microsoft’s isn’t trying to win the AI assistant market as such; they are building the architecture for the agentic workplace. Think of it as the difference between building a smart car versus building the entire road system it drives on. 

Final Thoughts

Work IQ as the missing piece that makes Copilot more than a productivity tool. It’s the connective tissue that transforms AI from assistant to organisational intelligence. 

The real question is how quickly enterprises will adapt to this new standard, and how competitors will respond when Microsoft have just raised the bar so high. 

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AI Explained: 9 Key Concepts You Need to Know in 2025

Artificial intelligence, whilst a phrase used in most of our daily lives, can feel huge, strange, unknown, scary, exciting and sometimes even intimidating. In this post I decided I would strip back the noise and waffle and share nine crisp, usable concepts. I’ve aimed to provide clarity over jargon and give some practical examples over theory.

Before I start, many and to put into familiar brands, here are a few AI tools and brands you will of already know or at least of have heard of:

1. Common AI Tools to know about

  • ChatGPT – What really started the world of “publicly accessible” Generative AI Chat Bots. ChatGPT (version 5 is the current) is a conversational AI that generates text, pictures, and even video. It can answer questions and help with creative writing. It’s a clear example of generative AI in action, showing how large language models can produce human‑like responses. Free and Paid versions.
  • Copilot (Microsoft) – leverages many different AI models including ChatGPT, Microsoft’s own and others, can do very what ChatGPT can do, but is also integrated across line of business apps and data like Word, Excel, PowerPoint, and Windows. Copilot acts as an AI agent that helps you create, draft, analyse, and even automate tasks. It’s a practical demonstration of how AI agents and retrieval techniques can boost productivity. Free tier (ChatGPT Pro equivalent) and Premium for Consumer/Family. Microsoft 365 Copilot for Business use.
  • Google Gemini – Google’s AI assistant that blends search with generative capabilities, pulling in live information to give context‑aware answers. Free and Paid tiers.
  • GitHub Copilot – A developer‑focused AI that suggests code snippets and functions in real time. It shows how reasoning models and pattern recognition can accelerate software development.
  • MidJourney / DALL·E – Image generation tools that turn text prompts into visuals. These highlight the creative side of AI, where models learn patterns from vast datasets and apply them to new artistic outputs.
  • Perplexity – Great for research including financial data and educational content. Has free and paid versions.
  • Siri / Alexa – typically home style voice assistants that act as simpler AI agents, interpreting commands and connecting to external systems like calendars, music apps, or smart home devices. Great for simple tasks like “what is weather like today” and for linking to smart home devices – “Alexa, turn on the porch light“.

If you are just starting (or are a beginner), the easiest way to decide which AI tool to use is to match the tool to the problem you’re trying to solve. If you need help writing or brainstorming, generative text tools like ChatGPT or Copilot in Word are ideal. If you’re working with numbers or data, Copilot in Excel can analyse and visualise patterns for you. For deeply creative projects, image generators like MidJourney or DALL·E turn ideas into visuals, while GitHub Copilot accelerates coding tasks. The key is not to chase every shiny new AI release, but to ask: what am I trying to achieve, and which tool is designed for that job? If you are starting out, start small, experiment with one or two tools in their daily workflow, and build confidence before expanding into more advanced applications.

Which AI in 5: Pick the AI tool that fits your task- writing, data, images, or code—and grow from there.

2. What is Artificial Intelligence (AI)

Artificial Intelligence (AI) is not really a product though word bingo might have people say ChatGPT or Copilot (at work), but it is far more than that! AI is a broad field of computer science focused on creating systems that can perform tasks which normally require human intelligence. These tasks include many things such as recognising speech, interpreting and understanding images and videos, making decisions, and even generating creative content such as music, videos and images. As of 2025, AI is already embedded in many aspects of our everyday lives – in work and in personal life – from recommendation engines on Netflix to fraud detection in banking, to summarising meetings at work.

At its core, AI combines data, algorithms, and computing power to simulate aspects of human cognition, but it does so at a scale and speed that humans could never achieve.

AI in 5: AI is machines learning, reasoning, and acting like humans.

3. AI Agents

Right, so an AI Agent is a system designed to act autonomously in pursuit of a goal. Unlike traditional software that follows rigid instructions, agents can perceive their environment, make decisions, and take actions with or without constant human input.

For example, a customer service chatbot is an agent that listens to queries, interprets intent, and responds appropriately. More advanced agents can coordinate multiple tasks, such as scheduling meetings, analysing reports, or even controlling robots in manufacturing.

The key is autonomy: agents don’t just follow orders—they adapt to changing conditions.

AI Agents in 5: AI agents are digital helpers that think and act for you.

4. Retrieval-Augmented Generation (RAG)

RAG is a technique that makes AI more reliable by combining generative models (or sub models) with external knowledge sources such as the Web or date from corporate SharePoint sites, email etc.

Instead of relying solely on what the AI model was trained on (which may be outdated or incomplete), RAG can retrieves relevant documents or data in (near) real time and integrates them into its response.

This is especially powerful in business contexts, where accuracy and timeliness are critical – for example, pulling the latest compliance rules or product specifications from an application or data repository, before answering a query. RAG bridges the gap between static training data and dynamic, real-world knowledge.

RAG in 5: RAG = AI that looks things up from multiple sources before answering.

5. Explainable AI (XAI)

One of the biggest challenges with AI is the “black box” problem. What I mean by that is that often do not know how AI arrived at its decisions or answer when instructed.

Explainable AI addresses this by making the reasoning process transparent and understandable to humans. For instance, if an AI is being used by a bank to determine if a customer should/can get a loan or not and that AI  model rejects the loan application, XAI will highlight / explain the factors such as credit history or income that influenced the decision.

In essence this is about seeing it’s workings out. If you have used Microsofts Researcher or Analyst agent at work, you will see some of this as it does its work.

This transparency is vital in ensuring we can trust AI and is required in regulated industries like healthcare, finance, and law, where accountability and fairness are non-negotiable.

By opening this black box, XAI builds trust and ensures AI is used responsibly.

XAI in 5: XAI shows you why the AI answers the way it did, what information it used and how it made its choice.

6. Artificial Super Intelligence (ASI)

While today’s AI is powerful, it is still considered “narrow AI” – specialised in specific tasks despite the advances we see every week.

Artificial Superintelligence (ASI) is a (some say) theoretical future state where machines surpass human intelligence across every domain, from scientific discovery to emotional understanding.

Many might be thinking “The Terminator” here but in reality it is more than conceivable given the current pace of evolution that ASI could in design new technologies, solve global challenges, or even “create” beyond human imagination.

This naturally raises profound ethical and safety concerns: how do we ensure such intelligence aligns with human values and what happens if ASI becomes smarter than the humans that created it?

ASI remains speculative and there are many opinions and research on the matter, but today it is a concept that drives much of the debate around the long-term future of AI.

ASI in 5: ASI is the idea of AI being smarter than all humans in every way.

7. Reasoning Models

Traditional AI models excel at recognising patterns, but they often struggle with multi-step logic.

Reasoning models are designed to overcome this by simulating structured, logical thought processes. They can break down complex problems into smaller steps, evaluate different pathways, and arrive at conclusions in a way that mirrors human reasoning.

This makes them especially useful in domains like legal analysis, financial analysis, scientific research, or strategic planning, where answers are notjust about recognising patterns and finding information but about weighing evidence and making defensible decisions in a way similar to how we as humans might undertake such work.

Reasoning Models in 5: Reasoning models let AI think step by step like us.

8. Vector Databases

AI systems need efficient ways to store and retrieve information, and that’s where vector databases come in.

Unlike traditional databases that store data in rows and columns, vector databases store information as mathematical vectors – dense numerical representations that capture meaning and relationships.

This allows AI to perform semantic searches, finding results based on similarity of meaning rather than exact keywords. For example, if you search for “holiday by the sea,” a vector database could also return results for “beach vacation” because it understands the conceptual link.

Vector Databases in 5: Vector databases help AI find meaning, not just words.

9. Model Context Protocol (MCP)

Finally, MCP is a framework that helps AI agents connect seamlessly with external systems, APIs, and data sources. Instead of being limited to their own training data, agents using MCP can pull in live information, interact with business tools, and execute workflows across platforms. For example, an MCP-enabled agent could retrieve customer records from a CRM, analyse them, and then trigger a follow-up email campaign—all without human intervention.

MCP makes AI more versatile and practical in enterprise environments.

MCP in 5 : MCP is the bridge that connects AI to other tools.

What next and Getting Started

AI is not a single technology but a constellation of concepts – agents, RAG, XAI, ASI, reasoning models, vector databases, and MCP – that together define its capabilities and potential. Understanding these terms helps demystify AI and highlights both its current applications and future possibilities.

As AI continues to evolve, these building blocks will shape how businesses, governments, and individuals harness its power responsibly.

AI is a toolkit of ideas working together to change the world. When we look at what tool to use when, in reality there is not one better than the other it’s more about context of use, the platform you use it on, what your work provides, what you get included in your other software (for example Copilot in Windows, Office apps etc) and what task you are performing. Some AI’s are better at images, some at research and some at writing and analysis.

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Microsoft “App Builder” & “Workflow” Agents

Microsoft is expanding its Copilot Frontier Programme with two powerful new agents. These are the App Builder and Workflows Agents.

These put “app creation” and automation directly into the hands of everyday users, with zero coding needed just an idea and an ask. These new agents are designed to further democratise innovation across every person in every organisations, making it possible to build “apps” and streamline processes using nothing more than natural language.

They are rolling out in the US now and will come to UK, Canada and the other regions over the next week or so.

I’ll add a demo to this blog soon!

What are the App Builder and Workflows Agents?

Firstly, these are new, in preview for Frontier (early adopters) and may change. They are not designed to replace Power Apps or Copilot Studio but more about adding value to info workers and non developers. Here is the new agents, which you can get by going to the main Copilot page, agents and get more agents.

App Builder: A no-code agent that enables anyone to design and deploy lightweight apps in minutes. It can generate a Microsoft Lists backend if needed and is grounded in Microsoft 365 content like Word, Excel, and Teams.  These are not full blown apps that can hook into enterprise data or anything but create simple to use, functional and simple agents for things like data input, collection and look up.

Image (c) Microsoft

Workflows: An automation agent that turns everyday requests into flows across Outlook, Teams, SharePoint, Planner, and more – without needing Power Automate expertise. Again these are quite simple, but great for simple automation needs when you know what you want to do but don’t have time or want to learn / use Power Automate.

Image (c) Microsoft

Both these new agents are integrated into the Copilot Studio lite experience, ensuring they inherit Microsoft 365’s enterprise-grade security, compliance, and governance. 

How Do They Work?

These agents work like other agents but are specific functional agents. They work by:

  • Using Natural Language Prompts: users can simply describe what they need. For example “Build me a dashboard to track campaign milestones” or “Send a Teams reminder every Friday at 3pm” – and Copilot translates that into a working app or automated flow. 
  • Multi-turn Editing: Once the agent is created it can be modified, updated, refined with additional interactions without having to starting from scratch. 
  • Ensuring Seamless Integration: Outputs are instantly shareable, just like a document link, and respect existing permissions and governance.

These agents lower the barrier to innovation and help spur on what is possible. Instead of relying on IT or developers, any employee can now build tools that fit their needs whether that’s a lightweight app for tracking, or a workflow that eliminates repetitive admin. Since they are built into Microsoft 365, they inherit the same security, compliance, and governance as the rest of the platform. 

App Builder Use examples

  • Create a product launch dashboard to track milestones and assign tasks. 
  • Build a calculator app for quick cost estimates, grounded in Excel data. 
  • Generate interactive lists for project tracking, with Microsoft Lists as the backend.

Workflows agent use examples

  • Automate weekly Teams updates with deadlines pulled from Planner. 
  • Set up email reminders for approval deadlines. 
  • Manage calendar scheduling by automatically blocking time for recurring tasks. 

Current Limitations

  • Frontier Programme Only: Currently limited to participants in the Copilot Frontier Programme and need to be “deployed by IT admin” initially
  • Language Support: Available in English only. 
  • Controls: Access depends on Microsoft 365 app store settings and admin policies. 
  • Governance & Permissions: Agents respect existing role-based access controls. 
  • Scope: Aimed at designing lightweight apps and workflows; complex scenarios will still require Copilot Studio or Power Platform. 
  • Performance Throttling: Heavy usage may trigger throttling.  


Deploying the App Agent and Workflow Agent

These new agents are currently only available for organisations enrolled in the Copilot “Frontier Programme”.To access the agent, you need to go to the M365 Copilot app (or https://m365.cloud.microsoft/chat) and go to Agents. From there you should be able to see the new Agents as shown below.

NOTE: If you can’t see these new agents, you’ll need to chat to your friendly IT team as they may need to enable / deploy these agents whilst they are still in preview state. Again these are only available for organisations enrolled in the Copilot “Frontier Programme”.

Final Thoughts

The App Builder and Workflows agents represents another step forward in Microsoft’s vision of empowering everyone to innovate with AI.

Whilst these agents are far from a replacement for full-scale development or automation platforms, they provide a fast, accessible way to solve everyday problems. For organisations in the Copilot Frontier Programme, these agents are a glimpse into a future where building apps and automations is as easy as describing what you want.

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It’s Agent Mode the new way to do human-agent collaboration?

Microsoft Copilot development just doesn’t sleep… This time they have just announced “agent mode” which they claim could be game changer in the way we (humans) work with AI agents (Copilot). Called “Agent Mode” this latest update marks is not just about new features, but a significant shift in how we interact with Office apps through Copilot.

Agent Mode in Excel

What is Agent mode?

Agent Mode is Microsoft’s answer to the growing demand for intelligent, iterative workflows without needing to craft lengthy prompts. Agent Mode brings agentic reasoning into Excel and Word, (others will follow), allowing users to work along side Copilot through multi-step tasks ranging from data analysis to document creation – with a level of depth and refinement that feels like working alongside an expert.

“In the same way vibe coding has transformed software development, the latest reasoning models in Copilot unlock agentic productivity for Office artefacts.”

Sumit Chauhan |CVP |Microsoft Product Group

These are both application and context aware. As an example:

  • In Excel, Agent Mode “speaks spreadsheet” language. Whether you need to build financial models, loan calculators, resource calculators or budgets, Agent Mode in Excel means Copilot now understands the nuances of formulas, formatting, and validation. Rather than just generating outputs, it can evaluate your work, suggest fixes, and works with you until you get the result you need.
  • In Word, Agent Mode will be able to transform writing into a dialogue. Users can prompt, Copilot drafts, user can then asks clarifying questions, and Copilot will refines the content with native styling and formatting. Microsoft say this is vibe writing in action — fast, fluid, and focused.

Chat first creation…

Then, there is the new “Office Agent”, which will live inside Copilot chat. This is designed for when discussions start in a Copilot Chat, rather from within document or spreadsheet. In this context, the Office Agent will have the ability to create “proper” documents directly from your chat, using deep reasoning and live previews to guide the process and creation. These will be powered by Anthropic models and not OpenAI.

Microsoft have given (in their official article) some examples we can use.

In Excel

Financial Analysis Prompt: “Create a financial monthly close report for a bike shop business, including a breakdown of product lines across VTB, VTF, sequential, and year-over-year growth. Use standard financial formatting and best practices.”


Loan Calculator Prompt: “Build a loan calculator that computes monthly payments based on user inputs for loan amount, annual interest rate, and term in years. Generate a schedule showing month, payment, principal, interest, and remaining balance. Present the results in a clear, formatted table.”

Monthly Report Update Prompt: “Help me update this monthly report for September. Update the data table with the latest numbers from the /Sept Data Pull email. Summarise the key highlights including insights compared to last month’s /August monthly report.doc.”

In Word


Project Update Prompt: “Update the executive summary for clarity, bold all key findings, and insert a bulleted list of next steps based on the /Project update meeting. Make sure to add a conclusion“.


Document Style Prompt: “Can you clean up this document? Title case for section headers, branding updates per the ‘/Latest brand guidelines’ email, and italicize all external partner mentions. Feel free to ask if you need help identifying partners or guidelines.”

In Powerpoint (coming later)

Interestingly, Microsoft say that Copilot can now (finally) create good presentations in PowerPoint!

“PowerPoint is one of the most used tools for creating presentations, but over the last two years, AI (Copilot) has often fallen short when creating slides. Office Agent changes that. Office Agent creates tasteful, well-structured PowerPoint decks and well-researched Word documents. ”

Microsoft say that now… When you work with Copilot to create presentations you will get a totally transformed experience. It will

  • Clarify your intent
  • Conduct deep research
  • Produce high-quality content.

How to use “Agent Mode”

First thing first….. Not everyone can yet and it’s not available day one… OK now read on…

Currently, Agent Mode is available for organisations (and users) enrolled in the Frontier program for Microsoft 365 Copilot who have a Microsoft 365 Copilot license or that have Microsoft 365 Personal or Family with a Copilot Pro license.

Agent Mode works in Excel on the web but will be coming soon to desktop. Word is also coming soon.

For Excel, you will also need to install the Excel Labs add-in and choose “Agent Mode”.

Oddly, from what I have read, the Office Agent is only available for Copilot Pro subscribers on Microsoft 365 Personal or Family or Premium and not (yet) Microsoft 365 Commercial. It’s also limited to USA currently! 🙁

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Cisco Webex One 2025 – Chatbots to Agents

Watching late last night on the last day of September 2025, from my living Room (wishing I was there), I tuned into the keynote from Cisco Weex One 2025.

Every year, Cisco WebexOne feels like a pulse check on the state of collaboration from one of the global big three collaboration and meeting platform vendors. This year, incase you had been asleep for the last 12 months), Cisco made it clear: The world is shifting beyond chatbots , with the new frontier being agentic AI – autonomous digital teammates designed not just to answer questions, but to take action on our behalf. We are seeing this everywhere!

We’re squarely in the next era of AI where we’re moving from this notion of chatbots that intelligently answer our questions to agents that are going to conduct tasks and jobs almost fully autonomously on our behalf.

Jeetu Patel | President and CPO | Cisco

Whilst the event continues this week and with other global Collaboration events taking place across the globe, the focus was very much agents agents everywhere…

Webex – Agents, Agents Everywhere

Cisco unveiled a suite of new AI agents that they say feel less like bolt on AI features and more like colleagues or team mates, possible through the huge advances in AI models and reasoning in the last year alone.  These Cisco first party agents include:

Cisco Webex One 2025
  • Task Agent – Which can automatically generates action items from meeting summaries. This will be available in Q1 of 2026.
  • Notetaker Agent – which captures and summarise in-person huddles in real time without the need for a formally scheduled meeting. This will be built into Cisco RoomOS 26 and will also be Generally Available in Q1 of 2026.
  • Polling Agent – nothing to do with elections! This agent can suggests live polls mid-meeting to capture sentiment and input leveraging slido. Again also also GA in Q1 2026.
  • AI Receptionist – this will provide the ability to act as a true virtual front desk receptions for businesses. Built on Webex Calling, it will be able to handle queries, transfers, and scheduling of meetings or call backs and even handle “standard” enquiries. This will start beta testing and controlled rollout from Q1 2026. .
  • Meeting Scheduler – scan meetings and be able to suggest or proactively turn action items into automated scheduling. This should be be GA before Xmas so you don’t forget to book those new year meetings!

These subtle first party AI ingestion is not just about incremental productivity and keeping up with jones’ (though the other big two have similar), but it’s more about smart and intelligent delegation and follow up – handing off the admin so people can focus on the work that matters and not forget to follow up on meetings.

RoomOS 26: biggest update ever.

Cisco also unveiled some big updates to their RoomOS (the OS that powers their meeting room devices), claiming it is their biggest, richest release yet. Coming in this update we will see, yes more agents including:

  • Director Agent – which can anticipate meeting flow and dynamically adjusts camera views for a more engaging, cinematic experience.
  • Workspace Agent – Uses (Nvidia) AI to optimise physical workspace setups, proactively recommending improvements.
  • Audio Exclusion Zones – allows and can automatically configure digital boundaries to block out background noise and distractions using AI and noise cancelling technologies which I’d argue Cisco do better than anyone!

Again, these are subtle but important features, placing AI into meetings in a subtle yet important way. It’s all about making the meeting room experience just work with minimal manual configuration and tweaking in meeting.

Troubleshooting Gets Agentic Too

Just like with saw with AI Canvas in Cisco networking at Cisco live, Cisco have been busy behind the scenes too. 

Cisco is extending its AI Canvas into Webex Control Hub, enabling multi-domain troubleshooting through natural language.

Think of it as a collaborative whiteboard for IT teams, powered by Cisco’s Deep Network Model. This won’t be available until the back end of 2026 but brining network, security and now Collab and meetings together into a since AI canvas is going to be huge for proactive issue resolution.

For any organisation that is already invested or investing in Cisco for their infrastructure stack this is huge and a great compete angle for Cisco where together really can be better!

Expanded Open Ecosystem

Cisco clearly recognise the power of a connected eco system and meeting customers where they are in terms of the wider technology vendors and eco systems they are investing in. Cisco continues to leaning hard into openness, with more integrations that would have been unthinkable a few years back.

  • Microsoft Copilot – Yes… More Microsoft integrations. Users will be able to search across SharePoint and OneDrive directly from Webex, while Copilot users can pull in Webex meeting summaries.
  • Zoom for Cisco Rooms – Cisco are brining a huge update to how the Zoom experience works on Cisco devices, moving away from the “nasty” WebRTC experience.
  • Salesforce and Amazon CCaaS – Webex Contact Center will bring new native integration with Salesforce CRM data as well as Amazon Lex.

This isn’t Cisco versus the world in a closed eco system.. Not anymore. This is Cisco with the world and with your tech!

Customer Experience Gets Smarter

Cisco is also betting big and continuing to innovate in their Webex Contact center portfolio: I will cover more on this in a later blog, but in summary, they are adding:

  • AI Quality Management (QM) – which wl empower supervisors to coach both human and AI agents from a single platform. – GA Q1 2026.
  • Webex Contact Center for Salesforce CRM – this is already in early access now with GA expected late Q1 2026.
  • Amazon Lex Integration – Available now immediately, enabling smarter call routing and intent recognition.
  • Microsoft Teams – just mentioning as I get asked a lot. This is all ready fully supported as a Teams certified Contact Centre.

Customer experience is no longer about managing queues and IVRs. it’s about orchestrating intelligence and line of business workflow integration and automation.

My Take

WebexOne 2025, as expected was about updates and AI infusion. The focus for me was refinement in the way Cisco do best. No gizmos and pointless features just maturity, evolution and AI in the right places, along with true customer choice and openness. Cisco sprinkling of AI across their suite was all about agency—giving AI the ability to act, not just advise, which of course shifts the course of AI just being a human advisor to taking actions…  That’s also a whole other topic of conversation!

For IT, Customer Service and Business Leaders, this is all about trust: how much autonomy are we willing to give an AI agent? How much do we trust it, will out customers and who’s in control and accountable. For  users, it’s about relief: less admin, more impact and more customer impacting time.

Cisco’s bet continues to be bold, but it’s also pragmatic. By further opening up and integrating their ecosystem to Microsoft, Zoom, Salesforce, and AWS, they are acknowledging that the future of collaboration isn’t about vendor battles it’s about platform, cohesion and interconnection.

The era of chatbots is over. The era of agents has begun.

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