The Microsoft 365 Copilot Agent's Playbook: A Free 4-Part Livestream Series

Microsoft Reactor is running a four-part livestream series featuring engineers and product makers from Microsoft — direct access to the teams building the features shaping Microsoft 365 Copilot agents today. Free, live, with Q&A.

What the Series Covers

The Microsoft 365 Copilot Agent's Playbook focuses on how modern Microsoft 365 Copilot agents — including declarative agents — are built, grounded, extended, and evaluated. Each session pairs a short presentation with live demos and open Q&A. 

What you'll walk away with:

• Extending agents with Skills and actions
• Grounding responses with enterprise context using Work IQ
• Connecting MCP apps for interactive user experiences
• Evaluating and improving agent quality with Microsoft 365 Copilot Evals

The Four Sessions

🗓️ Aug 18 — Skill Up: Adding Skills to Your Agent in Microsoft 365 Copilot How Skills extend Declarative Agents with new capabilities, actions, and knowledge for your business scenarios.

🗓️ Aug 25 — Context Is Everything: Building Agents That Know Your Work Context How Work IQ helps agents understand the people, projects, and information that matter most in your organization.

🗓️ Sep 01 — MCP Apps: Bringing Interactive UI to Microsoft 365 Copilot Connecting MCP Apps to Declarative Agents, turning agent responses into actionable, interactive workflows.

🗓️ Sep 08 — Terminal First Approach to Build and Evaluate Microsoft 365 Copilot Agents A developer-first approach using M365 Agent Evals and skill-based tooling — from the command line to production readiness.

All sessions run 4:00–5:00 PM UTC. 

Read here to know more and Register Soon: The Microsoft 365 Copilot Agent's Playbook – Microsoft Reactor

Copilot Studio Harnesses in Practice: Microsoft's Free Agent Academy

If you read my last post on Copilot Studio harnesses, the natural next question is — where do I actually learn to build on one? Microsoft has the answer, and it's free: Agent Academy, a self-paced, hands-on curriculum for mastering agent building in Copilot Studio, with a dedicated track for each harness.

What Is Agent Academy?

It's a structured, mission-based training program built around a "Recruit → Operative → Commander" progression — think of it as a field-training arc for agent builders. You start as a Recruit, work through hands-on missions, and earn an official digital badge (issued through the Global AI Community) when you complete each path. 

The Recruit rank splits into two paths, one per harness, and both start from zero:

• Standard Harness — best for rule-based, predictable conversations. Broadest coverage of classic Copilot Studio: topics, Adaptive Cards, Power Fx, agent flows.
• GitHub Copilot Harness — instruction-driven. Guide agent behavior with natural-language instructions, skills, tools, and workflows instead of manually built conversation paths.

Microsoft's own guidance: start with Standard if you want the broadest foundational coverage of Copilot Studio; start with GitHub Copilot harness if you're building on the new experience today and want the instruction-driven approach directly.

Track 1: Standard Harness (13 Missions)

The original, foundational course — comprehensive and hands-on, taking you from zero to a published, licensed agent. 🧭

What you'll build:

•  Core agent concepts — LLMs, RAG, declarative vs. autonomous agents
• A declarative agent deployed into Microsoft 365 Copilot
• A packaged, reusable solution for environment management
• A custom agent grounded in your own knowledge sources
• Adaptive Cards built with Power Fx and SharePoint
• Agent Flows triggered from Adaptive Card input
• Event-based triggers for autonomous behavior
• Publishing to Microsoft Teams and Microsoft 365 Copilot
• Licensing and billing fundamentals

Track 2: GitHub Copilot Harness (Recruit NextGen)

The newer track, built specifically around the harness I covered in my last post. It intentionally reuses the same IT support business scenario as the Standard track — so you're comparing architectures, not learning a new use case from scratch. 

What's different here:

• Instead of manually authoring topics and branching logic, you describe what your agent needs to do in natural language and let Copilot Studio generate the initial agent
• You refine the result — updating the agent name, adding knowledge sources, verifying instructions
• Missions cover adding skills, tools, and workflows rather than Adaptive Cards and agent flows
• The agent lifecycle follows create → build → test → publish → monitor

 Worth flagging before you start: this track runs on Copilot Credits — consumption-based billing during natural-language authoring, Preview, and Evaluation. Manual configuration in the Build and Monitor tabs doesn't consume credits, but the billing exception available to licensed Microsoft 365 Copilot users in authenticated employee scenarios doesn't apply here — so check your environment's credit capacity before diving in. Mission 09 covers this in full, and it lines up directly with what I covered in my Copilot Credits breakdown.

Completing this path earns the Recruit NextGen badge.

What You'll Need Before Starting (Either Track)

• A Microsoft 365 Developer tenant with SharePoint enabled
• Access to Copilot Studio (trial or licensed)
• Optional: basic familiarity with SharePoint, Power Platform, or Power Fx

Each track has its own Course Setup mission to get you there.

Why This Matters

Reading about harnesses is one thing — building an actual agent, publishing it, and understanding its licensing is what turns theory into a skill you can bring to your organization. Microsoft built this as genuinely practitioner-grade training, not marketing fluff, and both tracks are free. Doing both back-to-back is also the fastest way to feel the architectural difference between topic-based authoring and instruction-driven building — rather than just reading about it. 

Read here to know more: Agent Academy – Recruit (both paths)

Standard Harness track: Recruit – Standard Harness

GitHub Copilot Harness track: Recruit – GitHub Copilot Harness

Stay tuned for more updates...

Driving AI Adoption: Microsoft's Copilot Cowork Webinar Series, Broken Down

Microsoft Community Learning has put together a useful video series covering some of the practical questions organizations are facing as they move from experimenting with AI to making Microsoft 365 Copilot and Copilot Cowork part of everyday work.

Rather than treating the playlist as simply a collection of videos, I looked at it as a snapshot of the AI adoption challenges enterprise IT and business leaders are dealing with right now.

Watch the full playlist: Driving AI Adoption with Microsoft 365 Copilot and Copilot Cowork

What's in the series?

The playlist brings together a full webinar, focused Q&A sessions, and a live AMA.

Webinar: Driving AI Adoption with Microsoft 365 Copilot and Copilot Cowork

The main webinar looks at what it takes to move beyond simply making Copilot available and instead drive meaningful adoption across an organization.

That distinction is important.

Enterprise AI adoption isn't achieved by assigning licenses and waiting for usage to appear. Organizations need to think about user readiness, business scenarios, prompting skills, measurement, governance and how AI becomes part of normal workflows.

Measuring productivity and managing Copilot Credits

One of the questions addressed in the series is how organizations can measure AI-driven productivity gains and allocate credits effectively.

This is becoming increasingly important as Microsoft's AI portfolio moves beyond a simple per-user licensing model.

Copilot Credits are the metered currency for Copilot consumption across a tenant, covering Microsoft 365 Copilot Chat sessions for users without a Copilot license, Copilot Studio agents, Dynamics 365 first-party agents, and Work IQ APIs , with organizations able to purchase via pay-as-you-go, Capacity Packs, or a Pre-Purchase Plan, and manage consumption through Microsoft 365 admin center cost-management tools.

For IT leaders, this means adoption and cost governance increasingly need to be considered together.

The question isn't simply:

How many people are using Copilot?

It becomes:

What work is being performed, how much value is being generated, and what is that work costing the organization?

That is a much more meaningful conversation for enterprise AI programs.

August 2026 Update: Cowork Makes Cost More Visible

Update — September 1, 2026

Microsoft's August Copilot update adds another practical dimension to the Copilot Credits discussion.

Cowork users can now select an effort level that balances quality, speed, and credit usage. Medium is the default for everyday work, while Light is intended for simpler tasks. High, Extra High, and Max allow Cowork more room for deeper analysis and complex reasoning, but can take longer and consume usage limits faster.

Microsoft has also expanded the /cost skill. In addition to estimating credits used for the current Cowork task session, users can now see credits used month to date, the percentage of their monthly credit limit remaining, and when that limit resets.

This makes cost management much more visible at the user level.

For enterprises scaling Cowork, there is an important principle here:

Use the right level of AI reasoning for the value and complexity of the task.

More reasoning isn't automatically better if the business outcome doesn't require it. As agentic AI becomes part of everyday work, helping users understand the relationship between task complexity, reasoning effort, business value, and consumption could become an important part of AI adoption and cost governance.

Reference: What's New in Microsoft Copilot | August 2026 – Microsoft

Saving prompts and prompt history

Another question focuses on how users can save prompts and maintain prompt history.

It may sound like a relatively small feature question, but it points to a larger adoption challenge.

Organizations need to move from individual experimentation to repeatable AI practices.

If a user discovers a highly effective prompt or workflow, the value shouldn't necessarily remain locked inside that individual's experience. The longer-term opportunity is to develop reusable patterns, guidance and organizational knowledge around effective AI interactions.

Prompt literacy therefore becomes part of the broader AI enablement conversation.

Can Copilot improve outcomes during a process?

The series also addresses how Copilot can learn from context, reason through tasks, and iteratively refine outcomes during a process.

This gets closer to the fundamental shift happening with agentic AI.

Traditional productivity tools typically respond to explicit user instructions.

Agentic experiences increasingly involve reasoning over context, planning work, using tools and iterating toward an outcome.

Microsoft's recently announced Work IQ vision illustrates this broader shift.

Work IQ provides agents with access to Microsoft 365 context including email, meetings, documents, Teams messages, and organizational context while preserving existing permissions, governance and compliance controls, and supports Agent-to-Agent (A2A), Model Context Protocol (MCP), and REST-based interaction models.

The important enterprise question is therefore not simply whether AI can generate a better answer.

It is whether AI can participate in a business process and continuously improve outcomes while remaining governed.

Live AMA: Driving AI Adoption with Microsoft 365 Copilot and Copilot Cowork

The final session is a live AMA featuring Karuana Gatimu, Director of the SCALE Experience Group at Microsoft, and Amy Dolzine, Microsoft 365 Copilot Activation Leader at EY Americas and longtime Microsoft MVP.

This session adds an important practical perspective to the technical discussion by focusing on real-world adoption, activation and how organizations bring their workforces along on the AI journey.

That human element is critical.

Technology can change quickly.

Organizational behavior generally doesn't.

The companies that succeed with AI adoption will need more than technical deployment teams. They will need leaders who can help employees understand where AI fits into their work, how to use it effectively and how to develop new ways of working around it.

Why these videos matter together

Taken individually, these videos answer very specific questions.

Taken together, they tell a much bigger story.

They highlight four challenges that every enterprise AI program eventually has to address:

1. Adoption

How do we get people to actually use AI?

2. Skills

How do we turn prompting and AI interaction into repeatable capabilities rather than individual experimentation?

3. Value

How do we demonstrate that AI is improving productivity and business outcomes?

4. Governance and Cost

How do we control usage, protect enterprise data and manage consumption as AI becomes more deeply embedded in workflows?

These are no longer separate conversations.

They are becoming one enterprise AI operating model.

Enterprise Takeaway

Organizations that separate AI adoption, governance, cost management and workforce enablement into different programs may struggle to scale successfully. The most effective AI deployments increasingly treat these as a single transformation initiative.

Copilot Cowork changes the adoption conversation

Copilot Cowork is particularly interesting because it moves the discussion beyond the traditional "AI assistant" model.

The emerging model is increasingly about delegating work to AI rather than simply asking AI questions.

That creates a different set of requirements.

Organizations need to think about:

• Which processes are suitable for AI delegation?
• What level of autonomy is appropriate?
• What enterprise data can agents access?
• How are permissions and compliance enforced?
• How is AI activity monitored?
• How are costs controlled?
• How do employees learn to work alongside agents?

So AI adoption is increasingly becoming both a people challenge and an operating-model challenge.

Where this connects with Copilot Studio

This also connects closely with the broader Microsoft agent ecosystem.

As I discussed in my earlier Copilot Studio Harness article, organizations building agents need to think about not only what an agent can do, but also how those agents consume shared AI capacity.

The Copilot Credit model makes that connection even more relevant. The same metered currency spans Copilot Studio agents, Dynamics 365 agents, Microsoft 365 Copilot Chat overage, and Work IQ APIs.

That means organizations should avoid looking at Copilot, Cowork, Copilot Studio and Work IQ as completely independent initiatives.

They increasingly form parts of a broader enterprise AI platform and consumption model.

Final Thoughts

Microsoft's Driving AI Adoption with Microsoft 365 Copilot and Copilot Cowork series is valuable because it captures the questions organizations are asking as AI moves from experimentation toward operational adoption.

The biggest lesson isn't about a particular Copilot feature.

It is that successful AI adoption requires organizations to address people, skills, business value, technology, governance and cost together.

Rolling out Copilot Cowork isn't simply about enabling another AI experience.

It is about preparing the organization for a different way of working, where employees increasingly collaborate with AI and where agents can take on increasingly meaningful pieces of work.

For organizations planning their next phase of Microsoft AI adoption, this playlist is worth watching.

Copilot Studio Harness Explained: Types, Examples, and What Each One Costs in Copilot Credits

Every agent you build in Microsoft Copilot Studio runs on a harness — and picking the right one is now a first-order architecture decision, not an afterthought. Here's a complete breakdown of what harnesses are, the three types available, and exactly how each one hits your Copilot Credits.

What Is a Harness?

You design the agent — the tools, knowledge, actions, and workflows. The AI model supplies the reasoning and generation. The harness is the runtime that sits in between: it decides when to call the model, what to send it, how to interpret what comes back, and which tool to fire next. It's invisible in the UI, but it's the thing quietly deciding how "smart" your agent actually feels — and how it gets billed.

The Three Harness Types

Standard Harness

Rule-based agents that follow the topics, conversation paths, and branching logic you explicitly define. No dynamic planning — it executes the exact structure you built.

Example: An IT onboarding agent that routes a laptop request through a fixed approval-then-provisioning flow.

Copilot Chat Harness

Built for extending Microsoft 365 Copilot itself with your organization's own knowledge, rather than standing up a separate agent.

Example: An employee onboarding assistant inside Copilot Chat that answers questions grounded in your SharePoint content.

GitHub Copilot Harness (the new one — GA August 3, 2026)

The most capable of the three. Natural-language-first authoring, deep reasoning, planning, and multi-step tool execution across files, systems, and other agents — the same engine behind Copilot Cowork and the GitHub Copilot coding agent. 

Example: An accounts-payable agent that reads incoming invoices, matches them against purchase orders, and routes exceptions for human approval — a long, multi-step process with ambiguous decision points that the Standard harness would struggle to script.

Quick pick rule: scripted and predictable → Standard. Layering AI onto Microsoft 365 Copilot → Copilot Chat. Messy, multi-step, needs reasoning and adaptation → GitHub Copilot harness. One catch either way — agents built on one harness can't be moved to another.

Harness vs. Copilot Credits

This is the part worth flagging to finance and governance before you scale adoption. Per Microsoft's Copilot Credits Guide (August 2026):

• Standard Harness — billed through Copilot Credits, but usage is generally lower and more predictable since it's just executing pre-built flows

• Copilot Chat Harness — billed through Copilot Credits, though rates don't apply to Microsoft 365 Copilot users in authenticated B2E scenarios

• GitHub Copilot Harness — billed in two stages: Creation (authoring, preview, evaluation) and Runtime (every task execution)

For the GitHub Copilot harness specifically, runtime cost is driven by four factors: 

• Models — which AI model is used, chosen for the quality/speed/cost the task demands
• Runtime — the managed cloud orchestration keeping the agent working, including long-running tasks
• Context — understanding of people, roles, and collaboration patterns drawn from emails, files, and meetings
• Tools — the actual actions taken: sending emails, updating documents, scheduling, and more

One thing that costs nothing: manual configuration work in the Build and Monitor tabs. Only LLM-powered authoring and actual agent execution draw from your credit pool.

Buying Copilot Credits

• Pay-as-you-go: $0.01/credit, billed in arrears at month-end, no upfront commitment

• Pre-Purchase Plan (P3): one-year upfront purchase with volume discounts — starting at 5% off for 300K credits, scaling up to 20% off at 300M credits

Credits pool at the tenant level across all Copilot Credit–powered experiences (Cowork, Work IQ APIs, Copilot Studio, Business Applications), so usage across the org draws from one shared balance.

The Bottom Line

Microsoft isn't just shipping a feature here — it's signaling where Copilot Studio is headed: fewer rigid flowcharts, more goal-driven agents that plan, adapt, and recover mid-task. The harness you choose shapes what your agent can do; the credit model behind it shapes what it costs. Model both before you commit to scaling an agent org-wide.

Read here to know more: Choose a harness – Microsoft Copilot Studio

Also review: Introducing a new harness for Copilot Studio

Watch here: Inside the new agent and workflow harness | Copilot Studio Updates August 2026

Also watch: Copilot Cowork Webinar & AMA – Allocating and Managing Copilot Credits

Full pricing detail: Microsoft Copilot Credits Guide – August 2026 (PDF)

Stay tuned for more updates...

Microsoft Frontier Transformation Week: Turn AI Strategy Into Action

AI strategy is one thing — deploying it at scale is another. Microsoft's next big virtual event is built to bridge exactly that gap. 

Microsoft Frontier Transformation Week is a global digital event designed for anyone taking AI from potential to production — with real-world demos, expert insights, and practical next steps. It runs across multiple regions, each on its own dates, so you can register for the one that fits your time zone

• Americas: August 11–14, 2026
• Asia/APAC: August 18–21, 2026
• China (Simplified Chinese): August 18–21, 2026
• EMEA: September 14–17, 2026

There's something for every role:

• Decision-makers — walk away with a strategy, not just a story: how to articulate your organization's AI maturity, what successful Frontier Transformation looks like in your region, and the building blocks for success
• Practitioners — go from knowing what agents can do to knowing how to deploy and optimize them, with real demos and technical best practices across Microsoft's products and solutions
• Developers — get the tools and learning to build something yourself, including highlights from Microsoft Build and new innovations to support your next project
• Small and midsize businesses — get a clear path to turning AI into business impact, with right-sized approaches and practical steps to deploy your first AI agents

Why it matters: this isn't another vision keynote — it's positioned as the bridge from AI strategy to deployable know-how, with role-based tracks and local context for your region. 

Register for your region:

• Frontier Transformation Week – Americas
• Frontier Transformation Week – Asia/APAC
• Frontier Transformation Week – China (Simplified Chinese)
• Frontier Transformation Week – EMEA

Microsoft's AI-Era Security Push: New Vision, New Platform, New Assessment, New Skills

AI is changing the physics of cybersecurity — and Microsoft just moved on four fronts at once: a new strategic vision, a new agentic security platform, an upgraded assessment tool, and a skilling series to build AI-specific defense skills. Here's the roundup. 

The Vision: Rethinking Security for the Age of AI

Microsoft Security EVP Hayete Gallot laid out why the old security playbook won't survive the AI era. Autonomous systems can now reason, adapt, and operate continuously — and attackers are moving at machine speed too. Microsoft's answer: a new "cyber stack," introduced as Project Perception, designed to continuously perceive risk across the entire digital estate, reason across massive context, and act at machine speed. 

Read more: Rethinking Security for the Age of AI

The Platform: Project Perception Enters Public Preview

The vision now has a name and a launch date. Project Perception is Microsoft's new agentic security platform — a workforce of specialized AI agents that reason over your security data, tools, and workflows to expose gaps, investigate threats, and remediate them continuously. It enters public preview on August 3, 2026, launching first inside Microsoft Defender. 🤖

• Red agents find potential attack paths and vulnerabilities before they're exploited
• Blue agents investigate findings and determine what represents real risk
• Green agents take corrective action and strengthen defenses
• Humans stay in control of every critical decision — this is agentic, not autonomous

Read more: Project Perception | Microsoft Security

The Assessment: Zero Trust Assessment Now Covers AI

Talk is one thing — measuring where you actually stand is another. The Zero Trust Assessment automates hundreds of security configuration checks across your tenant, aligned with the Secure Future Initiative and Zero Trust pillars — and it now spans seven pillars, including Infrastructure, Security Operations, and AI. ✅

• Connects to your Microsoft Entra tenant for an automated posture check
• Guides you through prioritized, actionable remediation steps
• Newly revamped Overview page for aggregated risk insights

Read more: Zero Trust Assessment Overview

The Skills: AI Red Team 101 Training Series

Once you know the risks and your posture, it's time to build the muscle. Microsoft's AI Red Team 101 is a modular training series covering generative AI vulnerabilities, attack techniques, and defenses — straight from lessons learned red-teaming 100+ generative AI products. 🎯

• Prompt injection (direct and indirect) with real-world case studies
• Single-turn and multi-turn attack techniques (like Skeleton Key and Crescendo)
• Defensive strategies and Microsoft's spotlighting techniques
• Automating red teaming at scale with PyRIT, Microsoft's open-source tool

Read more: AI Red Team Training

Stay tuned for more updates...

Microsoft Defender Challenge: Enroll and Complete Soon

Security teams today are defending across identities, endpoints, email, cloud workloads, and now AI environments too. Microsoft just launched a hands-on challenge to help you build exactly those skills. 

The Microsoft Defender Challenge is a free, curated learning experience running July 20 – August 21, 2026, focused on real-world skills across:

• Microsoft Defender XDR — the latest detection capabilities and unified incident response across identities, endpoints, email, and cloud apps
• Microsoft Sentinel — workspace architecture, data connectors, analytics rules, and building a mature SIEM/SOAR practice
• Microsoft Defender for Cloud — investigating, triaging, and responding to alerts across cloud and AI workloads

Who it's for: SOC analysts, security engineers, cloud security practitioners, and any IT pro looking to level up their security chops.

Complete the challenge on Microsoft Learn and submit the official sweepstakes entry form by August 21, 2026 for a chance to win one of 500 certification exam vouchers — 50% off toward:

• SC-200: Security Operations Analyst
• SC-500: Cloud and AI Security Engineer Associate

Access here to know more: Microsoft Defender Challenge

Microsoft's New Certification for AI-Powered IT Admins: AI Services Administrator Associate

AI isn't just a productivity layer anymore — it's mission-critical infrastructure. Microsoft just rolled out a certification built exactly for the admins who have to keep it secure, governed, and running. 

Microsoft 365 Certified: AI Services Administrator Associate validates your ability to configure, manage, secure, and govern Microsoft 365 tenants, workloads, and AI services — including Copilot, agents, and connected AI capabilities.

To earn it, you'll need to pass: Exam AB-650: Administering Microsoft 365 and AI Services (currently in beta)

• Configuring and managing Microsoft 365 tenants and workloads
• Securing and governing Copilot, agents, and connected AI capabilities
• Protecting data and information across users and agents
• Operating and continuously optimizing AI services at enterprise scale
• Collaborating across identity, security, compliance, and endpoint teams

Recommended background: experience with Microsoft 365 workloads and Microsoft Entra ID, an understanding of Defender XDR, and familiarity with Microsoft Graph PowerShell.

Access here to know more: New Microsoft 365 Certified: AI Services Administrator Associate Certification

Microsoft's New Certification for the Agentic Era: Multi-Agent AI Solutions Expert

The future of AI isn't a single model — it's systems of agents working together. Microsoft just rolled out a certification built exactly for that shift.

Microsoft Certified: Multi-Agent AI Solutions Expert validates your ability to design, build, and operate scalable, production-ready multi-agent AI solutions using Microsoft Foundry and Azure.

To earn it, you'll need to pass: Exam AI-500: Designing and Implementing Multi-Agent AI Solutions (currently in beta)

• Designing logical architecture for multi-agent solutions
• Building and integrating tool ecosystems
• Implementing multi-agent orchestration
• Evaluating, optimizing, and monitoring multi-agent solutions
• Securing, governing, and deploying multi-agent solutions

You'll first need the Azure AI Apps and Agents Developer Associate (AI-103) certification — it lays the Foundry and agent-development foundation that AI-500 builds on.

Access here to know more: New Microsoft Certified: Multi-Agent AI Solutions Expert Certification

Microsoft Launches MAI: Its Own Family of AI Models

At Build 2026, Microsoft introduced MAI (Microsoft AI) — seven in-house models spanning reasoning, coding, image, voice, and transcription, marking a shift away from its heavy reliance on OpenAI.

The flagship, MAI-Thinking-1, is a 35-billion-parameter reasoning model with a 256,000-token context window, trained entirely from scratch with no distillation from other labs. In blind testing, it was preferred over Claude Sonnet 4.6 and matched Claude Opus 4.6 on the SWE-Bench Pro benchmark.

The rest of the family includes MAI-Code-1-Flash (already in VS Code and GitHub Copilot), MAI-Image-2.5 (live in PowerPoint, ranked No. 2 on Arena.ai), MAI-Voice-2 for natural speech generation, and MAI Transcribe 1.5, which supports 43 languages.

Microsoft is emphasizing cost efficiency — an Excel-tuned MAI model reportedly matches GPT-5.4 at roughly a tenth of the cost — and is distributing the models beyond its own products via OpenRouter, Fireworks, and Baseten. A Mayo Clinic partnership for a healthcare-specific model was also announced.

For the Microsoft 365 and Copilot ecosystem, MAI signals that Microsoft is now building its own AI foundation, not just distributing others'.

Watch the MS Build video here: Microsoft AI CEO unveils 7 new AI models | Mustafa Suleyman at Microsoft Build 2026

Read below articles to know more 

Building a hill-climbing machine: Launching seven new MAI models

New MAI models in Microsoft Foundry across text, image, voice, and speech

Microsoft Copilot Expands Beyond OpenAI with Anthropic Claude

Microsoft is continuing its multi-model AI strategy by bringing Anthropic Claude models into the Microsoft Copilot ecosystem. Organizations can now leverage Claude models within Microsoft 365 Copilot and Copilot Studio for advanced reasoning, research, workflow automation, and agent-based scenarios, while still benefiting from Microsoft's enterprise-grade security, compliance, and governance capabilities.

The key benefit for organizations is flexibility. Customers can choose the most suitable AI model for different business scenarios while continuing to leverage Microsoft 365 Copilot's security, compliance, governance, and seamless integration with enterprise data. This enables better outcomes for research, reasoning, automation, content creation, and custom AI agents.

Read here to know more: Anthropic joins the multi-model lineup in Microsoft Copilot Studio

Also review: Anthropic models in Microsoft Online Services | Microsoft Learn

Keep a tab on the Microsoft 365 Copilot Blog for latest updates.

Microsoft Scout: Your Always-On AI Agent Has Arrived

Microsoft just introduced Microsoft Scout — its first "Autopilot" agent and a genuinely new category in the AI agent space.

What is an Autopilot? Autopilots are always-on agents that work autonomously, with their own identity, and act on your behalf — staying active in the background without needing to be prompted each time.

What does Scout actually do? Scout is integrated across Microsoft 365 apps — Teams, Outlook, OneDrive, and SharePoint — and works across cloud, desktop, and web. It can proactively schedule meetings across time zones, flag important meetings, generate prep materials, block calendar time for upcoming deliverables, and surface risks like stalled decisions before they become blockers.

The intelligence layer: Work IQ Over time, Scout builds context powered by Work IQ — learning how you work, what you care about, and what needs to happen next — becoming more useful and aligned to your priorities.

Enterprise-ready from day one Every agent operates under its own governed Entra identity, credentials are scoped to the task at hand and redacted from logs, and Microsoft Purview data protection policies are enforced in the moment — before anything is sent or written.

How to get it Scout is currently available in private preview and through Frontier organizations. Access requires Frontier enrollment, Intune policy configuration, and a GitHub Copilot license.

Read here to know more: Introducing Microsoft Scout: Your always-on personal agent

Microsoft AI Skills Fest is here !

Microsoft AI Skills Fest runs June 8–12, 2026, online and open to everyone — whether you're a developer, student, business professional, or just getting started with AI. The week is packed with live shows, expert sessions, hands-on learning, and role-based playlists designed to help you build AI skills you can actually use straight away. Plus, register before June 8 and you get two sweepstakes entries for a chance to win prizes, including a VIP experience at Microsoft Ignite 2026 — and complete a playlist to earn a Credly badge or a Microsoft Certification exam voucher.

Register here: Microsoft AI Skills Fest

Stay tuned for more updates...

Microsoft Build 2026 is just around the corner!

Microsoft Build 2026 is coming up on June 2–3, 2026, and it's open for everyone — whether you're a developer, tech enthusiast, or just curious about the future of AI and technology. The event takes place at Fort Mason Center, San Francisco, and is also available online for free so anyone around the world can tune in. Expect hands-on sessions, live demos, and deep dives into AI, Azure, GitHub, Copilot, and the latest Microsoft tools — all designed to help you learn, grow, and stay ahead in tech. 

Register here: Microsoft Build 2026

Agent Academy Live

Build production ready AI agents with Microsoft Copilot Studio. Agent Academy Live is a one-day free virtual conference designed to help developers, builders, and architects move from their first agent to production-ready solutions. Join Microsoft engineers, product leaders, MVPs, and community members for practical sessions on real agent patterns, governance, and architecture. 

Event is scheduled for May 12, 2026 | 8:30 AM – 2:30 PM PT 

Register here: Agent Academy Live