AI agents are suddenly the talk of the tech world — and for good reason. These smart digital assistants are reshaping how businesses work, collaborate, and serve customers.
AI agents in Microsoft 365 hit the mainstream in mid-2025, with the launch of the Agent Store and expanded Copilot capabilities announced at Microsoft Build in May. Since then, they’ve become a hot topic across business and tech circles — and they’re already embedded in the tools many teams use every day.
In this blog, Essential Tech is here to help you understand what AI agents are and why they matter.
What is an AI Agent?
An AI agent is a smart software assistant that understands your goals, plans tasks, and takes action using tools like email, spreadsheets, and chat. Unlike chatbots, which follow fixed scripts, AI agents can reason, adapt, and work across apps — often completing tasks without human input.
Where you’ll find them in Microsoft 365
Copilot in Word, Excel, Outlook, PowerPoint, and Teams
Used to draft emails, summarise meetings, analyse data, and more
Copilot Studio
Used to build custom agents — like a customer service agent that handles chats and escalates issues
Agent Store (launched May 2025)
Offers over 70 prebuilt agents developed by Microsoft and trusted partners and accessible via Copilot Chat. These cover use cases like Human Resources onboarding, IT support, research, and more
Embedded agents in Teams and Viva
Used to summarise conversations, surface expertise, and support collaboration
Example: Customer Service Agent
Imagine a customer service agent built in Copilot Studio. It monitors incoming chats, answers FAQs, escalates complex issues, and even drafts follow-up emails — all within Teams or Outlook. No more juggling inboxes or repeating the same answers. The agent handles the routine, so your team can focus on other tasks.
Here’s how you’d set one up:
- Define the goal
→ “Respond to customer queries, answer FAQs, and escalate complex issues.” - Choose a template or start from scratch
→ Copilot Studio offers prebuilt flows for customer service, or you can build your own. - Design the conversation flow
→ Add triggers (e.g. “new chat received”), define responses, and set escalation rules. - Connect to data sources
→ Link to your knowledge base, CRM, or FAQ documents so the agent can pull accurate info. - Test and refine
→ Simulate conversations, adjust tone, and make sure the agent handles edge cases smoothly. - Deploy across channels
→ Publish the agent to Microsoft Teams, your website, or other platforms. - Monitor and improve
→ Use built-in analytics to track performance and update responses as needed.
What about more complex agents?
For more advanced use cases — like coordinating across departments, automating multi-step workflows, or integrating with external systems — businesses can:
- Use Copilot Studio’s advanced logic tools to build layered flows
- Connect agents to Power Automate, Dataverse, or external APIs
- Define role-based access and security boundaries
- Incorporate adaptive cards, custom prompts, and plugin actions
- Work with developers to tailor agents to business processes
These agents can handle tasks like onboarding, reporting, compliance checks, or even internal service desk triage — all with minimal manual input.
Why it matters for business
AI agents help businesses save time, boost accuracy, and deliver smarter service — all without needing extra headcount or developer skills. With Copilot Studio and built-in templates, it’s easy to start small and scale up. They’re not just hype — they’re here, accessible, and ready to work.
Want to learn more?
If you’re a Microsoft 365 subscriber, you already have access to built-in agents through Copilot. To explore custom agents:
- Open Copilot Studio via Microsoft 365 or Power Platform
- Choose a template or start from scratch
- Define your goal (e.g. customer support, internal reporting)
- Test, refine, and deploy — or ask your IT team or Essential tech to help
Want to learn more or explore what’s possible for your business? Contact us.
We’ll help you design, build, and deploy agents that actually work — saving time, scaling service, and unlocking real value from your technology.