Not All Copilot Agents Are Created Equal
Last week, we kicked off a breakdown of Microsoft’s expanding Copilot ecosystem, focusing on what the strategy means for organizations trying to adopt AI. This week, I’m keeping the momentum going by answering one of the most common questions I hear from clients, partners, and even internal teams:
“We know we need Copilot… but where do we actually start?”
Between all the overlapping product names—Copilot Studio, Dynamics Copilots, Azure Foundry, and more—it’s easy to lose track of what each one actually does.
So, I’ve put together a quick-reference guide to help clarify your options. Whether you’re just starting with Copilot or figuring out how to scale it securely, this comparison will help you assess which path aligns best with your goals, capabilities, and licensing realities.
Three Ways to Build or Use Copilot Agents
Microsoft offers three primary ways to build or use AI agents:
Built-in Copilots – Found in products like Outlook, Teams, and Dynamics 365, these are ready-to-use and embedded directly into Microsoft apps. Some, like Word and Excel Copilot, are broadly available. Others—like Dynamics 365 Copilots—offer more advanced, role-specific capabilities. Copilot Studio also now unlocks new personas like Researcher and Analyst (see last week’s blog post).
Copilot Studio – A low-code platform for building custom agents using natural language, business rules, and connectors. It shines when paired with Power Automate, enabling copilots that can not only respond—but act.
Azure Foundry + OpenAI – The most advanced path. Foundry lets developers orchestrate agents, connect to private data, and fine-tune LLM behavior within apps or services.
Each approach supports Microsoft’s broader vision: making secure, role-aware AI part of everyday work. Let’s break them down.
| Dimension | Built-in Copilots | Copilot Studio | Azure Foundry + OpenAI |
|---|---|---|---|
| Product |  |
 |
 |
| Best Suited For | Business users and everyday professionals looking for in-app AI support | Power users and solution designers building copilots for business workflows | Dev teams and architects building enterprise-grade, embedded AI agents |
| Customization | Predefined features only; no control over logic or prompts | Custom prompts, flows, and logic using low-code tools | Full control over orchestration, memory, and behavior |
| Data Access | Integrated with Microsoft data (e.g., Outlook, CRM) | Connects to data via Power Platform connectors | Custom access via APIs, RAG, and vector embeddings |
| Where It Runs | Hosted by Microsoft inside M365/D365 apps | In your Power Platform environment and connected services | In your Azure infrastructure, tied to your app ecosystem |
| Cost Consideration | Included with most licenses; no extra infra cost | Billed by usage or capacity in Power Platform | Usage-based pricing via Azure (tokens, compute, storage) |
1. Built-in Microsoft Copilot
Built-in Copilots are the easiest entry point to Microsoft AI—baked into the apps you already use, and constantly evolving in their capabilities.
A) Out-of-the-box AI Across Microsoft 365
These include the widespread Copilots already available in Word, Excel, Teams, and Outlook—designed to assist with daily tasks like summarizing emails or generating responses.
One of the most exciting advancements here is Copilot Tuning, which lets organizations fine-tune these experiences to reflect their own terminology, workflows, and even cultural norms. It moves the experience from generic to organizationally relevant.
B) Dynamics 365 Copilots
These agents are embedded in D365 modules like Sales, Customer Service, and Finance, and are purpose-built to support role-specific outcomes.
They offer more advanced, contextual behaviors than M365 Copilots—similar to how Dynamics is a “Power Platform-plus” experience in terms of complexity and capability.
For a detailed list of the latest copilots available for Dynamics 365, check out Microsoft’s official guide.
A sneak peek from DynamicsCon: the D365 Sales Copilot can now generate live charts and summarize CRM data on demand, entirely via natural language.
When to use:
You’re already licensed for D365 or M365 and want to get quick value
You need AI features embedded in day-to-day work (e.g., email replies, lead summaries)
You don’t need to control the logic, prompts, or data sources
2. Copilot Studio
Copilot Studio is Microsoft’s low-code builder for creating custom copilots tailored to your org’s workflows. It’s flexible, approachable, and where we’re seeing the most traction.
A) Build Natural Language Workflows
Use Power Fx, connectors, and prompts to create guided flows or chatbots.
Pair with Power Automate to let copilots not just respond—but act.
Generation use-cases are rapidly expanding. Our internal Use-Case Coach, for example, uses Prompt with AI Builder to generate full HTML layouts from Dataverse prompts.
B) Adoption Momentum & Smart Licensing
Its balance of simplicity and power is driving fast adoption.
Makers can build copilots with just a user license, while message packs let you scale usage without needing to license every end user.
When to use:
You need a guided flow or chatbot tailored to your business
Your team has Power Platform skills (Power Fx, connectors, etc.)
You want to expose logic and automation using natural language
3. Azure Foundry + OpenAI
Azure Foundry is the most advanced and flexible way to build copilots. It’s designed for dev teams that want total control over how AI integrates into their systems.
A) Custom AI in Your App Stack
- Foundry lets you orchestrate agents, manage memory, and ground responses using enterprise data.
- It’s not just a chatbot—it’s a framework for building smart, embedded AI into your apps or services.
- Developers can fine-tune behavior using RAG, plugins, and OpenAI’s GPT models.
B) Scalable, Secure Intelligence
- Ideal for orgs building multi-turn agents, customer-facing agents, or AI-enhanced apps.
- Built on Azure, with full support for RBAC, plugin governance, and enterprise security.
When to use:
- You’re building an agent as part of an app, not just a chatbot
- You want full control over RAG, plugin behavior, and orchestration
- You need to access private data via APIs, embeddings, or custom indexes
In Summary
No matter which path you start with—out-of-the-box copilot, low-code customization, or full-scale automation—the key is understanding where each modality fits into your broader digital strategy. Each layer of Microsoft’s AI ecosystem is powerful on its own, but when used together, they can deliver end-to-end intelligence that adapts to both the business and the user. Keep an eye on your use cases, your audience, and your readiness to scale—because the Copilot journey isn’t one-size-fits-all.
Let Us Help!
If you’re trying to evaluate which path fits your organization—or thinking about how to expand what you’ve started—schedule time with our team. We’re happy to help explore the strategy, licensing, and implementation that fits where you are and where you’re going.
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