AI Agents Made Easy: Choosing between Microsoft 365 Copilot (Extended), Microsoft Copilot Studio and Azure AI Foundry

Summary

·      Microsoft offers three distinct AI agent development tools – Microsoft 365 Copilot (Extended), Copilot Studio, and Azure AI Foundry – each catering to different needs.

·      Microsoft 365 Copilot (Extended) is ideal for enhancing internal workflows, leveraging Microsoft Graph and enterprise data with limited customization.

·      Copilot Studio provides a low-code environment for building custom AI agents with workflow automation, external integrations, and more control over business logic.

·      Azure AI Foundry is a developer-first platform for building enterprise-grade AI solutions, offering full control over models, data orchestration, and advanced AI capabilities.

·      The choice depends on three factors – the type of agent needed, the technical skill level of your team, and the level of control required over AI architecture.

·      Copilot Studio and Azure AI Foundry can be used together, allowing organizations to start with low-code AI solutions and scale to fully customized enterprise AI applications as needed.

AI agents are becoming indispensable in modern enterprises, transforming the way businesses automate tasks, enhance productivity, and interact with users. As organizations adopt AI-driven solutions, the complexity of choosing the right tools for building these agents has also increased. Microsoft offers a range of solutions for developing autonomous agents, but navigating these options can be overwhelming.

With Microsoft 365 Copilot (Extended), Microsoft Copilot Studio, and Azure AI Foundry, businesses have powerful yet distinct tools at their disposal. However, understanding which one best aligns with specific needs isn’t always straightforward. Some tools cater to users with no coding experience, while others provide deep control over models and data pipelines.

This article aims to break down these choices, helping you identify the right approach based on three key considerations:

1. Type of agent needed – Will your agent operate within Microsoft 365 or as a standalone solution?
2. Maker skills – Do you need a natural language-driven interface, a low-code builder, or a code-first development environment?
3. Level of control – How much flexibility do you require in defining the agent’s knowledge, orchestration, and user experience?

Understanding the Two Main Types of Agents

When choosing the right AI agent development approach, the first key distinction to make is whether you need an extension of Microsoft 365 Copilot or a custom standalone agent. These two categories determine where and how your AI agent will operate, as well as the level of flexibility and control you’ll have.

Extending Microsoft 365 Copilot

This approach involves building autonomous agents that function within the Microsoft 365 Copilot interface, enhancing its existing capabilities. These agents leverage Microsoft Graph data, meaning they can access and process information from across an organization's Microsoft 365 environment—such as emails, documents, calendars, and Teams conversations.

Since these agents inherit the security and authentication framework of Microsoft 365, they are best suited for internal, enterprise-wide use cases. Employees can interact with these agents securely within their existing workflows, enabling automation, document retrieval, and business process improvements without needing to switch platforms. While extending Microsoft 365 Copilot simplifies agent creation, it also means that control over certain aspects—such as the underlying AI model and user interface—remains limited.

Custom Standalone Agents

Standalone agents operate independently of Microsoft 365 and can be deployed across a variety of environments, including external, customer-facing applications. These agents are ideal for businesses that require AI-driven solutions outside of Microsoft’s ecosystem, such as chatbots for websites, virtual assistants for customer support, or AI-powered automation integrated with third-party services.

With a standalone agent, businesses gain greater flexibility and control over every aspect of the agent’s architecture. They can customize the AI model, knowledge base, integration points, and even deploy the agent on different platforms, including mobile apps, web applications, and other digital services.

Choosing between these two types of agents is the first step in determining which Microsoft tool is best suited for your needs. If your primary goal is to enhance Microsoft 365 Copilot for internal users, extending its capabilities may be the right approach. However, if you need a fully custom AI solution with external reach, a standalone agent will provide the control and scalability required.

Selecting the right approach for building AI agents requires careful consideration of your specific needs and capabilities. Three critical factors will help guide your decision: Type of Agent Needed, Maker Skills, and Level of Control Needed.

Key Considerations for Choosing an Agent-Building Approach

Type of Agent Needed

The first step is to determine whether your AI agent will be integrated within the Microsoft 365 ecosystem or operate as a custom, standalone solution. This choice directly impacts the tools you’ll use and the control you’ll have over the agent.

• Internal (Microsoft 365-integrated) Agents - These agents extend the capabilities of Microsoft 365 Copilot, offering seamless integration with existing Microsoft applications and data. They are ideal for internal business processes, leveraging Microsoft’s secure environment.
• Custom/External Agents - If your goal is to build AI solutions for customer-facing applications or systems outside of Microsoft 365, standalone agents provide the flexibility to operate independently. This approach is suited for companies looking to deploy AI across multiple channels and third-party platforms.

Maker Skills

The skill level of your team influences which tool is the best fit. Microsoft provides a spectrum of options, each catering to different levels of expertise:

• Agent Builder - Designed for end-users with no coding experience, Agent Builder offers a natural language interface. Users can create simple AI agents by describing tasks and workflows in plain language.
• Copilot Studio - A low-code, drag-and-drop interface for makers with basic technical skills. It enables rapid development of AI agents through intuitive tools and templates. Copilot Studio bridges the gap between non-technical users and professional developers.
• Azure AI Foundry - This code-first environment is tailored for developers and data scientists who need full control over AI models, data integration, and advanced customizations. It requires expertise in tools like GitHub, Visual Studio, and programming languages such as Python or C#.

Level of Control Needed

One of the most important things to assess is to fully understand the level of control you require from your AI agent. The anatomy of an agent includes:

• Instructions: Defining the agent’s tone, behavior, and purpose.
• Knowledge: Accessing specific data sources and information.
• Actions: Automating tasks and workflows.
• Orchestration: Managing how the agent interacts with different systems.
• Foundational Models: Leveraging AI models.
• User Experience: Customizing the interface and interactions.

The degree of control over these components varies by tool. On a spectrum between natural language (no code) and code first approach you have two extremes:

• Microsoft 365 Copilot Extensions - Offer lower control, as the core AI model and user interface are managed by Microsoft. Users can customize instructions, knowledge, and actions within the existing framework.
• Azure AI Foundry - Provides full control, allowing you to define every aspect of the agent’s architecture, from custom models and orchestration to user experience. This approach is suited for complex, enterprise-grade AI solutions.

Extending Microsoft 365 Copilot: A Closer Look

Building AI agents within Microsoft 365 Copilot follows a declarative approach, meaning users define an agent’s instructions, knowledge, and actions, while Microsoft manages the orchestration, AI model, and user experience. These "declarative agents" are tightly integrated into the Copilot UI, allowing organizations to enhance Copilot’s capabilities while staying within Microsoft’s ecosystem.

Benefits of Extending Microsoft 365 Copilot

Here are some of the advantages from which organizations benefit when using Microsoft 365 Copilot:

• Built-in AI Capabilities: These agents use GPT-4o, the same model that powers Microsoft 365 Copilot, ensuring high-quality natural language processing without requiring additional AI model management.
• Seamless Integration: Agents operate within the existing Copilot interface, providing a familiar user experience for employees without requiring new applications.
• Business Data Connectivity: Agents can securely connect to internal data sources via Microsoft Graph, allowing them to retrieve and process information from Outlook, SharePoint, Teams, and other Microsoft 365 services.
• Workflow Automation: Users can define custom actions, enabling AI-driven automation within business processes, such as pulling reports, summarizing emails, or executing structured workflows.

What Users Can Control

While Microsoft 365 Copilot manages core AI functionalities, users still have control over key agent behaviors:

• Instructions: Users can tailor tone, personality, and behavior to align with company guidelines and communication preferences.
• Knowledge: Agents can connect to internal knowledge bases, SharePoint libraries, Teams messages, and other enterprise data sources, ensuring they provide relevant responses.
• Triggers, Actions, and Workflows: Organizations can define specific event triggers and automate responses, such as generating reports, summarizing emails, or executing predefined workflows.

What Users Cannot Control

Despite these customization options, extending Microsoft 365 Copilot comes with some limitations:

• Orchestration: Microsoft’s backend manages the conversation flow, meaning users cannot modify how the agent processes queries.
• Foundational Models: Agents rely on Microsoft’s GPT-4o without the ability to fine-tune models or integrate external AI architectures.
• User Experience: The agent must operate within the Copilot chat interface, limiting UI customization.

Creating Agents in Microsoft 365 Copilot

Microsoft provides multiple ways to create and manage Copilot extensions:

1. Using the "Get Agents" Feature: Users can access pre-built AI agents within Microsoft 365 Copilot and modify them based on organizational needs.
2. Creating Agents via Natural Language: Copilot allows users to define simple AI agents by describing their functionality in plain language, making it accessible to non-technical users.
3. Building Agents Directly in SharePoint: Agents can be embedded into SharePoint-based workflows, enhancing document and content management with AI-driven interactions.

Extending Agents with Copilot Studio

For more advanced customization, Microsoft Copilot Studio allows users to extend Copilot agents with:

• Custom workflows and automation beyond what’s possible in the default Copilot experience.
• Integration with third-party applications such as ServiceNow, SAP, or Salesforce.
• More complex decision trees and conversation logic through low-code drag-and-drop tools.

A Code-First Approach with the Teams Toolkit

For developers requiring deeper integration, Microsoft Teams Toolkit provides a code-first option to build advanced extensions. This allows for:

• Custom connectors and plugins beyond Microsoft’s ecosystem.
• AI-driven workflows integrated with external APIs.
• More granular control over permissions and security when interacting with sensitive business data.

Extending Microsoft 365 Copilot is the best choice for organizations looking to enhance internal workflows, automate tasks, and leverage enterprise data while staying within the Microsoft ecosystem.

While users cannot modify the AI model or interface, they still control knowledge, behavior, and workflow automation, with a Microsoft Copilot Studio build and Teams Toolkit they can create responsible AI that handles needed workflows.

Building Custom Agents: Gaining Full Control

For organizations that need AI agents beyond the Microsoft 365 ecosystem, building a custom standalone agent provides greater flexibility and control.

Whether you need an agent that integrates with external applications, serves public-facing users, or requires advanced customization, Microsoft offers two primary approaches: low-code with Copilot Studio and code-first with Azure AI Foundry.

Reasons for Building Custom Agents

Organizations opt for custom AI agents when they require:

• Publishing to channels outside Microsoft 365 – Unlike Copilot extensions, which are limited to Microsoft 365 applications, standalone agents can be deployed on websites, mobile apps, chat platforms (e.g., WhatsApp, Slack), and other enterprise applications.
• Full control over the agent’s architecture – Custom agents allow businesses to define their own data sources, conversation flows, AI models, and integrations, ensuring a tailored solution that aligns with business goals.

Low-Code Approach with Copilot Studio

Teams that want to build custom AI agents with minimal coding should consider to purchase Microsoft Copilot Studio offers an intuitive, low-code platform.

Key Capabilities

• Pre-built templates – Copilot Studio provides ready-made agent templates for use cases such as customer support, HR automation, and IT helpdesks, allowing businesses to get started quickly.
• Drag-and-drop interface – Users can visually design conversation flows, business logic, and data integrations without writing extensive code.
• Connect to non-Microsoft systems – Agents can integrate with third-party applications like ServiceNow, SAP, and Salesforce, enabling cross-platform automation.

Advanced Customization Options

• Control over knowledge sources – Unlike Microsoft 365 Copilot extensions, Copilot Studio agents can fetch data from external APIs, databases, and knowledge bases beyond Microsoft Graph.
• Actionable AI – Agents can be configured to trigger workflows, execute backend tasks, and automate business processes in response to user inputs.
• Autonomous capabilities – Some agents can be designed to act without human intervention, making decisions based on predefined logic and real-time data.

The Copilot Studio paid license is ideal for organizations that want more control than Microsoft 365 Copilot extensions but without the complexity of full-code development.

Code-First Approach with Azure AI Foundry

For organizations requiring deep customization, control over AI models, and large-scale deployment, Azure AI Foundry provides a powerful developer-first environment.

Why Choose Azure AI Foundry?

• Custom AI models – Unlike Copilot and Copilot Studio, which rely on predefined models, Azure AI Foundry allows businesses to use custom-trained models based on GPT-4, Azure Machine Learning, or open-source models like Hugging Face.
• Advanced data indexing – Developers can configure custom search indexes for retrieving enterprise knowledge more efficiently.
• Scalability – Azure AI Foundry supports large datasets, multi-language AI models, and high-performance AI workloads.

Technical Considerations

• Expertise Required – Unlike Copilot Studio, Azure AI Foundry is a low-code IDE that requires Python, PromptFlow, and experience with Dev Containers in VS Code for local development. It is designed for enterprise-grade AI projects, supporting team collaboration, custom permissions, and advanced AI tools/services.
• Infrastructure Management – Users must handle cloud compute resources, model hosting, data pipelines, and security configurations.
• Cost & Control – Unlike Copilot, which operates on a per-user licensing model, Azure AI Foundry provides greater control over AI deployment. Businesses pay for model training, storage, and API usage, but they also gain the ability to configure custom networking policies and fine-tune AI models—options not available in Copilot Studio.

Choosing the Right Approach

If you need a low-code solution for business automation, Copilot Studio is the best choice. If you require custom AI models, large-scale indexing, and complete control, Azure AI Foundry provides the necessary tools for building enterprise-grade AI applications.

Bridging the Gap: Copilot Studio and Azure AI Foundry Together

While Copilot Studio and Azure AI Foundry serve different user groups and development needs, they are not mutually exclusive. In fact, they are complementary tools that can be used together to build AI agents that are both easy to develop and highly customizable.

Starting with Copilot Studio for Rapid Development

For many organizations, Copilot Studio provides a quick and accessible way to create AI agents. With pre-built templates, a low-code environment, and seamless integration with business applications, it allows teams to prototype and deploy AI solutions without requiring extensive AI expertise.

Previously known as Microsoft Power Virtual Agents, Copilot Studio now incorporates its core capabilities, enabling businesses to build intelligent chatbots and conversational AI experiences with enhanced customization, automation, and integration options.

However, as business needs evolve, organizations may require:

• Custom AI models for more specialized responses.
• Integration with proprietary or external data sources beyond what is available in Copilot Studio.
• Advanced AI orchestration to fine-tune how the agent processes and retrieves information.

Extending with Azure AI Foundry for Full Control

Organizations that need deeper customization can deploy AI solutions using both Copilot Studio and Azure AI Foundry, which provides:

• Custom-trained AI models that can replace or augment standard Microsoft models.
• Scalable data indexing and retrieval, allowing agents to process large enterprise datasets efficiently.
• Advanced orchestration to define exactly how AI agents interact with different systems and users.

The Role of the Microsoft 365 Agents SDK

Microsoft is also working on the Microsoft 365 Agents SDK, a developer toolkit designed to bridge the gap between low-code and code-first approaches. With this SDK, businesses will be able to:

• Seamlessly integrate Copilot Studio agents with Azure AI services.
• Extend Microsoft 365 Copilot’s capabilities with custom logic, actions, and AI models.
• Enable developers and business users to collaborate on building AI solutions that start with Copilot Studio but leverage the power of Azure AI.

Bringing It All Together

Organizations can leverage Copilot Studio for quick workforce solutions and use Azure AI Foundry to develop sophisticated, enterprise-grade AI solutions with deeper customization and control.

The upcoming Microsoft 365 Agents SDK will further simplify this integration, making it easier than ever to create intelligent, adaptable AI agents that fit any business need.

Conclusion

Choosing the right approach for building AI agents depends on three key factors:

1. Type of Agent – Will your agent operate within Microsoft 365 Copilot or as a standalone AI solution?
2. Maker Skills – Do you need a natural language-based tool, a low-code interface, or a code-first development environment?
3. Level of Control – How much flexibility do you require over knowledge, orchestration, AI models, and user experience?

There is no single “right” choice—each tool serves different needs and skill levels. Microsoft 365 Copilot extensions are ideal for enhancing internal workflows, while Copilot Studio provides a low-code platform for custom AI solutions.

For businesses that need full control, Azure AI Foundry offers deep customization and scalability. Importantly, you are not locked into a single choice—you can start with Copilot Studio for rapid deployment and scale with Azure AI Foundry as your needs evolve.

Before deciding, consider your team’s expertise, available resources, and long-term AI investment.

If you're exploring an AI solution or need a PoC to validate its potential before committing to a larger build, our team can help. Feel free to reach out to our team of experts and find out what you need to kickstart your project.