How Microsoft Copilot Finds Information: Complete Guide

Published: June 2026 • 18 min read

Millions of users ask Microsoft Copilot questions every day. They ask about documents, business data, company policies, and industry trends. But how does Copilot find the information it uses to answer these questions? And how can you ensure that when someone asks about your business, Copilot has the right information to reference?

Understanding how Microsoft Copilot finds information is essential for any business that wants to be visible in AI-generated answers. Copilot combines a large language model (LLM) with secure access to your work data through the Microsoft Graph, real-time web search via Bing, and enterprise-specific knowledge sources using Retrieval-Augmented Generation (RAG).

This comprehensive guide explains everything you need to know about how Microsoft Copilot finds information—from its core architecture and RAG workflow to Bing Search integration and enterprise data access. Whether you are a marketer, publisher, or business owner, this guide will help you understand and optimize for Copilot discoverability. For a structured approach to mastering these skills, explore our Learning Paths designed for AI-driven business growth.

1. What Microsoft Copilot Is

Microsoft Copilot is an AI-powered assistant that uses the power of generative AI to respond to natural language queries and instructions[citation:5]. It is designed to help users create content, find information, and automate tasks across Microsoft 365 applications.

Key Definition

Microsoft Copilot: An AI-powered assistant built on a large language model (LLM) that combines secure access to work data with intelligence that understands context and priorities to provide personalized, timely assistance[citation:5].

Copilot has several key capabilities:

Conversational AI – Engages in natural, human-like dialogue[citation:5].
Microsoft Graph integration – Securely accesses work data such as emails, files, meetings, chats, and people[citation:5].
Work IQ intelligence layer – Understands context, remembers work patterns, and connects related information[citation:5][citation:7].
Retrieval-Augmented Generation (RAG) – Combines reasoning with trusted, organization-specific knowledge[citation:1].
Web search via Bing – Accesses real-time web information to ground responses[citation:9][citation:11].
Agentic capabilities – Can plan and execute multi-step tasks in the background[citation:7].

2. How Microsoft Copilot Works

Microsoft Copilot works through a multi-step process that combines user prompts, contextual augmentation, and LLM generation[citation:5].

2.1 The Copilot Workflow (Textual)

Copilot Flow: User Prompt → Prompt Preparation (adding context) → LLM Processing → Response Generation → Response Delivered[citation:5]

2.2 Key Components

User prompt – The natural language question or instruction you submit[citation:5].
Prompt preparation – Copilot augments the prompt with additional contextual information, such as rules about the response type and a summary of conversation history[citation:5].
LLM processing – The prompt is sent to a large language model, which interprets the request and generates a response based on the vast data it was trained on[citation:5].
Response delivery – Copilot responds with the output from the model[citation:5].

2.2 The Work IQ Intelligence Layer

Work IQ is the intelligence layer behind Microsoft 365 Copilot that builds on Microsoft Graph data to understand context, remember work patterns, and connect related information[citation:5][citation:7].

Understands how teams work together[citation:7]
Prioritizes tasks based on urgency and behavior[citation:7]
Uses context from emails, files, meetings, and chats[citation:7]
Provides more personalized, timely assistance[citation:5]

3. How Copilot Finds Information

Microsoft Copilot finds information through a combination of three core technologies: the LLM itself, the Microsoft Graph, and retrieval systems including Bing Search[citation:1][citation:5]. Each plays a distinct role in how Copilot discovers and retrieves information.

3.1 The Three Core Information Sources

Copilot's Information Sources
Technology	Role	What It Provides
LLM (Training Data)	Foundation knowledge	General knowledge, language understanding, pattern recognition[citation:5]
Microsoft Graph	Work data access	Emails, files, meetings, chats, people—only what you have permission to see[citation:5]
Bing Search (RAG)	Real-time retrieval	Current information, public web content, citations[citation:1][citation:9]

3.2 How Copilot Uses Each Source

LLM training data – Copilot's foundation model is trained on vast amounts of public web content, providing general knowledge and language understanding[citation:5].
Microsoft Graph – Copilot securely connects to your Microsoft 365 data—emails, files, meetings, chats, and people. Graph enforces permissions and access rules, ensuring Copilot can only use information you are already allowed to see[citation:5].
Bing Search (web grounding) – When enabled, Copilot can fetch information from the Bing Search service when information from the web helps provide a better, more grounded response[citation:9][citation:11].

4. Retrieval-Augmented Generation (RAG) in Copilot Studio

Retrieval-Augmented Generation (RAG) in Microsoft Copilot Studio combines the reasoning capabilities of language models with trusted, organization-specific knowledge[citation:1]. It enables agents to generate accurate, contextual, and grounded responses based on enterprise content.

4.1 The RAG Workflow (Textual)

RAG Workflow: User Query → Query Rewriting → Content Retrieval → Summary & Response Generation → Security & Governance Validation[citation:1]

4.2 Step 1: Query Rewriting

Copilot Studio optimizes the user's question before searching[citation:1]:

Clarifies its meaning
Adds contextual signals (last 10 turns)
Improves keyword matching
Generates search-friendly queries

4.3 Step 2: Content Retrieval

After rewriting the query, the system runs it against all configured knowledge sources[citation:1]. Copilot Studio gets the top three results from each source, balancing relevance with performance.

4.4 Supported Knowledge Sources

Public data (websites) – Websites indexed by Bing[citation:1][citation:13]
SharePoint / OneDrive – Internal enterprise content (requires authentication)[citation:1][citation:13]
Uploaded files – Files uploaded to Dataverse storage[citation:1][citation:13]
Dataverse tables – Structured business records[citation:1][citation:13]
Graph connectors – Enterprise applications indexed in Microsoft Graph[citation:1][citation:13]
Real-time connectors – Live data from systems like Salesforce, Zendesk, SQL[citation:1][citation:13]
Azure AI Search – Vector-based semantic search[citation:1][citation:13]
Custom data – Data provided through APIs, flows, or custom logic[citation:1][citation:13]

4.5 Step 3: Summary & Response Generation

AI synthesizes the retrieved content[citation:1]
Applies custom instructions for tone, formatting, security, or brevity[citation:1]
Generates citations for the underlying data[citation:1]
Personalizes responses using user context (such as language, department, or region)[citation:1]

4.6 Step 4: Security & Governance Validation

Moderates harmful, malicious, non-compliant, or copyrighted answers[citation:1]
Validates grounding and removes incorrect information[citation:1]
No customer data is used to train language models[citation:1][citation:13]

RAG Best Practices

RAG works best for factual question answering, not deep document analysis[citation:1]. It is ideal for answering questions from knowledge bases, summarizing policies and FAQs, and retrieving specific facts. It is not intended for full document comparison, policy compliance evaluation, or complex reasoning over long unstructured documents[citation:1].

5. Bing Search Integration and Web Grounding

Microsoft Copilot can reference web content when responding to user prompts through the web search or web content plugin[citation:9][citation:11]. This improves the quality of Copilot responses by grounding them in the latest information from the web.

5.1 How Web Search Works

Copilot parses the user's prompt and identifies terms where web grounding would improve response quality[citation:9][citation:11]
Based on these terms, Copilot generates a search query that it sends to the Bing Search service[citation:9][citation:11]
The generated query is different from the user's original prompt—it consists of a few words informed by the user's prompt[citation:9][citation:11]
Copilot does not send the user's entire prompt, entire Microsoft 365 files, or identifying information (username, domain, or tenant ID) to Bing[citation:9][citation:11]

5.2 Examples of Generated Search Queries

User prompt: "Who is my manager and what public information is available about them?"
Generated query: [Manager name][citation:9][citation:11] How it works: Copilot finds the manager's name from Microsoft 365 data, then generates a Bing search query based on their name[citation:9][citation:11]
User prompt: "We're considering a possible acquisition of Fabrikam. Summarize financial information about the company."
Generated queries: "Fabrikam strategy" and "Fabrikam financials"[citation:9][citation:11]

5.3 How Microsoft Handles Web Search Queries

Generated search queries sent to Bing are disassociated from the user ID and tenant ID[citation:9][citation:11]
Queries are not used to improve Bing, not shared with advertisers, and not used to train generative AI foundation models[citation:9][citation:11]
Queries are treated as customer confidential information and protected by appropriate technical and organizational measures[citation:9][citation:11]

6. Microsoft Graph Integration

Microsoft Graph is a critical component of how Microsoft Copilot accesses organizational information. It securely connects your Microsoft 365 data—such as emails, files, meetings, chats, and people—across apps and services[citation:5].

Secure access – Graph enforces permissions and access rules, ensuring Copilot can only use information you are already allowed to see[citation:5]
Contextual understanding – Graph provides context about your work relationships, documents, and communications[citation:5]
Work IQ integration – Work IQ builds on Graph data to understand context, remember work patterns, and connect related information[citation:5][citation:7]

7. Work IQ and Organizational Memory

Work IQ is Copilot's organizational memory layer that enables deeper understanding of how your organization works[citation:7].

Organizational understanding – Understands roles, communication patterns, past decisions, task histories, and project context[citation:7]
Personalized assistance – Provides more relevant and personalized support based on how you work[citation:7]
Multi-step workflows – Enables Copilot to plan and execute multi-step tasks in the background[citation:7]

8. Public Web Content and Bing Index

Public web content is accessible to Copilot through Bing Search integration[citation:1][citation:9]. For content to be discoverable via Copilot's web search, it must be indexed by Bing[citation:1][citation:13].

Bing indexing – Websites must be indexed by Bing to be accessible through Copilot's web search[citation:1][citation:13]
Website ownership verification – Confirming website ownership can yield better results[citation:1][citation:13]
Public data sources – Support includes public websites with up to two sub-page depth[citation:1][citation:13]

For more on optimizing your content for AI search visibility, visit our Academy for advanced training.

9. Trusted Sources and Publisher Authority

Like other AI systems, Microsoft Copilot prioritizes content from trusted, authoritative sources. Here is why it matters:

Bing index – Content must be indexed by Bing to be discoverable[citation:1][citation:13]
Publisher authority – Content from established, reputable publishers is more likely to be surfaced[citation:1]
Accuracy – Authoritative sources are more likely to provide accurate information[citation:1]

10. News Websites and Bing News

News websites are particularly important for Copilot discoverability through Bing Search integration:

Bing indexing – News content from sites indexed by Bing is accessible[citation:1][citation:13]
Real-time retrieval – Copilot can access timely news content via Bing Search[citation:9][citation:11]
Authority signals – News sites are generally considered authoritative[citation:1]
Entity recognition – News articles often include named entities that help with discoverability

11. Press Releases and Copilot Discoverability

Press releases distributed through reputable newswires can contribute to Copilot discoverability when they are indexed by Bing[citation:1][citation:13]:

Bing indexing – Press releases on sites indexed by Bing are discoverable[citation:1][citation:13]
Syndication – Press releases are republished on multiple publisher sites, increasing discoverability[citation:1]
Named entities – Press releases include named people, places, and organizations that help with entity recognition
Freshness – Press releases signal timely authority[citation:1]
Bing News – Content from reputable newswires may appear in Bing News

Need help with media credentials? Visit our Press Pass & Credentials page for journalists and PR professionals.

12. Structured Data

Structured data (schema markup) helps search engines and AI systems like Copilot understand your content and entities[citation:1].

Bing indexing – Structured data helps Bing index and understand your content[citation:1]
Entity recognition – Structured data helps Copilot identify entities
Context – Provides context about your business
Knowledge Graph – Structured data feeds into search engine knowledge graphs

For more on optimizing your content with structured data, explore our Business Action Center for actionable strategies.

13. E-E-A-T

E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is a critical framework for content discoverability in AI systems like Copilot, as they prioritize authoritative, trustworthy sources[citation:1].

Experience – Content creators have first-hand experience
Expertise – Content creators have the necessary knowledge
Authoritativeness – The website is a recognized go-to source[citation:1]
Trustworthiness – The content is accurate and transparent[citation:1]

To see how other businesses have successfully built their AI visibility, check out our Testimonials page for real-world examples.

14. Topical Authority

Topical authority is the recognition that your website is a trusted source on a specific topic. Copilot values topical authority through its reliance on authoritative sources[citation:1].

Depth of content – Cover topics comprehensively
Consistency – Regularly publish on the same topic
Expert contributions – Include expert commentary and insights
Entity relationships – Connect your content to relevant entities

15. Internal Linking

Internal linking helps search engines and AI systems understand the relationships between your content and entities.

Link to entity pages – About, team, and product pages
Link to related content – Connect content that covers related topics
Use descriptive anchor text – Helps context understanding
Create topic clusters – Link pillar content to supporting content

16. Content Freshness

Content freshness is the timeliness of your content. Copilot values fresh information through its Bing Search integration[citation:9][citation:11].

Publication date – Newer content is prioritized[citation:1]
Update frequency – Regular updates signal freshness
Real-time retrieval – Copilot can access fresh content via Bing Search[citation:9][citation:11]

17. AI Discoverability

AI discoverability is the ability of your content to be found and cited by AI tools like Microsoft Copilot. Here is how to improve it:

Bing indexing – Ensure your content is indexed by Bing[citation:1][citation:13]
E-E-A-T – Demonstrate experience, expertise, authority, and trust[citation:1]
Structured data – Use schema markup to define entities
Named entities – Include people, places, and organizations
Topical authority – Build comprehensive topic coverage[citation:1]
Media mentions – Appear in trusted publications[citation:1]
Press releases – Distribute through reputable newswires[citation:1]
Microsoft Graph access – For enterprise content, ensure proper indexing in Microsoft Graph[citation:5]

You can check your AI discoverability readiness with our AI Discoverability Checker tool.

18. Common Misconceptions

There are several misconceptions about how Microsoft Copilot finds information:

"Copilot only uses Bing Search." – No. Copilot also uses the LLM's training data, Microsoft Graph, and organization-specific knowledge sources[citation:1][citation:5].
"Copilot always cites sources." – Not always. Copilot provides citations when using RAG or web search, but may not cite sources when relying on its training data[citation:1].
"Copilot has access to all web content." – No. Copilot can only access content via Bing Search when web search is enabled and indexed by Bing[citation:1][citation:9].
"Structured data guarantees Copilot citations." – It helps, but does not guarantee citations.
"Copilot uses all work data for training." – No. Customer data is not used to train language models[citation:1][citation:13].

19. Common Mistakes

Avoid these common mistakes when optimizing for Copilot discoverability:

No Bing indexing – Content not indexed by Bing is not discoverable[citation:1][citation:13]
No structured data – Missing schema markup reduces AI understanding
No entity optimization – Missing named entities
Low E-E-A-T – Content lacks expertise and trust[citation:1]
No authority building – Ignoring media mentions and press releases[citation:1]
Duplicate content – AI may ignore duplicate content
Inconsistent information – Conflicting business information

To test the newsworthiness of your content for AI discovery, try our Press Release Newsworthiness Checker.

20. Best Practices

Follow these best practices to improve your Microsoft Copilot discoverability:

Ensure Bing indexing – Make sure your content is indexed by Bing[citation:1][citation:13]
Build E-E-A-T – Demonstrate experience, expertise, authority, and trust[citation:1]
Use structured data – Implement schema markup for all content
Include named entities – People, places, and organizations
Build authority – Earn media mentions and press releases[citation:1]
Use topic clusters – Organize content into pillar and cluster pages
Link internally – Connect all related content
Maintain freshness – Update content regularly
Be consistent – Consistent business information across platforms
Monitor performance – Track how often your content appears in Bing Search
Stay current – AI search best practices evolve rapidly

To understand your overall business visibility score, try our Business Visibility Score tool.

22. Frequently Asked Questions

How does Microsoft Copilot find information?

Microsoft Copilot finds information through a combination of three core technologies: the LLM's training data (general knowledge), the Microsoft Graph (work data access), and retrieval systems including Bing Search (real-time web information)[citation:1][citation:5].

Does Copilot use real-time web search?

Yes. When the web content plugin is enabled, Copilot can fetch information from the Bing Search service when information from the web will help provide a better response[citation:9][citation:11].

Does Copilot cite sources?

When using RAG or web search, Copilot can generate citations for the underlying data[citation:1]. However, citations are not guaranteed for every response—particularly when Copilot relies on its training data alone.

What is the role of the Microsoft Graph in Copilot?

The Microsoft Graph securely connects Copilot to your work data—emails, files, meetings, chats, and people. It enforces permissions and access rules, ensuring Copilot can only use information you are already allowed to see[citation:5].

What is RAG in Copilot Studio?

Retrieval-Augmented Generation (RAG) combines the reasoning capabilities of language models with trusted, organization-specific knowledge[citation:1]. It enables Copilot to generate accurate, grounded responses based on enterprise content rather than relying solely on the model's memory.

How does Copilot decide which information to use?

Copilot uses a multi-step process: it rewrites the user's query to improve search, retrieves content from available knowledge sources, synthesizes the retrieved content, and applies security validation[citation:1]. The system balances relevance with performance, prioritizing authoritative, accurate sources.

Can Copilot access private content?

Copilot can access private content within your organization through the Microsoft Graph, but only when you have permission to see that content[citation:5]. Copilot cannot access private content from outside your organization—it can only access content that is publicly available on the web via Bing Search[citation:1][citation:9].

What is Work IQ in Microsoft Copilot?

Work IQ is the intelligence layer behind Microsoft 365 Copilot that builds on Microsoft Graph data to understand context, remember work patterns, and connect related information[citation:5][citation:7].

How can I improve my content's Copilot discoverability?

Ensure your content is indexed by Bing, build E-E-A-T, use structured data, include named entities, earn media mentions and press releases, maintain content freshness, and for enterprise content, ensure proper indexing in Microsoft Graph[citation:1][citation:5][citation:13].

What information does Copilot send to Bing Search?

Copilot sends a generated search query that is different from the user's original prompt—it consists of a few words informed by the user's prompt. Copilot does not send the user's entire prompt, entire Microsoft 365 files, or identifying information (username, domain, or tenant ID)[citation:9][citation:11]. For continuous learning, explore our Certifications to validate your AI visibility skills.

23. Final Summary

Key Takeaways

Microsoft Copilot is an AI-powered assistant that combines a large language model with secure access to work data through the Microsoft Graph and real-time web search via Bing[citation:5].
Copilot finds information through a "trinity" of sources: the LLM's training data, the Microsoft Graph, and Bing Search (RAG)[citation:1][citation:5].
Retrieval-Augmented Generation (RAG) in Copilot Studio combines reasoning with trusted, organization-specific knowledge to generate accurate, grounded responses[citation:1].
Bing Search integration allows Copilot to access real-time web information when the web content plugin is enabled[citation:9][citation:11].
Generated search queries sent to Bing are disassociated from user identity and not used to improve Bing or train foundation models[citation:9][citation:11].
Work IQ is Copilot's organizational memory layer that understands roles, communication patterns, and project context[citation:7].
For content to be discoverable via Copilot's web search, it must be indexed by Bing[citation:1][citation:13].
E-E-A-T, structured data, named entities, media mentions, and press releases all contribute to Copilot discoverability[citation:1].
Avoid common mistakes: no Bing indexing, no structured data, no entity optimization, low E-E-A-T, no authority building.
In 2026, understanding how Microsoft Copilot finds information is essential for any business seeking visibility in Microsoft's AI-powered ecosystem.

Microsoft Copilot is increasingly becoming a primary source of information for users worldwide. Understanding how it finds and evaluates information is essential for any business that wants to be visible in Microsoft's AI-powered ecosystem.

To improve your Copilot discoverability, focus on ensuring your content is indexed by Bing, building E-E-A-T, using structured data, including named entities, earning media mentions, distributing press releases, and maintaining content freshness. For enterprise content, ensure proper indexing in Microsoft Graph.

Ready to improve your Copilot discoverability? Use the checklist and best practices in this guide to get started.

If you have questions or need support, don't hesitate to Contact Us. Our team is here to help you succeed.

How Microsoft Copilot Finds Information: Complete Guide (2026)

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