Microsoft intelligence layer — definitions
What Are Work IQ, Fabric IQ & Foundry IQ?
Microsoft announced three intelligence layers at Ignite 2025. Each one gives AI agents and copilots a different type of enterprise context. Here is what each layer does, what it connects to, what it does not replace, and when it matters.
What is Work IQ?
Work IQ is intelligence about how work actually happens inside your organization. It models collaboration patterns from Microsoft 365 data — emails, Teams conversations, meetings, SharePoint files, and organizational graph signals — and exposes that understanding through Copilot and through APIs for custom agent development.
What Work IQ provides
Work IQ gives AI systems three kinds of organizational awareness. First, it provides personal context: your preferences, habits, frequently used documents, and communication style. Second, it provides organizational context: who works with whom, how teams actually collaborate versus the formal org chart, and where information flows. Third, it provides memory: the ability for Copilot and agents to learn from past interactions and improve over time.
What Work IQ connects to
Work IQ is the intelligence engine behind Microsoft 365 Copilot. Every time Copilot personalizes a response, remembers a preference, or surfaces a relevant document based on your work patterns, it is drawing from Work IQ capabilities. Microsoft is also exposing Work IQ through APIs, which means developers can build custom agents that access the same organizational intelligence.
What Work IQ does not replace
Work IQ does not provide business data semantics — that is Fabric IQ. It does not provide governed enterprise knowledge retrieval — that is Foundry IQ. And it does not fix broken workflows. Work IQ gives AI better visibility into how people work, but if the underlying workflow is poorly designed, Work IQ simply provides clearer visibility into a bad process.
When Work IQ matters
Work IQ matters most for organizations with active Microsoft 365 deployments that want Copilot to deliver personalized, organizationally relevant value rather than generic AI assistance. It also matters for organizations building custom agents that need to understand collaboration patterns, meeting behavior, or work overload signals.
What is Fabric IQ?
Fabric IQ is a workload inside Microsoft Fabric that unifies enterprise data and organizes it according to business semantics. It takes structured data sitting across OneLake and adds meaning through ontologies, enhanced semantic models, a graph engine, and AI agents — making it possible for both humans and agents to understand what data represents in business terms, not just what values it contains.
What Fabric IQ provides
Fabric IQ combines five integrated capabilities into one semantic intelligence system. The ontology defines business entities, relationships, rules, and objectives in a formal model. Semantic models extend Power BI's trusted definitions beyond analytics into operations and AI. The graph engine enables multi-hop reasoning across business concepts. Data agents answer business questions using structured business meaning. And operations agents reason, learn, and act in real time to advance business outcomes.
What Fabric IQ connects to
Fabric IQ sits inside Microsoft Fabric as a workload. It builds on existing data in OneLake — lakehouses, eventhouses, and Power BI semantic models — and can incorporate external operational data through OneLake shortcuts without copying or building ETL pipelines. Fabric IQ also integrates with Foundry IQ and Work IQ to form the complete intelligence layer.
What Fabric IQ does not replace
Fabric IQ does not replace Power BI. It extends Power BI's semantic models into operations and AI. It does not replace the need for data engineering or data quality work — Fabric IQ's value depends on clean, well-structured data. And it does not replace Foundry IQ's unstructured knowledge retrieval capabilities.
When Fabric IQ matters
Fabric IQ matters most for organizations invested in Microsoft Fabric and Power BI that want to extend their semantic model investment into AI and operations. It is especially relevant when different teams define the same business terms differently, when AI agents need trusted business definitions to produce consistent results, or when the organization wants to build operations agents that can reason about business outcomes.
What is Foundry IQ?
Foundry IQ is a fully managed knowledge system, currently in preview as a capability of Microsoft Foundry (formerly Azure AI Foundry). It provides a single endpoint for high-quality organizational knowledge, built on Azure AI Search, with enterprise governance including Entra ID-based permissions and Microsoft Purview sensitivity labels throughout the retrieval pipeline.
What Foundry IQ provides
Foundry IQ federates knowledge retrieval across multiple source types: Microsoft 365, SharePoint, Fabric IQ, OneLake, Azure Blob Storage, Azure AI Search indexes, the web, and (in private preview) MCP sources. It provides permission-aware retrieval that respects user access controls. It supports multi-hop reasoning for iterative search across sources. And it enables source citation so agents can show where their answers come from.
What Foundry IQ connects to
Foundry IQ is part of Microsoft Foundry, the platform for building, evaluating, and managing AI models and solutions. It provides the knowledge grounding layer that AI solutions built in Foundry need to answer questions accurately. It also draws from Fabric IQ's ontologies and Work IQ's organizational data as knowledge sources, creating a federated retrieval system across all three layers.
What Foundry IQ does not replace
Foundry IQ does not replace structured data analytics — that is Fabric IQ and Power BI. It does not replace collaboration intelligence — that is Work IQ. And for organizations with specialized retrieval requirements, unusual data formats, or non-Microsoft knowledge sources, custom RAG implementations may still be needed alongside Foundry IQ.
When Foundry IQ matters
Foundry IQ matters most for organizations building AI agents or solutions that need governed access to enterprise knowledge. It is especially relevant when governance, compliance, and permission enforcement are high priorities, when knowledge is spread across many systems and repositories, or when reducing AI hallucination through grounded, citation-capable retrieval is important.
A practical example: how all three layers work together
Consider a supply chain organization trying to understand delivery delays.
Fabric IQ sees the data
Fabric IQ detects that certain suppliers are delivering late more frequently and that regional on-time delivery rates have dropped. Because it understands the business ontology, it can identify which materials, products, and customer segments are affected.
Foundry IQ provides the knowledge
Foundry IQ retrieves supplier contracts, service-level agreements, and penalty clauses from the organization's document repositories. It understands the contractual obligations around delivery timelines and can surface relevant terms with citations.
Work IQ reveals the human pattern
Work IQ observes that operations teams are spending excessive time in email chains and delay review meetings, manually chasing supplier updates. It detects that the human workaround has become the process.
The result: an AI agent that understands where and why delays occur (Fabric IQ), what the contractual obligations are (Foundry IQ), and how people are currently handling the problem (Work IQ) can recommend escalations, draft communications quoting relevant SLA terms, and flag process improvements. That is the combined intelligence layer at work.
Part of a larger system
Why these questions matter beyond Microsoft
Understanding Microsoft's intelligence layers is the fourth stage of the AI Advantage Framework. The first three stages address which work to fund, whether the information is usable, and whether the workflows can execute. Platform decisions make more sense when those foundations are in place.
AI Advantage Framework
AI Fit & Governance → AI-Ready Data → Operational AI → Microsoft Intelligence
Need help deciding where these layers fit?
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