TL;DR

Microsoft Graph provides permission-aware access to Microsoft 365 data, but it doesn’t interpret meaning. The IQ layers add context so AI can reason safely: Work IQ helps Copilot connect people, conversations, content, and activity into usable work context; Fabric IQ (preview) adds governed business meaning so AI understands what data represents and how key entities relate; and Foundry IQ grounds custom agents in trusted enterprise knowledge via Azure AI Search, enabling secure retrieval and governance. In short, Graph enables access; IQ enables understanding.

Work IQ, Fabric IQ, Foundry IQ, vs Microsoft Graph

Over the past year, Microsoft has introduced a new family of concepts: Work IQ, Fabric IQ, and Foundry IQ.

If you’ve been following Copilot, Power Platform, Dynamics 365, or Azure AI Foundry, you’ve probably seen “IQ” mentioned more and more, often without a clear explanation of what it actually is, how it relates to Microsoft Graph, or why it matters for real business outcomes.

This post cuts through unnecessary complexity.

General AI is no longer the differentiator

A year ago, access to powerful AI models felt like an advantage. Today, it’s a must.

Every enterprise has access to strong foundation models. The real difference is no longer how smart the model is, but how well it understands your organisation.

What AI lacks is not general knowledge but enterprise context:

• how your processes actually work

• how your data is structured and governed

• how decisions are made

• what is allowed, restricted, or risky

• what is happening right now in your workflows

This is where the new “IQ” concepts come in. At its core, IQ is Microsoft’s way of describing an enterprise context engine. It’s the layer that turns raw data into something AI can reason over safely.

Microsoft Graph vs IQ: access vs understanding

Let’s start with the foundation: Microsoft Graph.

Microsoft Graph is:

• a unified API and access layer, and

• a data model that spans services

• connecting users, emails, files, calendars, Teams, SharePoint, and more.

The Graph name isn’t a coincidence. It reflects a connected data model of entities and relationships across Microsoft 365.

You can think of Graph as the unified access layer and permission model that gives consistent access to data stored across Microsoft 365 services.

What Graph does not do is interpret meaning.

Graph answers questions like:

• Which emails exist?

• Which files belong to this user?

• Which meetings happened last week?

It gives you access. The IQ layers sit above this. They don’t replace Graph, but they use it, enrich it, and reason over it.

A simple way to frame it:

Graph enables access. IQ enables understanding.

Work IQ: understanding how work actually happens

Work IQ is the intelligence layer Copilot uses to understand day-to-day work.

It builds a dynamic picture of:

• emails, chats, meetings, files

• tasks and decisions

• Dynamics 365 and Dataverse entities (when connected through Copilot experiences, plugins, or agents)

• relationships between people, content, and actions

• how work evolves over time

Crucially, Work IQ doesn’t just retrieve information, it interprets context.

That’s why Copilot can answer questions like:

• “What did we decide last week about the field project budget?”

• “Summarise the latest customer escalations and draft a report.”

It’s not searching like a document library. It’s reasoning over signals, patterns, and workflows.

A helpful analogy:

• Microsoft Graph is the access layer

• Work IQ is the intelligence layer that makes work context searchable, explainable, and useful

Work IQ also learns work patterns, preferences, and typical next actions. This is why it feels “personal” without breaking security boundaries.

From an organisational point of view:

• Work IQ is accessed primarily through Copilot

• It is out of the box

• You don’t need to define complex use cases to see value

But it only works well if your work is structured.

Copilot cannot infer intent from SharePoint chaos.

Fabric IQ: giving AI business meaning, not just data

If Work IQ understands work, Fabric IQ (preview) understands data.  

In Fabric, IQ is essentially a governed business knowledge layer — a way to define entities, relationships, and meaning so AI can query and reason over data correctly.

Microsoft Fabric already centralises analytics across, OneLake, data warehouses, lakehouses, and Power BI semantic models.

Fabric IQ adds a critical layer on top: business meaning, capturing:

• data models and relationships

• semantic definitions

• measures and business logic

• lineage and governance rules

In other words, Fabric IQ allows AI to understand things like what the data represents, how entities relate, which numbers matter, and which rules must be respected.

This is a shift away from basic retrieval-augmented generation. Fabric IQ allows agents to ask analytical questions, generate code. spot anomalies, or explain trends in business terms.

For example:

• “Why did request volume spike in the North region last month?”

• “Show anomalies in field service cycle time.”

The difference is subtle but important: Fabric IQ grounds AI in what the data means, not just where it lives.

Foundry IQ: how custom agents stay grounded in trusted data

Foundry IQ is the knowledge grounding layer in Azure AI Foundry — it helps agents retrieve the right information from approved sources (securely and with governance), so they can reason and act with the right context.  

While Work IQ and Fabric IQ are largely plug-and-play, Foundry IQ is fully custom, designed for Copilot agents, pro-code development, and multi-agent collaboration.

Foundry IQ brings together:

• knowledge sources (documents, databases, APIs)

• indexing + retrieval orchestration

• permission-aware grounding

• citations / traceability (where supported)

• governance + safety controls for knowledge use

If Work IQ is about understanding work and Fabric IQ is about understanding data, then:

Foundry IQ is the knowledge layer for Azure AI Foundry agents, built on Azure AI Search. It helps developers create reusable knowledge bases that agents can query through one API, with retrieval planning, source routing, and permission-aware grounding.

Without clear objectives, well-defined processes, and strong governance, Foundry IQ can quickly become expensive and ineffective.

It is powerful, but it’s not something to adopt without a clear business case.

Security, grounding, and guardrails

One common concern we hear is security. A critical point often missed:

Enterprise access control is enforced by the infrastructure (identity + permissions), not by the model.

Permissions, identity, access control, environment separation, and governance all sit below the IQ layers.

The IQ concepts don’t bypass security. They operate within it. This is why custom security policies and guardrails must be designed upfront, not added later.

Always keep in mind that AI is only as trustworthy as the context and constraints you give it.

What Microsoft-centric organisations should do now

For Dynamics 365 and Power Platform customers, the message is clear: go back to basics.

Before moving on to advanced agent scenarios:

• clean up SharePoint structures

• reduce duplication

• clarify ownership and versioning

• document key processes

• align Dataverse models with real business logic

AI is not magic, it just amplifies what already exists.

Where you can get real, immediate value

We see the fastest returns where context is already well defined. A classic example is onboarding.

If onboarding processes are documented:

• new hires can ask Copilot how things work

• find the right documents instantly

• understand workflows without tribal knowledge

Other early wins can be for example personal work summaries, prioritisation (“what needs my attention?”), or light decision support.

These are safe entry points that build trust before moving into deeper workflow augmentation with Foundry IQ.

The context advantage

In today’s AI landscape general knowledge is commoditised and models are interchangeable. What isn’t interchangeable is your context. The organisations that win will be those that make their context explicit, govern it properly, and design it deliberately for AI.

AI is only as smart as the context you allow it to see.

That’s where the real advantage lies.

Want to know where your organisation actually stands?
We help Microsoft-centric teams assess their readiness and identify where agents will create real value. Get in touch for a free audit.  

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