Report

AI context platforms: A market overview for AI leaders

Discover how governed context helps AI agents work reliably in production. This Gartner® report gives enterprise AI leaders the market definition, required capabilities and example vendors to plan with.

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Each new AI agent means rebuilding context from scratch

You build one AI agent, then rebuild its context for the next: definitions, data connections, rules. Each rebuild slows delivery. And when agents disagree on what your data means, people stop trusting their answers.

80%

Up to 80% increase in agentic AI accuracy when organizations prioritize semantics in AI-ready data.

60%

Up to 60% reduction in agentic AI costs when organizations prioritize semantics in AI-ready data.

By 2028

The majority of enterprises running AI agents in production will standardize on a dedicated context platform rather than build and govern context separately for every agent.

Gartner®, Market Overview for AI Context Platforms, 13 August 2026

Made for leaders putting AI agents to work

You’re responsible for AI agents that have to work reliably in production, not just in a pilot. This report is useful if you are:

An AI or transformation leader deciding how to give agents consistent, governed context
An enterprise architect working out where semantic models and knowledge graphs fit in your stack
A data governance or security leader who must control what AI agents use

What you’ll discover

Gartner® defines the AI context platform market and sets out what these platforms must do. It also lists example vendors across the market, including Digital Science.