Gartner pitches 'Context Layer' as AI infrastructure necessity; researchers find 42% of leaders cite infrastructure as biggest obstacle despite 87% claiming data is AI-ready

At the 2026 Gartner Data & Analytics Summit, industry was introduced to the 'Context Layer'—a semantic map that helps AI understand business relationships and data definitions before processing raw data. Gartner predicts that 60% of AI projects will be abandoned by 2028 due to lack of this foundation.

A Drexel LeBow study from early 2026 found a disconnect: while 87% of leaders claim their data is AI-ready, nearly half (42%) admit their infrastructure is actually their biggest obstacle. The article argues this gap reflects unresolved 'data debt'—accumulated problems like undocumented data definitions and manual, repetitive work ('Toil') that undermine AI reliability.

True AI-readiness, the article contends, requires three concrete steps before building semantic maps: defining a 'Data Contract' between data producers and consumers, automating manual pipeline restarts, and consolidating core metrics so humans and AI share the same definitions (e.g., what 'Active User' means).