The AI-Driven Shift in Enterprise Knowledge Consumption
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Abstract
This report analyzes a structural shift in how internal documentation is consumed within a large technology organization, driven by the rise of retrieval-augmented generation (RAG) in an internal AI assistant. Analysis of traffic data shows that AI-driven retrieval became a primary mode of wiki consumption as assistant usage matured. Over the analysis period, the share of assistant responses using RAG increased substantially, and AI retrievals grew to represent the majority of measured documentation consumption. This contributed to a large year-over-year increase in overall documentation usage.
Notably, this growth appears additive rather than substitutive: human readership remained relatively stable over the same broader period. The analysis also reveals an uneven consumption landscape, in which many pages are frequently retrieved by the AI system yet rarely visited by people, and vice versa. A minority of active pages were retrieved by the assistant, while a much larger share received human visits.
The report situates these findings against broader industry trends toward AI-first documentation architectures and concludes that content quality, freshness, structural clarity, and expanded measurement frameworks are now critical determinants of AI output quality, positioning knowledge management as a key strategic capability.
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