Enterprise AI stalls in the messy middle: measure value, not activity
DavidLinthicum · x · 2026-10-30
David Linthicum argues enterprise AI conversation fixates on the happy path: demos and pilots look impressive in clean, controlled environments, but production brings messy data, exceptions, unclear ownership, security concerns, hidden rework, and brittle workflows. The issue isn't AI's potential but measuring the wrong things—faster drafts, more generated code, and higher tool adoption don't automatically translate into business outcomes. CIOs should shift focus from AI activity to AI value, measuring end-to-end production results.
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