Azilomen Ibhawoh15 June 2026
Most automation disappointment traces back to the same root cause: the data and processes underneath were not ready. Models trained on unreliable data automate unreliability at scale.
AI readiness means fixing the foundations: clean, governed data, well-understood processes, clear ownership, and a governance framework that knows what 'good' looks like.
It also means being honest about where automation adds value. Not every process deserves automation — some deserve redesign or retirement first.
The organisations that benefit from AI are the ones that did the unglamorous work first. Readiness is the competitive advantage.