What is it?
Between 60 and 95 per cent of enterprise AI initiatives produce no measurable business value. Research from RAND, MIT and Gartner arrives at that range separately, and the cause they identify sits underneath the technology rather than in it.
This handbook covers what has to be true inside an organisation before AI produces anything worth having: explicit business objectives, data you can trust, governance built in from the start, and infrastructure that keeps your options open. It gives you a model for deciding where AI creates measurable value, a three-phase sequence for building it and a five-question self-assessment.
Vendor-neutral by design. The reasoning holds regardless of who executes it.
What you get out of it:
- A way to choose the first use case, scoring candidates on volume, friction and data readiness together rather than on ambition
- A simple way to estimate impact before committing, looking separately at efficiency gains, quality improvements, and future strategic value instead of reducing everything to one ROI number.
- A three-phase sequence for deciding where to invest, building, and scaling, with the owner, the decisions and the completion test for each phase
- A clear view of which decisions stay yours whoever executes the work
- A five-question self-assessment and a six-step starting sequence you can run this week
- A seventeen-point checklist to work against once the programme is underway
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