Free Ebook
The AI ROI Playbook
How to pick AI projects that pay back, and kill the ones that won't
Most AI programmes stall because nobody agreed what success would look like before the work started. This playbook walks through selecting candidate use cases, sizing the return honestly, running a shadow-mode pilot against a human baseline, and deciding — on evidence — whether to scale or stop.
Who it's for
CTOs, heads of data, and operations leaders with a budget and a shortlist of AI ideas.
What you'll take away
- A one-page scoring sheet for ranking candidate AI projects
- The baseline measurements to capture before any model is trained
- A go/no-go checklist for moving a pilot into production
What's inside
- 1Scoring use cases on value, data readiness, and reversibility
- 2Sizing the return before you build: the four numbers to collect
- 3Baselines — measuring the human process you're trying to beat
- 4Shadow-mode pilots and what they actually prove
- 5The cost model nobody budgets for: evaluation, drift, and retraining
- 6Stop criteria, and how to retire a use case without losing the team
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