Where in your processes does AI truly create value — and how to measure it?

Outcomes

What gets created

Every module ends with a working document that stays in the organisation and is usable the next day.

• A completed survey → workshop input material.
• Fact / Assumption / Hype on example claims about AI → a shared AI Reality Checklist.
• Assessing one service area as Keep / Buy / Build / Agentify → AI Make-Buy-Agentify Canvas.
• Scoring 2–3 of your own processes; team scoring of the workshop pool and selecting a process for P2–P3 → Process Scorecard.
• Three redesign variants of a single process — Amplify, Recalibrate, Reset — and choosing the best one.
• A Redesign Canvas (to-be) + a mini-canvas of the participant’s own process.
• A Data Readiness Checklist for your own initiative + a decision on the approach justified in one sentence.
• Pilot Autopsy — an analysis of an initiative that stalled → AI Scaling Readiness Check.
• An AI Thesis for your own initiative + peer critique (is X a process? does Y have a face? does Z have a number?) → AI Thesis.
• Work on a real initiative → an AI Value Hypothesis Canvas with a baseline, metrics and a value owner.
• Ranking 3–5 initiatives → an Executive AI Portfolio Scorecard and a list of initiatives that need further evidence.
• A control and decision-rights design for one use case → AI Decision Rights Map.
• A team 12-month Roadmap (3 tracks: initiatives / competencies / governance) + a ‘one-pager’ Exec Buy-in with role assignments for S2.
• Work on real initiatives → a prioritized portfolio, Decision Cards, a Decision Register and a 90-Day Decision Roadmap.