A Framework for Turning AI Ambition Into Execution
Seven letters. I built this because every failed AI programme I've seen fails in a predictable place.
After 25 years in transformation and the last several years watching AI programmes specifically, I built a framework for the part almost everyone skips: turning ambition into execution. I call it the DISRUPT Method™, and I'm giving it away in full here, because the value was never in the acronym. It's in actually running it.
Diagnose the status quo. Not "where could AI help," but which of your processes exist only because nobody has had permission to kill them. Outdated assumptions, structural constraints, process friction, data weaknesses: name them before you reach for a technology answer.
Identify disproportionate value. Find where AI materially improves outcomes, in economics, decisions, customer outcomes, resilience, rather than marginally speeding up a task nobody questioned in the first place.
Simplify the complexity. Separate genuine transformation from technology theatre before you commit a single pound of investment. Most portfolios are a mix of both, and almost nobody has actually sorted which is which.
Redesign the work. Do not automate a broken process. Reimagine the workflow, the decision, the hand-off, the customer journey. Automating the current version just gets you to the wrong outcome faster.
Unite human and artificial intelligence. Decide, explicitly, what the agent executes and what a person decides. Where judgement stays human. Where accountability sits. What controls are required. Leave this implicit and you'll find out the hard way.
Prove the outcome. Measure what actually changed, in value, risk, adoption, business impact, not what was demonstrated in a room. A great demo and a proven outcome are not the same thing, and most AI reporting still confuses them.
Transform at scale. Move what worked from proof point to permanent capability: enterprise platforms, operating models, governance, culture. Otherwise it stays a pilot forever, however good it was.
Most programmes I see start at step six. They want to prove the outcome before they've diagnosed anything. That's why they stall. Run the sequence in order, once, on your next AI initiative, before you write the business case, not after.
Nigel Guy
The Disruptive AI Enabler™
One useful disruption every week.
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