AI Execution — Problem gravity

AI programmes fail. Predictably.

More pilots won’t fix it. You need an execution system that makes value, controls, integration and adoption inevitable.

AI programmes fail for predictable reasons.

It’s rarely the model. It’s value, governance, data, integration, adoption, operating model and risk. Galapagos gives you the execution mechanics to fix each one.

Value

Pilot drama (no kill/scale decisions)

Teams build interesting demos, but nobody makes the hard calls. Galapagos uses decision logs, timeboxed action sessions and evidence gates to kill, scale, or pivot.

Governance

Risk controls arrive late

Controls get bolted on at the end, so delivery slows or stops. The Island bakes governance in through clear interfaces and grown-up working relationships — fast decisions, rapid turnaround, and no delivery drag.

Data

Data readiness is assumed

AI depends on data quality, access and lineage. Galapagos forces explicit data contracts, staged access and controlled environments so teams don’t discover reality in production.

Integration

Proof-of-concept ≠ production

Most programmes stall at the handover from prototype to operational workflow. Galapagos ships MMMSS: many small releases into real journeys, so integration is solved step-by-step.

Adoption

People don’t change on PowerPoint

Usage doesn’t happen automatically. Galapagos treats adoption as delivery: the feedback loop is part of the work, not a comms afterthought.

Operating model + risk

No accountable delivery system

AI cuts across business, data, technology and controls. The Island works when leadership is small enough to decide and senior enough to unblock — with a single accountable executive and clear business and delivery ownership.

The gravity is real (and it’s accelerating)

Gartner predicts over 40% of agentic AI projects will be cancelled by the end of 2027 due to escalating costs, unclear business value, or inadequate risk controls.

Gartner press release (June 2025)

FT reporting highlights that the AI rollout is “messy” — adoption, change, and proving ROI are hard in real organisations.

FT Working It: The AI rollout is here — and it’s messy

And FT’s data-centre investigation underlines the scale of investment and the uncertainty around cost and necessity — the hidden “execution tax” leaders underestimate.

FT: Inside the relentless race for AI capacity

Start with the AI Readiness Review Stuck in pilots? Rescue it See the execution mechanics