Why Good AI Ideas Die Badly
Most organisations have exactly one of two problems with AI approvals. Either proposals get approved too easily — a compelling demo, executive enthusiasm, a budget sign-off, and the thing is live before anyone has mapped the risks. Or proposals get stuck in committee indefinitely — every idea dies in review, innovation stalls, and competitors move faster.
Failure Mode 1: The Rubber Stamp
Rubber-stamp organisations approve AI proposals based on the strength of the pitch rather than the quality of the evaluation. The hallmarks: approval decisions made by people who don't understand the technology; no documented risk assessment; no defined accountability if things go wrong; no post-deployment review mechanism. When these systems fail, nobody knows whose responsibility it was.
Failure Mode 2: Committee Paralysis
Paralysis organisations require so many sign-offs, impact assessments, and reviews that almost nothing gets approved. Good ideas die in the queue. Teams stop proposing AI projects because the effort of getting approval outweighs the perceived chance of success. The organisation appears "safe" because little AI is deployed — but it's actually just stagnant.
The Eight Gates model gives AI proposals a structured, sequential path from idea to live — with defined gates, defined reviewers, and defined criteria at each stage. It's thorough enough to catch genuine risks. It's efficient enough that a well-prepared proposal can move through it in three to six weeks.
