Why do AI projects fail?

The 95% failure rate is now documented across MIT, Gartner, and BCG research. The common assumption is that the AI was bad. The common reality is that everything around the AI was bad: wrong use case, missing data, no governance, no integration, no measurement, no handoff.

The five patterns we see most often: (1) Pilots started without a readiness assessment — the organization didn't actually have the data, infrastructure, or talent to operate the system. (2) Governance was an afterthought — no audit trail, no policy enforcement, no incident response. (3) Integration was scoped as 'we'll figure it out later' — and later never came. (4) Measurement was vanity (pilots launched, models deployed) instead of business (cost per transaction, error rate, time to decision). (5) No ownership transfer — when the consultant left, the capability left.

SynthesisArc's Find, Fix, Future-Proof methodology reverses the failure pattern. Find: two-week readiness assessment that diagnoses gaps and ranks opportunities. Fix: 90-day deterministic deployment with governance embedded and measurement baselined. Future-Proof: complete ownership transfer with documentation, training, and clean handoff.

The guarantee: measurable operational results within 90 days of build start, or you don't pay. No other AI consulting firm makes that promise because no other methodology supports it.