AI doesn't fail. The organisations underneath it do.

Independent research keeps landing on the same number. MIT’s 2025 review of AI initiatives found 95% delivered no measurable financial return. RAND puts the failure rate above 80%. The tools aren’t the problem. What they’re being run on top of usually is.

MML doesn’t sell AI tools and doesn’t write AI strategy. The work is diagnostic: establishing whether the operating model, governance, data and decision rights underneath an AI investment can actually carry it. That diagnosis comes first. Everything built afterwards depends on it being accurate.

1. Start with the Baseline or go straight to the Diagnostic, depending on how much you already know.
2. Six domains get assessed against a consistent set of criteria: operating model, governance, data quality, decision rights, leadership and psychological safety, delivery maturity.
3. You get a written output, either a scored report or a full heat map, with a clear view of where the risk actually sits and why.

Built by Sarah, an agile coach and organisational diagnostician who spent her career inside delivery organisations watching this exact failure pattern play out, first with agile, now with AI. More on that on the About page →