Cudby opens by asking what baseline exists before any AI tooling is deployed, and answers it himself: for most organisations, none. That absence is what makes impact reporting unreadable, and the session's argument is about sequencing rather than instrumentation. Adoption and engagement are leading indicators; financial return is a lagging one, and reading the lagging figure without the leading ones produces a number nobody can act on — a poor result might mean the tools do not work, or that nobody uses them, or that they are pointed at the wrong tasks. The finding drawn from this year's industry research sets the expectation for anyone planning a rollout: structured enablement determines outcomes, and switching the tools on and hoping does not work. Placed beside Amazon's own measurement work at the same conference, the notable thing is how careful the category has become about what it claims.