AI Readiness
FoundationsGovernance, Safety and Ethics
AI readiness is whether an organisation's data, processes and people are in a state where AI can be deployed usefully, as distinct from whether the technology itself works. A readiness gap is usually mundane: records held in a form no system can query, a process nobody has ever written down, or no named owner for the output once it arrives. Deployments stall on these far more often than on model quality.
In practice
Where a pilot succeeds and the rollout does not, the cause is normally a readiness gap rather than the model, and swapping in a better model will not close it. Assess data quality, process documentation and named ownership before committing to a deployment date, because those carry the longest lead times.