How should your business prepare for AI adoption?

Common questions

• What should an AI readiness assessment cover?

  Assess the business problem, workflow owner, current performance, data quality, system access, security constraints and the skills of the people involved. Readiness is not just a tool inventory or a score: it should identify what must be resolved before a particular pilot can be evaluated safely.

• How do we choose the first AI pilot?

  Choose a bounded workflow with clear inputs, a repeatable task, an accountable owner and a measurable problem. Check whether a rules-based change could solve it before adding AI. Avoid starting with an organization-wide rollout or a high-consequence decision without suitable validation and human oversight.

• What should an AI adoption roadmap contain?

  A useful roadmap states the priority use case, expected outputs, responsibilities, data and integration dependencies, training needs and review points. Distinguish discovery, prototype, pilot and production stages. At each stage, specify the evidence needed for the next investment decision rather than promising a universal delivery timeline.

• How can we evaluate an AI pilot without relying on vendor ROI claims?

  Measure the existing workflow first, then compare like-for-like tasks during the pilot. Track completion time, error and rework, output quality, human review effort and actual usage. Include subscriptions, integration and support costs; define acceptable results and stopping conditions before seeing the outcome.

• What changes when a pilot moves into production?

  Production needs named owners for access, data handling, monitoring, exceptions, incident response and maintenance. Teams also need training and a way to report failures. Confirm integration permissions, security requirements, operating costs and ongoing support separately from the prototype scope.