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AI readiness assessment

Ten yes / maybe / no questions across data, infrastructure, team, governance and business case. You get a 0–100 score, a readiness band, and three concrete next actions. Takes about two minutes.

Data · Single source of truth

Do you have one place where customer data is canonical, rather than five spreadsheets and three CRMs disagreeing?

Data · Labelled or annotated history

Is your historical data tagged or annotated in a way an ML model could learn from?

Infrastructure · API layer

Do you have an API layer that exposes your core data — so AI tools can read and act on it without going through screens?

Infrastructure · Cloud presence

Is your stack on AWS, GCP, or Azure?

Team · Senior engineer to oversee AI

Do you have someone senior on staff who can own an AI integration, including the boring parts (evals, prompts, fallbacks)?

Team · Shipping behind feature flags

Is your team comfortable putting features behind flags, doing canary rollouts, and rolling back fast when something misbehaves?

Governance · Data classification policy

Do you have a documented policy that says what data is sensitive, what can be sent to third-party AI APIs, and what cannot?

Governance · Executive sponsor

Is there a named executive accountable for AI initiatives — not just enthusiastic, but accountable?

Business case · KPI an AI feature would move

Have you identified a measurable business KPI an AI feature would actually move (e.g. response time, conversion rate, churn)?

Business case · Sized ROI

Have you sized the ROI in £/$ terms? Even a rough back-of-envelope number counts.

AI readiness score

Answer all ten questions to see your score.

0 25 50 75 100 Foundational Emerging Operational Advanced
Data
Infrastructure
Team
Governance

Recommended next actions

Email me the full report

We'll send your score, the breakdown per category, and three tailored next actions you can hand to your team.

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