AI Maturity Assessment
12 questions on strategy, governance, automation and people. See your results as soon as you finish.
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Your AI maturity score
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What we measured: Your AI strategy, progress from pilot to production, and board engagement.
Why this matters: Firms with clear AI foundations were three times as likely to see cost and revenue benefits at the same time (PwC Global CEO Survey, 2026).
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What we measured: Who is accountable for AI, what is documented, and how AI outputs are checked.
Why this matters: 82% of firms using AI have AI frameworks in place, and only 34% fully understand the AI technologies they use (Bank of England and FCA).
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What we measured: How much work is still manual, how reliable your core data is, and where AI is embedded.
Why this matters: High-performing firms were 2.8 times more likely to have redesigned their workflows around AI (McKinsey State of AI, 2025).
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What we measured: Whether staff know the rules, whether training has changed behaviour, and whether experimenting is encouraged.
Why this matters: 93% of employees have put information into AI tools without company approval, and 33% have entered confidential client data (ManageEngine/Censuswide, 2025).
Each area is explained in our article An AI maturity framework for regulated financial services.
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