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What's inside
- Four data dimensions. Three questions per dimension across Quality, Classification, Governance, and Integration. The four things that determine whether an AI use case is even possible.
- Project go/no-go framing. Each question maps to a specific data foundation. Answering 'no' to more than three questions is a strong signal the AI project should pause for data work first.
- UK-anchored. References UK GDPR, ICO data-protection principles, and DPIA framework where relevant.
Who this is for
Anyone scoping an AI project where the project depends on internal company data — most B2B AI use cases. Useful for project sponsors, data leads, IT directors, and senior decision-makers.
How to use this
Run the checklist for each AI use case in scope. Twelve minutes per use case. Answer honestly. Anything answered 'no' is data foundations work that needs to happen before (or alongside) the AI project — not after.
Frequently asked
Why does data readiness matter more than AI readiness?
Data readiness is the gating factor on most AI projects. A perfect model on poor data underperforms a mediocre model on clean data. UK businesses consistently under-invest in data readiness relative to AI tooling.
Is this the same as a DPIA?
No. A DPIA (Data Protection Impact Assessment) is a UK GDPR-anchored process specifically about personal data risks. This checklist is broader — data quality, integration, governance — and applies whether or not personal data is in scope.
Does this apply if we're only using public LLMs (no fine-tuning)?
Yes — even prompt-only AI use depends on the quality, classification, and governance of the data you put into the prompts.
How does this fit alongside the AI Readiness Scorecard?
The scorecard scores 'Data' as one of five dimensions. The checklist is the deeper-dive that surfaces the specific data foundations the score reflects.
What if our score is bad on this checklist?
It's normal to score poorly on first run. Data foundations work is typically 6–18 months of cleanup before AI projects can scale safely. Better to know now than during the project.
Related Arx Certa services
If the gaps this resource surfaces for your business need outside help to close:
- AI services — implementation reviews, AI policy work, vendor due diligence, and pilot scoping.
- Cybersecurity — security overlay for AI use, UK GDPR / NCSC alignment, vendor risk assessment.
- Database — data foundations work AI projects depend on.
- Infrastructure — cloud, identity, network and integration foundations.
Score your AI readiness in 4 minutes
The Arx Certa AI Readiness Scorecard quantifies the foundations this resource describes — across governance, data, infrastructure, security and use case. Free, 12 questions, personalised report.
Get your AI readiness score →