Data and Compliance
AI Readiness: Verify Data, Processes, and Infrastructure
A six-dimension diagnostic for determining whether the organization can operate AI before committing the project budget.
Decision supported
A company is ready when it can provide a measured problem, authorised representative data, a understood workflow, operable architecture, clear ownership, and skills to evaluate and monitor the system. Budget alone creates none of these conditions; readiness must produce blockers and a preparation plan.
Executive summary
- Assess six dimensions with evidence.
- Treat data and process before model sophistication.
- Include security, operations, and skills from the start.
- Turn every critical weakness into a prerequisite action.
Assess six readiness dimensions
Evaluate business problem, process, data, technology, governance and risk, and people and operations. One critical blocker outweighs a good average.
Start with data and the real process
Trace inputs, exceptions, decisions, rights, quality, labels, feedback, and downstream consequences before selecting architecture.
Prove the system can be operated
Define evaluation, deployment, access, monitoring, cost, support, incident, rollback, supplier, and change ownership.
Produce a targeted preparation plan
Fund only the foundations needed for the first use case, assign owners and dates, and rerun the assessment before the pilot.
Decisions to make now
Recommended actions
- 01Bring business, data, architecture, security, and operations together.
- 02Collect one proof per dimension.
- 03Isolate blockers for the first use case.
- 04Fund only required foundations.
- 05Reassess before the pilot.
Watch points
- A total score hiding a critical blocker.
- Abundant but unauthorised or unrepresentative data.
- A project team with no production owner.
Frequently asked questions
Is a data lake required?
No. Data must be accessible, understood, authorised, and fit for the case; architecture follows the need.
Can imperfect data support a pilot?
Yes when imperfection is measured, representative, and compatible with risk.
Who owns readiness?
A business sponsor with product, data, security, architecture, and operations.
Sources and verification
Last editorial verification: 14 August 2026. Links point to the source texts, authorities, and reference guides consulted.
- 01The Adoption of Artificial Intelligence in Firms
OECD. Accessed 14 August 2026.
- 02Generative AI and the SME Workforce
OECD. Accessed 14 August 2026.
- 03AI RMF Core: Govern, Map, Measure and Manage
NIST AI Resource Center. Accessed 14 August 2026.
- 04Artificial Intelligence: An Accountability Framework
U.S. Government Accountability Office. Accessed 14 August 2026.
- 05Architecting a successful generative AI proof of concept
AWS Prescriptive Guidance. Accessed 14 August 2026.
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