AI Adoption & Strategy

AI Readiness Assessment

We assess your organisation's data, infrastructure, and skills readiness before you invest in AI.

We run a structured maturity assessment across data, infrastructure, talent, and governance to pinpoint exactly where your readiness gaps are. You receive an executive report with a clear maturity score and a prioritised, actionable backlog. The findings let you make confident investment decisions aligned with Vision 2030 ambitions and SDAIA frameworks.

What's included

  • Data maturity: quality, governance, availability, and accessibility across operational sources.
  • Infrastructure, compute capacity, and cloud readiness to run AI workloads.
  • Talent and skills-gap analysis across data science, engineering, and operations.
  • A review of governance, policy, and controls over data and AI usage.
  • Privacy and security posture of the data earmarked to feed models.

Methodology & standards

01

Scoping and evidence gathering: leadership interviews, a systems and data inventory, and review of existing documentation.

02

A structured assessment across the data, infrastructure, talent, and governance axes against a tiered maturity model.

03

Gap analysis and a maturity score per axis, with remediation priorities ranked by impact and effort.

04

A stakeholder validation workshop, followed by handover of the executive report and remediation roadmap.

Deliverables

  • An executive assessment report with an overall maturity score and per-axis sub-scores.
  • A gap matrix ranked by impact and effort, with practical remediation recommendations.
  • A prioritised backlog of candidate, executable use cases.
  • A requirements map for data and infrastructure readiness that shows what is missing.
  • A board-level executive summary linking findings to investment decisions.

Regulatory controls it satisfies

ISO/IEC 42001 (AI management system)
We benchmark your AI governance maturity against the management-system structure: context, leadership, planning, and operation.
NIST AI RMF (AI Risk Management Framework)
The assessment axes are derived from the framework's functions: Govern, Map, Measure, and Manage.
NDMO Data Management & Personal Data Protection Standards
Data-domain readiness is scored against the national data management domains.
PDPL (Personal Data Protection Law)
We check the lawful basis for processing personal data before it is fed into AI models.

Typical timeline

Typically delivered in three to five weeks, depending on organisation size and the number of systems and data sources in scope.

Common questions

Do we need a mature data foundation before the assessment?

No. The assessment is designed precisely to measure your current state, whatever it is, and its output makes clear which gaps to close before you invest.

How does this differ from the AI Strategy & Roadmap service?

The assessment diagnoses your readiness and fixes the starting point; the strategy then builds the plan and delivery priorities on top of that diagnosis.