Free diagnostic · 6 pillars · 12 questions
AI Readiness Diagnostic
Rate where your organisation actually stands — not where you'd like to
be. Each pillar has two questions; the radar chart below fills in live
as you answer, so you can see the shape of your readiness take form.
01
Strategy Not answered How clearly defined is your AI/data strategy, and who's driving it?
Level 1 · Ad hoc No stated AI/data strategy; activity is opportunistic and undirected.
Level 2 · Emerging A strategy is being discussed, but no executive owns it yet.
Level 3 · Defined A written strategy exists with an accountable executive sponsor.
Level 4 · Managed Strategy is reviewed regularly and tied to measurable business goals.
Level 5 · Optimised Strategy is embedded in company planning, with the board and C-suite actively steering it. How are AI/data initiatives prioritised against business value?
Level 1 · Ad hoc Projects get picked based on whoever asks loudest, not business value.
Level 2 · Emerging Some informal ranking exists, but no shared criteria.
Level 3 · Defined A documented use-case backlog is scored against value and feasibility.
Level 4 · Managed Prioritisation is a regular governance ritual with cross-functional input.
Level 5 · Optimised The portfolio is continuously re-ranked against realised ROI and strategic fit. 02
Data & Technology Not answered How mature is the underlying data foundation?
Level 1 · Ad hoc Data lives in spreadsheets and personal files; every report starts with manual pulling and re-checking.
Level 2 · Emerging One or two systems hold most data, but quality and structure vary by team.
Level 3 · Defined Core data is centralised in a warehouse or lake with agreed structure and a regular refresh.
Level 4 · Managed A governed platform with clear ownership, quality checks and documented lineage across sources.
Level 5 · Optimised A trusted, near real-time single source of truth with self-serve access and a live data catalogue. How mature is the technology and engineering platform (cloud, tooling, AI infrastructure)?
Level 1 · Ad hoc Infrastructure is entirely on-premises or ad hoc; no defined technical platform.
Level 2 · Emerging Some cloud or tooling is adopted, but inconsistent and largely unmanaged.
Level 3 · Defined A defined technology stack with standard tooling for data and AI workloads.
Level 4 · Managed A cloud-first, well-architected platform supporting production AI/ML workloads.
Level 5 · Optimised A fully cloud-native, elastic platform with mature MLOps and continuous engineering improvement. 03
Governance & Risk Not answered How formal are your policies for data privacy, access and AI risk?
Level 1 · Ad hoc No policy covers data or AI use; risk isn't formally considered.
Level 2 · Emerging Informal guidelines exist but aren't documented or enforced.
Level 3 · Defined Documented policies for privacy, access and model risk exist and are partly enforced.
Level 4 · Managed A formal framework with named data owners and clear escalation paths.
Level 5 · Optimised Governance is embedded and automated, with continuous compliance monitoring. How actively is compliance and risk actually monitored?
Level 1 · Ad hoc No one tracks whether policies are actually followed.
Level 2 · Emerging Occasional manual checks, mostly reactive after an issue.
Level 3 · Defined Regular audits and defined ownership for compliance monitoring.
Level 4 · Managed Audit trails and monitoring are systematic, with reporting to leadership.
Level 5 · Optimised Proactive, largely automated risk detection with real-time alerts and remediation. 04
People & Culture Not answered How widespread is data/AI literacy and skills across the organisation?
Level 1 · Ad hoc Only a handful of specialists understand data or AI tools.
Level 2 · Emerging Pockets of skill exist, but no structured upskilling.
Level 3 · Defined Core teams have received training; skills are growing steadily.
Level 4 · Managed Data/AI literacy is broad, with role-based training programmes in place.
Level 5 · Optimised Literacy is organisation-wide; most roles can work confidently with data and AI tools. How embedded is data-driven decision-making in everyday culture?
Level 1 · Ad hoc Decisions run on gut feel; data and AI are viewed with scepticism.
Level 2 · Emerging Pockets of enthusiasm exist, but leadership isn't yet bought in.
Level 3 · Defined Appetite for data-driven decisions is growing, with visible examples.
Level 4 · Managed Leadership actively champions data/AI-informed decisions.
Level 5 · Optimised A genuinely data-first culture where decisions are consistently evidence-based. 05
Operating Model & Delivery Not answered How consistent is the delivery methodology for data/AI projects?
Level 1 · Ad hoc Projects run informally, requested ad hoc with no shared process.
Level 2 · Emerging Basic tracking exists, but method and cadence vary by team.
Level 3 · Defined A consistent delivery methodology is used for most projects.
Level 4 · Managed A mature practice with defined SLAs and stakeholder sign-off.
Level 5 · Optimised Continuous delivery with a well-oiled, repeatable operating rhythm. How mature is the release and deployment process?
Level 1 · Ad hoc Releases are manual, infrequent and risky.
Level 2 · Emerging Some structure exists, but testing and deployment are still largely manual.
Level 3 · Defined A defined release process with testing gates before deployment.
Level 4 · Managed Automated testing and deployment pipelines are standard practice.
Level 5 · Optimised Fully automated CI/CD with rapid, low-risk iteration based on live feedback. 06
Ecosystem & Partners Not answered How effectively are external vendors, platforms and partners leveraged?
Level 1 · Ad hoc No structured use of external vendors or platforms; everything is built in-house ad hoc.
Level 2 · Emerging A few vendor relationships exist, but they're managed informally.
Level 3 · Defined Vendor and platform choices are deliberate, with clear roles and contracts.
Level 4 · Managed Strategic partnerships actively extend internal capability, with regular review.
Level 5 · Optimised A well-managed ecosystem of partners and platforms accelerates delivery and innovation. How connected is the organisation to the broader data/AI ecosystem (industry, standards, community)?
Level 1 · Ad hoc No external engagement; the organisation operates in isolation.
Level 2 · Emerging Occasional awareness of industry trends, but no active participation.
Level 3 · Defined Some participation in industry groups, conferences or standards bodies.
Level 4 · Managed Active engagement with the wider ecosystem informs strategy and adoption.
Level 5 · Optimised The organisation is a recognised contributor or leader in its data/AI ecosystem. Want a second opinion on your results?
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