About This Tool

The MIMER AI Assessment Tool helps organisations understand where they stand on the AI adoption journey and what support they need to move forward.

Purpose

Many organisations want to adopt AI but struggle to assess their own readiness. This tool provides a structured, evidence-based way to evaluate maturity across five key dimensions, map the result to one of eight adoption stages, and identify the most impactful next steps.

How it works

  1. Choose dimensions & sector: Select your sector and optionally reorder the five dimensions to match your priorities.
  2. Answer 25 questions: Five questions per dimension, each scored 1–4. You can navigate back at any time.
  3. See your results: Instantly view dimension scores, an overall maturity stage, and a radar chart of your profile.
  4. Get support: Submit your contact details to receive tailored guidance aligned to your stage.

The Five Dimensions

  • Strategy & Leadership: Assesses leadership vision, strategic intent, and organisational commitment to AI adoption.
  • Data Readiness: Evaluates the availability, quality, governance, and accessibility of data for AI initiatives.
  • Team & Competence: Measures AI skills, training, roles, and operational practices within the organisation.
  • Technology & Infrastructure: Reviews compute resources, tooling, scalability, and production monitoring capabilities.
  • Process & Governance: Examines how AI outputs are used, validated, governed, and evaluated for business impact.

Scoring

1
Not at all
2
Early stages
3
Progressing
4
Fully

Each dimension score is the average of its five question scores. The overall score (1.0–4.0) is the average of the five dimension scores. This overall score determines the maturity stage below.

The 8 Maturity Stages

# Stage Score range Client status Expected outcome Support focus
1 Exploring 1.0–1.5 Curious about AI, no concrete steps taken Informed decision on whether and how to pursue AI Executive briefings, AI landscape overview, opportunity mapping
2 Framing 1.5–2.0 Interest identified, path forward unclear Prioritised AI use cases with clear rationale Use-case workshops, feasibility assessments, business-case support
3 Preparing 2.0–2.3 Foundations identified, not yet operational Actionable readiness plan across key gaps Readiness assessments, gap analysis, foundational capability building
4 Building 2.3–2.6 First AI initiatives under development Early evidence of value from initial projects Technical mentoring, resource access, hands-on project support
5 Validating 2.6–2.9 Initial solutions working, not yet embedded in operations Validated AI solutions ready for integration Integration support, validation frameworks, stakeholder alignment
6 Expanding 2.9–3.2 Proven value in isolated cases, scaling challenges remain Repeatable, organisation-wide AI capability Operational scaling, process standardisation, capability development
7 Optimising 3.2–3.6 Mature capabilities, seeking efficiency and depth Optimised, high-performance AI operations Advanced optimisation, infrastructure scaling, research collaboration
8 Leading 3.6–4.0 AI fully embedded across the organisation Strategic autonomy and continuous innovation Peer collaboration, community building, frontier research partnerships