Data infrastructure maturity consultants

Data maturity assessment

2. Inference Group

Offers a dedicated Data Maturity Assessment covering architecture, integration, technology, data quality, governance, metadata, security, and organizational readiness. The output prioritizes the gaps to address before building AI systems.inferencegroup.com+2

Best fit: a structured data-readiness diagnostic with prioritized actions.

Data Maturity Assessment

3. DAI Consultancy

Evaluates data infrastructure, governance, analytics, talent, and organizational culture. Its published deliverables include a maturity scorecard, industry benchmarking, gap analysis, and a phased roadmap.daiconsultancy.com

Best fit: a formal maturity assessment spanning technology and organizational capabilities.

Data & AI Maturity Assessment

4. SEI

Provides AI readiness assessments across data quality, governance, technology infrastructure, processes, and organizational capabilities. Its stated approach produces a prioritized investment roadmap.www.sei.com

Best fit: an integrated assessment of technical readiness and business execution.

AI Readiness Assessments

5. PwC

Offers an enterprise AI readiness assessment with quantified maturity, industry benchmarking, analysis of technology infrastructure and data governance, and a sequenced transformation roadmap.www.pwc.com+2

Best fit: a large enterprise audit requiring executive reporting and organization-wide benchmarking.

Enterprise AI Readiness Assessment

Which should you approach first?

My recommendation depends on the kind of audit you want:

What your audit should cover

Whichever consultant you engage, ask them to assess six areas:

• Data quality and accessibility: Is the data complete, accurate, discoverable, and usable?
• Architecture and integration: Can systems and data pipelines support AI workloads?
• Governance and lineage: Are ownership, permissions, provenance, and compliance controls documented?
• Infrastructure and scalability: Can storage, compute, and cloud services support production workloads at a sustainable cost?
• AI-specific readiness: Can your data support retrieval-augmented generation (RAG), model training, and AI agents where relevant?
• Remediation roadmap: What must be fixed first, with estimated costs, priorities, and timelines?

These dimensions align with the assessment scopes described by Pythian, Inference Group, and PwC.www.pythian.com+2

One question to narrow the shortlist: Is your AI Readiness Audit for a large enterprise, a mid-market company, or a public-sector organization? That will help identify the most appropriate consultants and engagement style.