Assessment framework · Data & AI
Data & AI Governance assessment
Review data governance processes, systems and practices — spanning data management, security, lineage, quality, intelligence, sharing, AI ethics and privacy — to manage data across its lifecycle and deliver business outcomes.
Assess people capabilities, process effectiveness and practices for governing data and AI.
What it covers
Inside the Data & AI Governance assessment.
Celeredge scores governance across eight dimensions — data management, security, lineage, quality & monitoring, intelligence, sharing & collaboration, AI ethics & governance, and privacy & compliance — and ranks where governance is below best practice.
- Scored on Data & AI Governance's own scale, not a generic rubric
- Every score traceable to the client's own evidence
- Gaps ranked by severity, ready to become the plan
- A board-ready slide deck and detailed report, generated automatically
How it works
From the client's documents to a board-ready deck.
1 · Evidence in
Upload the client's documents: policies, reports, data. An AI interviewer asks targeted follow-ups to fill anything missing.
2 · Scored on the standard
Every dimension is scored on the framework's own scale, with each score traceable to the evidence behind it, and gaps ranked by severity.
3 · Board-ready out
A board-ready slide deck and HTML report are generated automatically: executive summary, maturity landscape and a sequenced plan.
Questions
Data & AI Governance assessment FAQ
What is Data & AI Governance?
Review data governance processes, systems and practices — spanning data management, security, lineage, quality, intelligence, sharing, AI ethics and privacy — to manage data across its lifecycle and deliver business outcomes.
What does a Celeredge Data & AI Governance assessment deliver?
An evidence-based maturity or readiness assessment scored on Data & AI Governance's own scale, with gaps ranked by severity and an auto-generated, board-ready slide deck and detailed report. Every score is traceable to the evidence behind it.
How does the Data & AI Governance assessment work?
Clients upload their own evidence: policies, reports and data. An AI interviewer asks targeted follow-ups to fill anything missing, the platform scores against the framework, ranks the gaps, and generates the deliverables.
More Data & AI frameworks
Related assessments
ISO/IEC 42001 AI Management System
Assess AI management-system readiness against ISO 42001 before certification.
NIST AI Risk Management Framework
Score AI risk practice across the NIST AI RMF Govern, Map, Measure and Manage functions.
EU AI Act Readiness
Classify AI systems by risk tier and assess obligations under the EU AI Act.
AI Governance & Responsible AI Maturity
Measure responsible-AI maturity across governance, risk, transparency and oversight.
Data Management Maturity (DAMA-DMBOK)
Score the data discipline against the DAMA-DMBOK knowledge areas: governance, quality, architecture and operations.
UK AI Regulation (DSIT Principles & Assurance)
Check alignment to the UK's five AI-regulation principles and assurance expectations.
UK GDPR & Data Protection / ICO Accountability
Assess UK GDPR accountability against the ICO's accountability framework.
DCAM Data Management Capability
Benchmark capability against the EDM Council DCAM model, the data-governance standard favored in financial services.
MLOps & Model Operations Maturity
Assess the maturity of model deployment, monitoring and lifecycle operations.
Analytics & BI Maturity
Measure analytics and BI maturity from reporting to embedded decision intelligence.
Data Strategy Assessment
Evaluate data maturity across governance, quality, architecture, analytics and culture.
See the Data & AI Governance assessment on real data.
We'll run Data & AI Governance live and score it from a client's own documents.