AI Governance Consulting Decision Framework
How to choose the right AI governance consulting firm — framework depth, platform integration, vertical experience, deliverables, and cost benchmarks.
Evaluate any firm on the same evidence
EPC Group wrote this framework and sells AI governance consulting, so read it as one view. The criteria ask for evidence rather than claims, and they apply to every firm on your list, including EPC Group.
- Standards mapping: ask for a redacted control map to NIST AI RMF 1.0 and ISO/IEC 42001; a proprietary framework sold as the standard is a red flag.
- Platform enforcement: ask for configuration and test evidence showing each policy enforced in the platforms you run.
- Your regulators: ask for a mapping of the guidance that applies to your industry, item by item.
- Independence: ask for a written disclosure of vendor partnerships and any resale or referral incentives.
- Named team and references: ask who does the work, and for two references from your industry you can call.
- Ownership and exit: confirm in the contract that you own every artifact and can run the program without the firm.
Download the evaluation rubric (CSV): ten weighted criteria, the evidence to request and the red flags for each, and score columns for three firms (0–3 per criterion, 60 points maximum). It is a sample rubric, not a ranking.
Frequently Asked Questions
What should we evaluate first when choosing an AI governance consulting firm?
Framework depth — does the firm actually implement recognized standards or does it invent proprietary frameworks that lock you in? Best-fit firms deploy NIST AI RMF 1.0, EU AI Act compliance, ISO/IEC 42001 (AI Management Systems), and where applicable industry-specific frameworks (HIPAA AI guidance, SR 11-7 for banks, NAIC AI Model Bulletin for insurance). Firms selling their own proprietary framework as the 'solution' are a red flag — regulators want to see recognized standards, not vendor-specific.
How does platform integration factor in?
AI governance without platform integration is just a document. The AI governance framework has to actually be enforced by controls in the AI platforms your organization uses. Microsoft-shop enterprises need firms with deep Microsoft Purview + Copilot governance + Copilot Studio + Azure OpenAI experience. Google Cloud shops need Vertex AI governance + Google Model Armor experience. AWS shops need Bedrock governance + Guardrails experience. Multi-cloud enterprises need firms with experience across all three. Test in the sales cycle: 'show me a governance framework document you deployed on my exact stack.'
What vertical experience matters?
Six verticals have materially different AI governance requirements. (1) Healthcare — HIPAA + PHI handling + FDA AI/ML guidance. (2) Financial services — SR 11-7 model risk + FINRA + OCC AI + GLBA. (3) Federal — FedRAMP High + CMMC + CUI + FOIA + Executive Order 14179 and current OMB AI guidance (Executive Order 14110 was revoked in January 2025). (4) Insurance — NAIC AI Model Bulletin + state-specific rules (Colorado, NY DFS). (5) Life sciences — FDA 21 CFR Part 11 electronic records + GxP. (6) Legal — attorney-client privilege + work-product doctrine. Firms without vertical-specific experience add cost and reduce success probability for regulated organizations.
What deliverables should the engagement produce?
Six categories. (1) AI Governance Framework document — NIST AI RMF / EU AI Act / ISO 42001 mapped. (2) AI Portfolio Inventory — every AI use case + risk tier + owner. (3) Sensitivity + Retention Label Taxonomy for AI-affected content. (4) Platform-specific controls deployed (DLP for Copilot policies, Vertex AI evaluation frameworks, Bedrock Guardrails). (5) Incident Response Runbook for AI-specific incidents (oversharing, decisioning failure, agentic action reversal). (6) Board / audit reporting template. Firms delivering fewer than these six categories are not producing a complete governance program.
What does AI governance consulting cost?
Baseline engagement (mid-market enterprise, single platform): scoped after discovery for a 3-6 month program producing the six deliverables above. Multi-platform engagements (Microsoft + Google + AWS) are scoped after discovery. Enterprise programs with a full AI CoE build run 6-12 months. Vertical-specific overlays (banking, healthcare, federal) add scope. EPC Group offers fixed-fee accelerators for common scopes; larger engagements custom-scoped after discovery.
Talk to a senior architect
Email contact@epcgroup.net or call 888-381-9725.
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