Description

A focused course, tailored for you

Building the Independent AI Governance and Strategy Consulting Practice (NIST AI RMF + EU AI Act + Sector Overlays + Enterprise Operating Model + Engagement Economics)

Build the independent AI governance and strategy consulting practice in 10 weeks. NIST AI RMF + EU AI Act + sector overlays + enterprise operating model + engagement economics.

Independent AI governance and strategy consultants compete with Big4 AI practices on enterprise engagements. Clients ask for NIST AI RMF alignment, EU AI Act compliance, sector-specific AI governance overlays, enterprise operating model design for AI, and engagement economics that work. Consultants who build the modern practice take the senior enterprise work. Here is the 10-week build.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

Independent AI governance and strategy consultants (boutique AI advisory practices, solo AI strategists, mid-tier AI consultancies, fractional Chief AI Officers) compete with Big4 AI practices (the firm AI Institute + AI Consulting, the firm Trusted AI, the firm.ai, the firm AI) and specialist firms (Anthropic Professional Services, OpenAI Enterprise, Microsoft AI Consulting, Google Cloud AI Consulting, Hugging Face Solutions) on enterprise engagements.

Enterprise clients (FS firms under Fed SR 11-7 and EU DORA and EU AI Act, healthcare under FDA AI/SaMD and EU AI Act and HIPAA, public sector under FedRAMP and CISA and EU AI Act and AI EO, manufacturing under EU NIS2 and EU AI Act, retail under EU AI Act and state privacy laws, telco under EU NIS2 and EU AI Act) ask for NIST AI RMF alignment (Govern, Map, Measure, Manage), EU AI Act compliance framework (risk classification, conformity assessment for high-risk AI, GPAI obligations, transparency obligations, post-market monitoring), sector-specific AI governance overlays, enterprise operating model design for AI (Centre of Excellence, federated, hybrid), AI risk taxonomy and quantification, AI vendor due-diligence, AI workforce design, and engagement economics that work for independent practice.

Consultants who build the modern practice take the senior enterprise work. Consultants who stay on classic 'AI policy + training deck' patterns watch the senior work shift to peers.

This course teaches the 10-week build of the independent AI governance and strategy consulting practice: NIST AI RMF framework, EU AI Act compliance framework, sector overlays, enterprise operating model framework, AI risk and quantification framework, AI vendor due-diligence, AI workforce design, engagement economics, and the client engagement model. Twelve modules with deliverables. Plus a hand-built implementation playbook for your specific practice and client mix.

What you walk away with

A documented NIST AI RMF framework.
An EU AI Act compliance framework.
Sector-specific AI governance overlays.
An enterprise operating model framework for AI.
An AI risk and quantification framework.
An AI vendor due-diligence framework.
An AI workforce design framework.
An engagement economics framework.
A 10-week build plan.

The 12 modules

Module 1. AI governance and strategy landscape 2026

Detailed walkthrough of the AI governance and strategy landscape in 2026: NIST AI RMF 1.0 + GenAI Profile, EU AI Act (high-risk obligations from August 2026, GPAI from August 2025, prohibited from February 2025), UK AI principles, AU AI Ethics Framework, Singapore Model AI Governance Framework, Canada AIDA, Brazil AI Act, ISO/IEC 42001 AIMS (Artificial Intelligence Management System), sector-regulator AI guidance (Fed, OCC, FDIC, CFPB, NAIC, FDA, EEOC, OCR HIPAA, OFCCP), and the strategic-level decisions facing independent consultants.

Module 2. NIST AI RMF framework

Build the NIST AI RMF framework: Govern function alignment (governance structures, policies, accountability, workforce, transparency), Map function alignment (context, AI-system categorisation, AI-system impacts), Measure function alignment (impact-assessment, performance-assessment, risk-assessment), Manage function alignment (risk-treatment, response, monitoring), GenAI Profile application, and the integration with broader risk management. Three NIST AI RMF patterns at peer engagements.

Module 3. EU AI Act compliance framework

Build the EU AI Act compliance framework: AI-system identification (which features are AI under the EU AI Act definition), risk classification (unacceptable, high-risk Annex III, limited-risk, minimal-risk, GPAI), prohibited-practices framework, high-risk obligations framework (risk management system, data governance, technical documentation, record-keeping, transparency, human oversight, accuracy and robustness and cybersecurity, conformity assessment, CE marking, post-market monitoring), GPAI obligations framework, transparency obligations framework, sandbox framework, and the integration with broader product compliance.

Module 4. Sector overlays

Build the sector overlays: FS sector overlay (Fed SR 11-7, ECB TRIM, OCC AI guidance, CFPB UDAAP, NAIC Model Bulletin on AI, Colorado Reg 10-1-1 for life insurance, NY DFS Letter on AI), healthcare overlay (FDA AI/ML SaMD Action Plan, FDA PCCP guidance, OCR HIPAA application to healthcare AI, EU MDR/IVDR overlap), public sector overlay (FedRAMP, CISA, OMB M-24-10 on AI use in government, state AI offices), manufacturing overlay (EU NIS2 + CER for AI in critical infrastructure), retail and consumer overlay (state privacy laws application, EEOC for hiring AI, NYC LL 144, Illinois AIVIA, California AB 2930, Colorado AI Act), telco overlay (EU NIS2 + EU AI Act for AI in telco operations), and the integration with broader sector strategy.

Module 5. Enterprise operating model framework

Build the enterprise operating model framework for AI: AI Centre of Excellence model, federated AI operating model, hybrid AI operating model, AI Office and CAIO role design, AI committee structure (executive AI committee, AI risk committee, AI ethics committee, AI workforce committee), decision-rights framework, AI-system inventory framework, AI-system lifecycle management framework, and the integration with broader operating model.

Module 6. AI risk and quantification framework

Build the AI risk and quantification framework: AI risk taxonomy (model risk, data risk, security risk, privacy risk, fairness risk, explainability risk, vendor risk, workforce risk, third-party-data risk, deployment risk, monitoring risk), quantification methodology (FAIR-AI, Monte Carlo, scenario-based, expected-loss), AI risk-tier framework, AI risk-treatment framework, AI risk-monitoring framework, and the integration with broader risk management.

Module 7. AI vendor due-diligence framework

Build the AI vendor due-diligence framework: AI vendor inventory framework, AI-vendor security due-diligence (SOC 2 Type II, ISO 27001/27017/27018/27701, FedRAMP if applicable, IRAP if applicable), AI-vendor compliance due-diligence (EU AI Act provider obligations, sector-overlay compliance), AI-vendor contract framework (data-isolation, audit-rights, model-disclosure, incident-notification, exit), AI-vendor monitoring framework, and the integration with broader vendor management.

Module 8. AI workforce design framework

Build the AI workforce design framework: AI-skills taxonomy maintenance, AI-skills demand forecasting, AI-skills supply forecasting, build-vs-buy-vs-borrow framework, AI-skills upskilling framework, AI-skills capability academy framework, AI-skills career-architecture framework, AI-skills change-management framework, and the integration with broader workforce planning.

Module 9. Sustainability and ethics framework

Build the sustainability and ethics framework: AI sustainability framework (model-compute energy efficiency, model-training energy efficiency, inference-energy efficiency, data-centre PUE optimisation, carbon-aware inference scheduling), AI ethics framework (fairness, accountability, transparency, contestability, explainability, harm minimisation), AI bias-monitoring framework, AI explainability framework, and the integration with broader sustainability and ethics strategy.

Module 10. Engagement economics

Build the engagement economics framework: assessment-engagement structure, design-engagement structure, implementation-oversight engagement structure, retainer engagement structure, fractional-CAIO engagement structure, sub-contractor model, AI-augmented productivity, and the practice-economics framework.

Module 11. Client engagement model

Build the client engagement model: client-CEO engagement framework, client-CAIO engagement, client-CTO engagement, client-CIO engagement, client-CISO engagement, client-CCO engagement, client-CRO engagement, client-board-AI-committee engagement, executive-business-review framework, and the integration with broader account management.

Module 12. Your 10-week build plan

Week-by-week plan with weekly deliverables. Weeks 1-2: AI governance and strategy landscape + NIST AI RMF framework. Weeks 3-4: EU AI Act compliance framework + sector overlays. Weeks 5-6: enterprise operating model framework + AI risk and quantification framework. Weeks 7-8: AI vendor due-diligence framework + AI workforce design framework. Weeks 9-10: sustainability and ethics + engagement economics + client engagement. Deliverable: independent AI governance and strategy consulting practice.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

Module 1 covers the landscape.

Module 2 produces NIST AI RMF.

Module 3 covers EU AI Act compliance.

Module 4 covers sector overlays.

Module 5 covers enterprise operating model.

Module 6 covers AI risk and quantification.

Module 7 covers AI vendor due-diligence.

Module 8 covers AI workforce design.

Module 9 covers sustainability and ethics.

Module 10 covers engagement economics.

Module 11 covers client engagement.

Module 12 covers the 10-week build plan.

What you get with this course

The 12-module course delivered as text plus downloadable templates.
Templates and worked examples for NIST AI RMF framework, EU AI Act compliance framework, sector overlays, enterprise operating model framework, AI risk and quantification framework, AI vendor due-diligence framework, AI workforce design framework, sustainability and ethics framework, engagement economics framework, client engagement model.
A hand-built implementation playbook generated for your specific practice and client mix.
Three worked examples of independent AI governance and strategy consulting practices at peer firms.
Scripted talking points for the client CAIO and CEO engagement.

What you will have in hand by Day 1, Week 1, Month 1

Day 1: NIST AI RMF framework scaffold drafted.

Week 4: EU AI Act compliance + sector overlays designed.

Week 8: Enterprise operating model + AI risk + vendor due-diligence + workforce design operational.

Week 10: Practice in operation.

Before and after

Before

Your independent practice loses AI engagements to Big4 AI practices. NIST AI RMF + EU AI Act integration is reactive. Sector overlays are thin. Enterprise operating model design lags. Senior enterprise work goes to peers shipping the modern practice.

After

An independent AI governance and strategy consulting practice is in operation. NIST AI RMF framework, EU AI Act compliance framework, sector overlays, enterprise operating model framework, AI risk and quantification framework, AI vendor due-diligence framework, AI workforce design framework, sustainability and ethics framework, engagement economics framework, client engagement model are all designed.

What happens if you do not address this

Consultants without the modern practice lose engagements. EU AI Act high-risk obligations from August 2026; NIST AI RMF + GenAI Profile sets US federal baseline; sector regulators publish AI guidance.

Who it is for

For independent AI governance and strategy consultants, principals at boutique AI advisory practices, senior AI consultants at mid-tier firms, fractional Chief AI Officers, and senior strategy leaders pivoting to AI advisory.

Who this is NOT for. Pure ML engineers without governance scope. Consultants at firms with no AI-advisory business. Pure compliance consultants without AI scope.

How it arrives

Text-based course via LMS, plus downloadable templates and worked examples and the hand-built implementation playbook.

Time investment. Roughly 18 hours of reading and 60 to 120 hours of consultant effort across the 10-week build.

Why $199 is the right number

External AI-governance consultants (Big4 AI practices, McKinsey QuantumBlack AI, BCG GAMMA, Bain Vector, the firm AI, the firm AI, IBM Consulting AI, specialist firms like Anthropic Professional Services, OpenAI Enterprise) charge $300K-$3M for governance programmes. Specialist AI compliance firms (Holistic AI, Credo AI, FairNow, Trustworthy AI, Modulos, Trustible) charge $50K-$500K. $199 buys the focused playbook plus the implementation document for your specific practice.

FAQ

Will this replace hiring an AI-governance specialist?

Partially. It teaches the modern practice. You may still want specialist input for complex EU AI Act conformity assessment.

What if my clients are primarily public sector (not enterprise)?

Module 4 covers public-sector-anchored patterns.

Does this cover Canada AIDA / Brazil AI Act / Singapore Model AI specifically?

Module 1 covers cross-jurisdictional regulator overlap.

What about ISO/IEC 42001 AIMS certification?

Modules 1 and 2 cover ISO 42001 AIMS.

What is in the implementation playbook for me specifically?

NIST AI RMF framework tailored to your specific client mix; EU AI Act compliance framework matched to your client AI use cases; a 10-week build plan.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.