A focused course, tailored for you
Advanced AI Strategy for Big4-Adjacent Consulting Partners
An advanced AI strategy playbook for partners at Big4-adjacent consulting firms in 2026: EU AI Act high-risk classification playbook, NIST AI RMF mapping framework, customer-side governance committee playbook, retainer engagement structure.
AI Strategy partners at Big4-adjacent consulting firms carry 8-to-12 active customer engagements each, all asking the same regulatory questions. The course delivers the reusable answer.
$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
AI Strategy partners at Big4-adjacent consulting firms (the firm Applied Intelligence, IBM Consulting, BCG GAMMA, McKinsey QuantumBlack, Bain Vector, the firm Invent, the firm AI Strategy) carry 8-to-12 active customer engagements each. Each engagement carries an EU AI Act high-risk classification question, a NIST AI RMF mapping question, and a customer-side governance committee question. Each partner is doing each question from scratch every engagement.
The course works through the reusable answer. The EU AI Act high-risk classification playbook. The NIST AI RMF mapping framework. The customer-side AI governance committee playbook. The customer-side AI use-case taxonomy. The customer-side AI impact-assessment framework. The customer-side AI technical-documentation framework. The customer-side AI human-oversight framework. The customer-side AI audit-trail integration. The engagement structure that converts each customer ask into a multi-quarter retainer. Twelve modules with deliverables. Plus a hand-built playbook for your specific account mix.
What you walk away with
- A documented EU AI Act high-risk classification playbook.
- A NIST AI RMF mapping framework.
- A customer-side AI governance committee playbook.
- A customer-side AI use-case taxonomy.
- A customer-side AI impact-assessment framework.
- A customer-side AI technical-documentation framework.
- A customer-side AI human-oversight framework.
- A customer-side AI audit-trail integration.
- An engagement structure for the retainer conversion.
- A 10-week build plan.
The 12 modules
Module 1. The 2026 advanced AI strategy landscape
Walkthrough of the 2026 advanced AI strategy landscape. The EU AI Act enforcement status. The NIST AI RMF adoption status. The competitive landscape across Big4-adjacent AI Strategy practices. The customer-side AI governance committee profile. The strategic decisions an AI Strategy partner faces in 12-month portfolio planning. The friction profile that slows customer engagement momentum.
Module 2. EU AI Act high-risk classification playbook
Build the EU AI Act high-risk classification playbook. The Annex III high-risk use-case framework. The use-case-classification framework. The high-risk-obligation framework. The customer-side conformity-assessment framework. The customer-side post-market-monitoring framework. The integration with the customer's existing AI governance framework. Plus the worked example for a customer's first three high-risk AI use cases.
Module 3. NIST AI RMF mapping framework
Build the NIST AI RMF mapping framework. The GOVERN function mapping. The MAP function mapping. The MEASURE function mapping. The MANAGE function mapping. The customer-side risk-classification framework integration. The customer-side risk-treatment plan integration. The integration with the customer's existing risk-management framework. Plus the worked example for a customer's first integrated NIST AI RMF mapping.
Module 4. Customer-side AI governance committee playbook
Build the customer-side AI governance committee playbook. The committee composition. The committee cadence. The committee decision framework. The committee escalation framework. The committee reporting framework. The integration with the customer's existing risk-management committee. The integration with the customer's existing audit committee. Plus the worked example for the customer's typical AI governance committee.
Module 5. Customer-side AI use-case taxonomy
Build the customer-side AI use-case taxonomy. The customer-side use-case identification. The customer-side use-case classification. The customer-side use-case prioritisation. The customer-side use-case roadmap framework. The integration with the customer's existing AI-strategy cadence. Plus the worked example for the customer's first three AI use cases under the taxonomy.
Module 6. Customer-side AI impact-assessment framework
Build the customer-side AI impact-assessment framework. The risk identification approach. The risk-classification framework. The risk-treatment plan structure. The stakeholder consultation framework. The documentation pattern. The review cadence. The integration with the customer's existing privacy-impact-assessment framework. Plus the worked example for the customer's first three impact assessments.
Module 7. Customer-side AI technical-documentation framework
Build the customer-side AI technical-documentation framework. The model-card pattern. The dataset-documentation pattern. The accuracy and robustness documentation. The bias-monitoring documentation. The conformity-assessment evidence chain. The integration with the customer's existing AI-governance committee. Plus the worked example for the customer's first three model cards.
Module 8. Customer-side AI human-oversight framework
Build the customer-side AI human-oversight framework. The decision-point design. The override pattern. The audit-log of overrides. The training framework for the customer-side decision-makers. The integration with the customer's existing operational-workflow cadence. Plus the worked example for the customer's first three human-oversight implementations.
Module 9. Customer-side AI audit-trail integration
Build the customer-side AI audit-trail integration. The decision-log structure. The override-log structure. The model-version-log structure. The integration with the customer's existing audit-trail infrastructure. The integration with the customer's existing SIEM. The integration with the customer's existing GRC platform. Plus the worked example for the customer's typical audit-evidence response.
Module 10. Engagement structure for the retainer conversion
Build the engagement structure for the retainer conversion. The discovery phase. The diagnostic phase. The transformation phase. The sustainment phase. The renewal conversation. The integration with the customer's existing IT-programme cadence. Plus the worked example for a 12-month customer engagement that converts to a multi-quarter retainer.
Module 11. Big4-adjacent differentiation framework
Build the Big4-adjacent differentiation framework. The Big4 AI Strategy practice alignment story. The boutique AI Strategy practice alignment story. The hyperscaler AI services alignment story. The customer-honest positioning for each. The where-the-practice-wins-and-where-it-does-not framing. Plus the worked example for a customer who has evaluated a Big4 or hyperscaler alternative.
Module 12. Your 10-week build plan
Week by week. Weeks 1-2: landscape and EU AI Act high-risk classification playbook. Weeks 3-4: NIST AI RMF mapping framework and customer-side AI governance committee playbook. Weeks 5-6: customer-side AI use-case taxonomy and impact-assessment framework. Weeks 7-8: technical-documentation, human-oversight, audit-trail. Weeks 9-10: engagement structure for retainer conversion, Big4-adjacent differentiation framework. Deliverable: a reusable advanced AI strategy playbook ready for the next customer engagement.
How this addresses your situation
Specific modules that map to what you said you are dealing with.
EU AI Act classification question → Module 2.
NIST AI RMF mapping question → Module 3.
Customer AI governance committee → Module 4.
Customer AI use-case taxonomy → Module 5.
Customer impact assessment → Module 6.
Customer technical documentation → Module 7.
Customer human oversight → Module 8.
Customer audit trail → Module 9.
Retainer conversion → Module 10.
What you get with this course
- The 12-module course delivered as text plus downloadable templates.
- Templates and worked examples for every module.
- A hand-built playbook generated for your specific account mix.
- Three reference engagements from peer Big4-adjacent AI Strategy practices.
- Scripted talking points for the customer AI governance committee engagement.
What you will have in hand by Day 1, Week 1, Month 1
Day 1: EU AI Act high-risk classification playbook scaffold drafted.
Week 4: NIST AI RMF mapping framework and customer-side AI governance committee playbook designed.
Week 8: Use-case taxonomy, impact-assessment, technical-documentation, human-oversight, audit-trail operational.
Week 10: Playbook ready for next customer engagement.
Before and after
Before
Each question from scratch every engagement. Partner time burned. Retainer conversion lags.
After
Reusable answer. Each customer ask converts to a multi-quarter retainer. Partner time scales.
What happens if you do not address this
EU AI Act enforcement and NIST AI RMF adoption cadences accelerate. AI Strategy partners who do not package the reusable answer lose customer pipeline.
Who it is for
For AI Strategy partners at Big4-adjacent consulting firms, principal AI Strategy consultants, senior AI Strategy leaders at peer firms, and senior consultants delivering AI Strategy customer engagements.
Who this is NOT for. Pure non-AI-Strategy practitioners. Practitioners with no consulting context. Pure non-customer-facing roles.
How it arrives
Text-based course via LMS, plus downloadable templates and worked examples and the hand-built playbook.
Time investment. Roughly 18 hours of reading and 60 to 120 hours of build effort across the 10-week plan.
Why $199 is the right number
External advanced AI strategy practice positioning consultants charge from 100,000 to 500,000 USD for practice-pivot programmes. 199 USD buys the focused playbook and the implementation document for your account mix.
FAQ
Does this cover the customer's existing OpenAI integration?
Module 4 covers OpenAI integration adjacency.
What about Anthropic Claude integration?
Module 4 covers Anthropic integration adjacency.
Does this cover the customer's existing Microsoft Azure OpenAI integration?
Module 4 covers Azure OpenAI integration.
What is in the implementation playbook for me specifically?
Playbook tuned to your account mix, EU AI Act classification matched to your customer industry concentration, retainer conversion structure pre-loaded with your typical sales cycle.
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.
