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DAT1152 Mastering ISO 42001 for M&A Leaders in Private Equity Advisory

$199.00
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A tailored course, built for your situation

Mastering ISO 42001 for M&A Leaders in Private Equity Advisory

Build AI governance frameworks that position you as the trusted authority in high-stakes transactions

$199 one-time
24-hour access provisioning 30-day money-back guarantee Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
AI governance still feels like a compliance afterthought in most transactions

The situation this course is for

Most advisors treat AI governance as a post-signing checklist item, waiting until integration to define controls. But PE firms now expect governance posture to be priced into due diligence. Without a structured framework, advisors risk losing influence, deals face higher scrutiny, and integration timelines stretch unnecessarily.

Who this is for

Senior transaction advisor at a global professional services firm, leading AI governance components in PE-driven M&A, advising on deal structure, integration planning, and risk positioning

Who this is not for

Junior analysts, compliance generalists without M&A exposure, or professionals outside transaction advisory

What you walk away with

  • Structure ISO 42001-aligned AI governance frameworks within 72 hours of deal announcement
  • Position yourself as the definitive internal reference on AI accountability in PE integrations
  • Embed governance requirements directly into LOI and SPA negotiation points
  • Confidently lead cross-functional teams on AI risk scoping before Day 1 planning begins
  • Produce integration-ready governance documentation that stands up under regulatory scrutiny

The 12 modules (with all 144 chapters)

Module 1. The PE Transaction Lifecycle and AI Governance Touchpoints
Map ISO 42001 requirements to each phase of a private equity deal, from initial diligence to post-close integration, identifying where governance becomes a value lever.
12 chapters in this module
  1. How PE value horizons shape AI governance expectations
  2. Key moments when AI risk posture influences deal terms
  3. Aligning ISO 42001 controls with 100-day integration milestones
  4. Governance scoping during vendor and technology due diligence
  5. Identifying AI-reliant systems in target operating models
  6. Assessing AI model lineage in acquired software portfolios
  7. Timing the first governance workshop post-announcement
  8. Integrating AI oversight into integration management offices
  9. Working with tech due diligence teams on model risk
  10. Setting thresholds for AI control exceptions in deals
  11. Prioritising high-impact AI systems for immediate review
  12. Building governance momentum before Day 1 planning
Module 2. ISO 42001 Fundamentals in Transaction Contexts
Translate the core structure of ISO 42001 into deal-relevant language, focusing on requirements that directly impact integration planning and risk transfer.
12 chapters in this module
  1. Understanding ISO 42001 clause 5 in acquisition scenarios
  2. Clause 6 integration planning and deal-specific risk appetite
  3. Defining organizational AI governance roles in transitional states
  4. Documenting AI policies under time-constrained transitions
  5. Establishing AI risk criteria aligned with PE holding periods
  6. Setting up governance under dual-reporting interim structures
  7. Tracking AI compliance across legacy and new entities
  8. Using ISO 42001 to strengthen indemnity negotiation positions
  9. Aligning AI assurance activities with earn-out conditions
  10. Reporting AI governance posture to PE sponsor teams
  11. Adapting Clause 8 for accelerated integration timelines
  12. Clause 9 audit planning in transitional organizational states
Module 3. AI Governance in Pre-Deal Due Diligence
Integrate ISO 42001 readiness assessment into technical and compliance diligence workflows to shape deal pricing and risk allocation.
12 chapters in this module
  1. Scoping AI systems during preliminary target assessments
  2. Identifying AI model dependencies in financial reporting
  3. Evaluating training data compliance in regulated domains
  4. Assessing model risk in customer-facing AI applications
  5. Reviewing AI vendor contracts for governance gaps
  6. Benchmarking target AI posture against ISO 42001 baselines
  7. Estimating remediation effort for non-compliant AI systems
  8. Linking AI risk findings to purchase price adjustments
  9. Documenting AI liability exposure for legal teams
  10. Preparing summary AI governance health reports for PE
  11. Highlighting AI scalability risks in growth assumptions
  12. Flagging model retraining requirements post-acquisition
Module 4. Structuring AI Governance Provisions in SPAs
Embed ISO 42001-aligned clauses into Share Purchase Agreements to define responsibilities, timelines, and accountability for AI oversight.
12 chapters in this module
  1. Defining seller representations on AI compliance status
  2. Drafting warranties for AI model lineage and training data
  3. Setting AI governance milestones in post-closing covenants
  4. Specifying timelines for first ISO 42001 gap assessment
  5. Linking AI remediation to deferred consideration payouts
  6. Establishing audit rights for AI systems in transition
  7. Defining governance continuity during leadership gaps
  8. Addressing AI model drift in post-acquisition monitoring
  9. Embedding AI oversight into integration committee charters
  10. Setting up AI compliance reporting for interim management
  11. Transferring AI risk ownership at Day 1 transition points
  12. Clarity on indemnification for AI-related regulatory fines
Module 5. Building the Day One AI Governance Playbook
Create an executable plan for standing up AI governance in the first 72 hours post-close, aligned with integration office priorities and PE expectations.
12 chapters in this module
  1. Assembling the core AI governance task force on Day 1
  2. Rapid documentation of acquired AI inventory and risk tiers
  3. Setting up interim ISO 42001 compliance tracking
  4. First 48-hour AI model inventory and ownership mapping
  5. Establishing cross-functional AI risk escalation paths
  6. Prioritizing critical AI systems for immediate controls
  7. Setting up weekly AI governance alignment meetings
  8. Communicating AI oversight plans to interim leadership
  9. Integrating AI risk updates into integration dashboards
  10. Documenting deviations from ISO 42001 during transition
  11. Planning first formal review within 30-day window
  12. Creating AI risk logs accessible to integration teams
Module 6. Leading Cross-Functional AI Risk Integration
Drive alignment between legal, compliance, IT, and operations teams on AI governance priorities during integration planning.
12 chapters in this module
  1. Aligning legal and compliance on AI liability exposure
  2. Integrating AI controls into broader SOX and regulatory maps
  3. Working with IT on model deployment and monitoring access
  4. Coordinating AI retraining schedules with product teams
  5. Involving HR on AI-driven workforce planning changes
  6. Engaging finance on AI cost allocation and tracking
  7. Setting up AI audit trails across legacy systems
  8. Communicating AI risk posture to investor relations
  9. Involving procurement in AI vendor reevaluation
  10. Coordinating incident response plans across silos
  11. Building shared understanding of AI failure modes
  12. Establishing unified AI risk taxonomy across functions
Module 7. Accelerating ISO 42001 Implementation Post-Close
Deploy a streamlined ISO 42001 compliance framework tailored to integration timelines and PE value horizons.
12 chapters in this module
  1. Adapting ISO 42001 for transitional organizational forms
  2. Setting up temporary AI governance committees
  3. Documenting AI policies under time pressure
  4. Rapid onboarding of key personnel to governance roles
  5. Establishing interim audit review cadence
  6. Prioritizing controls based on materiality thresholds
  7. Using automation for AI risk assessment at scale
  8. Conducting first internal review within 60 days
  9. Tracking progress against PE-specific milestones
  10. Reporting compliance status to sponsor teams
  11. Integrating findings into integration risk logs
  12. Preparing for first external audit engagement
Module 8. AI Governance for Integration Playbook Alignment
Ensure AI oversight is embedded in core integration playbooks for finance, HR, IT, and operations.
12 chapters in this module
  1. Linking AI model revalidation to finance system cutover
  2. Aligning AI workforce planning with HR integration
  3. Coordinating IT system decommissioning with AI models
  4. Updating customer communications for AI transparency
  5. Involving operations in AI-driven process changes
  6. Aligning AI model updates with product roadmaps
  7. Embedding AI risk triggers into milestone tracking
  8. Updating business continuity plans for AI failure
  9. Involving legal on AI-related contract renewals
  10. Tracking AI compliance in integration scorecards
  11. Connecting AI oversight to core KPIs
  12. Ensuring AI accountability in interim leadership
Module 9. Stakeholder Communication and Executive Presence
Position yourself as the authoritative voice on AI governance across sponsor teams, management, and functional leads.
12 chapters in this module
  1. Crafting clear AI governance narratives for PE sponsors
  2. Presenting risk posture without overstating exposure
  3. Using ISO 42001 as a credibility anchor in discussions
  4. Communicating progress during integration turbulence
  5. Handling pushback on governance resourcing
  6. Building trusted advisor status with interim CEOs
  7. Translating technical AI risk for non-technical teams
  8. Delivering concise governance updates under time pressure
  9. Anticipating sponsor questions on AI liability
  10. Balancing transparency with deal sensitivity
  11. Using case examples from prior integrations
  12. Positioning governance as value protection, not cost
Module 10. Regulator-Ready AI Documentation
Produce governance records that satisfy current regulatory expectations and position the business for future scrutiny.
12 chapters in this module
  1. Building audit trails for AI model decisions
  2. Documenting training data sources and lineage
  3. Creating model change logs accessible to examiners
  4. Maintaining version history for AI systems
  5. Setting up data governance alignment for AI
  6. Recording AI risk assessment methodologies
  7. Documenting ethical review board inputs
  8. Tracking AI bias testing and mitigation
  9. Preserving model validation reports
  10. Establishing retention policies for AI artifacts
  11. Preparing for ESG-linked AI audits
  12. Aligning with DORA, MiFID II, and other sector rules
Module 11. Scaling Governance Across PE Portfolio Companies
Extend transaction-level AI governance practices into repeatable frameworks for portfolio-wide adoption.
12 chapters in this module
  1. Identifying common AI governance gaps across deals
  2. Building template playbooks for future transactions
  3. Establishing PE-level AI oversight standards
  4. Creating governance checklists for acquisition teams
  5. Standardizing ISO 42001 implementation timelines
  6. Developing cross-portfolio AI risk dashboards
  7. Training PE operating partners on governance basics
  8. Setting up peer review for AI controls
  9. Benchmarking AI maturity across companies
  10. Sharing remediation tactics across deals
  11. Building a central repository for AI governance assets
  12. Positioning yourself as the firm’s AI governance reference
Module 12. Sustaining Governance Beyond Integration
Ensure AI oversight continues to add value after the integration period ends, supporting long-term value creation.
12 chapters in this module
  1. Transitioning from interim to permanent AI governance
  2. Embedding ISO 42001 into ongoing compliance cycles
  3. Involving internal audit in AI control testing
  4. Planning for annual certification and surveillance
  5. Updating AI policies with business evolution
  6. Incorporating AI risk into strategic planning
  7. Supporting ESG reporting with AI governance data
  8. Using governance maturity as a market differentiator
  9. Building client case studies on AI due diligence
  10. Positioning advisory services around proven frameworks
  11. Extending influence into pre-deal scoping phases
  12. Becoming the go-to advisor for AI in complex transactions

How this maps to your situation

  • Private equity M&A advisory
  • Post-acquisition integration planning
  • Regulatory scrutiny in financial transactions
  • Cross-functional leadership in transitional states

Before vs. after

Before
AI governance is treated as a technical compliance task, often deferred until late in integration, diluting advisory influence.
After
You lead with a structured, ISO 42001-aligned approach that embeds AI accountability early, shaping deals and positioning yourself as the trusted reference.

What's included with your purchase

  • 12 modules with 12 chapters each (144 chapters)
  • Downloadable templates and worked examples for every module
  • Hand-built implementation playbook delivered alongside course access
  • 30-day money-back guarantee

Delivery and format

  • Course and learning environment access provisioned within 24 hours of purchase
  • Hand-built implementation playbook delivered alongside course access

Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.

Time investment: Approximately 90 minutes per week over six weeks, with flexible access to materials and templates.

If nothing changes
Without a structured framework, AI governance remains reactive, deals face higher scrutiny, integration stalls, and advisors lose influence to more prepared firms.

How this compares to the alternatives

Generic AI governance courses focus on policy or technology, this course is built for transaction leaders who need to embed governance into deal strategy, integration, and sponsor communication.

Frequently asked

Is this course relevant if I don’t work directly on AI systems?
Yes. This course is designed for advisors who shape deal outcomes, not build models. You’ll learn how to structure governance, allocate risk, and lead cross-functional teams, without needing technical AI expertise.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will I receive practical tools I can use immediately?
Yes. Every module includes downloadable templates, checklists, and real-world examples tailored to M&A in private equity contexts.
$199 one-time. Approximately 90 minutes per week over six weeks, with flexible access to materials and templates..

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

30-day money-back guarantee· 144 chapters· Hand-built playbook included· Account access within 24 hours
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