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DAT8759 Mastering ISO 42001 for Executive and Enterprise Partner Managers

$199.00
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A tailored course, built for your situation

Mastering ISO 42001 for Executive and Enterprise Partner Managers

Build AI governance authority with structured implementation aligned to strategic vendor and technical decisions

$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.
Many AI governance efforts stall due to misalignment between technical teams, procurement, and client expectations

The situation this course is for

Without a clear, standardized framework, AI governance initiatives often lack executive support, fail vendor review thresholds, or get dismissed as theoretical. Practitioners struggle to demonstrate tangible control implementation that satisfies both technical and business stakeholders.

Who this is for

Senior Partner Managers in global IT services firms who influence vendor selection, technical architecture decisions, and enterprise client engagements

Who this is not for

Junior consultants, individual contributors without vendor or client decision influence, or practitioners focused solely on internal IT operations

What you walk away with

  • Structure AI governance frameworks that pass client procurement reviews on first submission
  • Lead cross-functional alignment between engineering, compliance, and client teams using ISO 42001 controls
  • Position yourself as the internal reference for AI governance in high-value client discussions
  • Reduce rework by applying a repeatable implementation playbook tailored to enterprise partner workflows
  • Gain confidence in articulating governance decisions during technical deep dives and contract negotiations

The 12 modules (with all 144 chapters)

Module 1. Introduction to ISO 42001 and Its Role in Enterprise AI Governance
Establish foundational knowledge of ISO 42001, its structure, and its growing importance in enterprise client contracts and vendor evaluations.
12 chapters in this module
  1. Understanding the scope and purpose of ISO 42001
  2. How ISO 42001 differs from other AI governance standards
  3. Mapping ISO 42001 to enterprise client procurement requirements
  4. The role of partner managers in AI governance adoption
  5. Key terminology and framework hierarchy explained
  6. Why ISO 42001 is becoming a vendor selection differentiator
  7. Linking ISO 42001 to existing CGI service offerings
  8. Common misconceptions about AI governance frameworks
  9. How ISO 42001 supports ethical AI deployment
  10. Integrating ISO 42001 with client risk assessment workflows
  11. Benchmarking current AI governance maturity levels
  12. Setting realistic implementation goals for client engagements
Module 2. Scoping AI Systems Under ISO 42001 Requirements
Learn how to define and document AI system boundaries in alignment with ISO 42001 controls for client-facing proposals and internal assessments.
12 chapters in this module
  1. Identifying AI systems eligible for ISO 42001 certification
  2. Documenting system purpose and intended use cases
  3. Defining system boundaries for audit readiness
  4. Classifying AI systems by risk level and complexity
  5. Engaging technical teams to validate scope definitions
  6. Aligning scoping with client procurement timelines
  7. Avoiding common scoping oversights in vendor bids
  8. Using templates to standardize scoping documentation
  9. Linking system scope to data lifecycle management
  10. Handling edge cases in multi-vendor AI integrations
  11. Validating scope with compliance and legal stakeholders
  12. Updating scope documentation during project evolution
Module 3. Establishing AI Governance Roles and Responsibilities
Define clear accountability structures within client teams and internal CGI units using ISO 42001 governance role frameworks.
12 chapters in this module
  1. Mapping ISO 42001 roles to existing team structures
  2. Defining AI governance leadership within client organizations
  3. Assigning accountability for model development and deployment
  4. Clarifying oversight responsibilities across vendor boundaries
  5. Creating RACI matrices for AI governance workflows
  6. Integrating governance roles into service delivery contracts
  7. Training non-technical stakeholders on governance duties
  8. Managing role changes during project transitions
  9. Ensuring continuity across team rotations
  10. Auditing role adherence during compliance reviews
  11. Aligning role definitions with client organizational charts
  12. Documenting role assignments for external verification
Module 4. Risk Assessment and Management for AI Systems
Apply ISO 42001 risk assessment methodologies to identify, evaluate, and mitigate AI-related risks in enterprise environments.
12 chapters in this module
  1. Developing a risk assessment methodology aligned to ISO 42001
  2. Identifying inherent risks in AI system design and deployment
  3. Classifying risks by likelihood and impact severity
  4. Engaging stakeholders in risk identification workshops
  5. Documenting risk treatment plans with clear ownership
  6. Linking risk controls to technical implementation steps
  7. Validating risk mitigation effectiveness over time
  8. Updating risk assessments for model updates and retraining
  9. Integrating risk registers into client reporting workflows
  10. Using risk heat maps for executive communication
  11. Benchmarking risk posture against industry peers
  12. Preparing risk documentation for external audits
Module 5. Data Management and Quality Assurance for AI Models
Ensure data integrity and quality throughout the AI lifecycle using ISO 42001 data management controls.
12 chapters in this module
  1. Defining data quality metrics for AI training and validation
  2. Establishing data lineage and provenance tracking
  3. Implementing data versioning and change control
  4. Ensuring data representativeness and bias mitigation
  5. Managing data access and confidentiality requirements
  6. Auditing data handling practices across vendor teams
  7. Documenting data governance policies for client review
  8. Integrating data quality checks into CI/CD pipelines
  9. Handling data drift and concept drift detection
  10. Using data quality reports in stakeholder communications
  11. Aligning data practices with regulatory expectations
  12. Maintaining data documentation for certification audits
Module 6. Model Development and Deployment Controls
Implement ISO 42001-compliant processes for model development, testing, and deployment in enterprise settings.
12 chapters in this module
  1. Establishing model development lifecycle standards
  2. Defining model validation and testing protocols
  3. Implementing version control for AI models
  4. Ensuring reproducibility of model training processes
  5. Managing model dependencies and environment configuration
  6. Conducting pre-deployment risk assessments
  7. Implementing model deployment checklists
  8. Monitoring model performance post-deployment
  9. Handling model rollback and incident response
  10. Documenting model changes for audit purposes
  11. Integrating deployment controls with DevOps workflows
  12. Training operations teams on model management procedures
Module 7. Human-AI Interaction and User Communication
Design transparent user interactions and communication strategies that meet ISO 42001 human oversight requirements.
12 chapters in this module
  1. Defining appropriate levels of human oversight
  2. Designing user interfaces for AI transparency
  3. Communicating model limitations to end users
  4. Establishing user feedback mechanisms
  5. Documenting human-in-the-loop decision points
  6. Training client teams on AI interaction protocols
  7. Ensuring accessibility of AI system information
  8. Managing user expectations during AI adoption
  9. Handling user complaints and escalation paths
  10. Auditing human-AI interaction effectiveness
  11. Updating communication materials for new features
  12. Aligning user communication with client branding
Module 8. Performance Monitoring and Continuous Improvement
Set up ongoing monitoring systems to track AI model performance and drive continuous improvement under ISO 42001.
12 chapters in this module
  1. Defining key performance indicators for AI systems
  2. Establishing baseline performance metrics
  3. Implementing automated monitoring dashboards
  4. Detecting model degradation over time
  5. Scheduling regular model retraining cycles
  6. Collecting and analyzing operational feedback
  7. Conducting periodic model reviews
  8. Updating models based on performance insights
  9. Documenting improvement initiatives
  10. Aligning monitoring practices with client SLAs
  11. Reporting performance trends to executive stakeholders
  12. Integrating monitoring data into governance reports
Module 9. Security and Cyber Resilience for AI Systems
Apply ISO 42001 security controls to protect AI systems from cyber threats and ensure operational resilience.
12 chapters in this module
  1. Identifying security threats specific to AI systems
  2. Implementing access controls for model and data assets
  3. Protecting against model inversion and extraction attacks
  4. Securing model deployment environments
  5. Establishing incident response plans for AI systems
  6. Conducting security testing and vulnerability assessments
  7. Managing third-party security risks in AI supply chains
  8. Ensuring secure model updates and patches
  9. Auditing security controls for compliance verification
  10. Integrating AI security into broader organizational frameworks
  11. Training teams on AI-specific security practices
  12. Documenting security posture for client assurance
Module 10. Compliance Verification and Audit Preparation
Prepare for internal and external audits using ISO 42001 compliance verification processes.
12 chapters in this module
  1. Understanding ISO 42001 audit requirements
  2. Preparing documentation for compliance review
  3. Conducting internal readiness assessments
  4. Engaging external auditors effectively
  5. Responding to auditor findings and recommendations
  6. Maintaining audit trails for AI system changes
  7. Demonstrating control effectiveness through evidence
  8. Addressing non-conformities promptly
  9. Using audit feedback for continuous improvement
  10. Aligning audit preparation with client timelines
  11. Training teams on audit response protocols
  12. Maintaining compliance documentation repositories
Module 11. Stakeholder Engagement and Governance Reporting
Develop effective communication strategies to engage stakeholders and report on AI governance performance.
12 chapters in this module
  1. Identifying key governance stakeholders
  2. Developing stakeholder communication plans
  3. Creating executive-level governance dashboards
  4. Reporting on control effectiveness and risk posture
  5. Conducting governance review meetings
  6. Addressing stakeholder concerns and questions
  7. Updating governance documentation for transparency
  8. Sharing best practices across client engagements
  9. Benchmarking governance performance over time
  10. Integrating governance reporting into client reviews
  11. Training client teams on governance communication
  12. Maintaining stakeholder engagement records
Module 12. Scaling AI Governance Across Client Portfolios
Extend ISO 42001 implementation across multiple client engagements using standardized playbooks and templates.
12 chapters in this module
  1. Developing reusable AI governance templates
  2. Standardizing implementation approaches
  3. Training teams on governance frameworks
  4. Creating centralized governance support functions
  5. Sharing lessons learned across engagements
  6. Adapting frameworks to different client industries
  7. Managing governance consistency across regions
  8. Integrating governance into sales and delivery workflows
  9. Measuring governance maturity across accounts
  10. Demonstrating ROI of governance investments
  11. Building internal governance communities of practice
  12. Positioning CGI as a leader in responsible AI adoption

How this maps to your situation

  • Partner Managers influencing AI governance in client contracts
  • Enterprise clients demanding certified AI governance frameworks
  • CGI positioning itself as a leader in responsible AI adoption
  • Growing need for standardized AI governance across global accounts

Before vs. after

Before
AI governance efforts are inconsistent, reactive, and lack standardization across client engagements
After
Structured, repeatable AI governance implementation that strengthens client trust and positions you as a key decision influencer

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 12 weeks, with flexible pacing options.

If nothing changes
Without a standardized approach, AI governance initiatives may fail client reviews, create compliance gaps, or miss strategic opportunities to differentiate CGI's offerings in competitive bids.

How this compares to the alternatives

Unlike generic AI ethics courses or high-level strategy decks, this program delivers actionable, ISO 42001-specific implementation guidance tailored to partner managers shaping technical and vendor decisions in enterprise environments.

Frequently asked

Who is this course designed for?
This course is for senior Partner Managers in global IT services firms who influence technical direction, vendor selection, and enterprise client engagements involving AI systems.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does the course include practical tools?
Yes, every module includes downloadable templates, worked examples, and a hand-built implementation playbook tailored to enterprise partner workflows.
$199 one-time. Approximately 90 minutes per week over 12 weeks, with flexible pacing options..

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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