A tailored course, built for your situation
Influence Across More Business Lines with ISO 42001
Design AI governance practices that scale across teams and domains with confidence and clarity
Who this is for
Senior practitioner in talent, people operations, or governance looking to expand influence into AI and compliance domains
Who this is not for
Individuals seeking technical implementation of ISO 42001 in engineering or data systems, or those without cross-functional coordination responsibilities
What you walk away with
- Lead alignment sessions on AI governance across non-technical teams
- Create reusable frameworks that hiring, L&D, and compliance teams can adopt
- Represent governance needs effectively in cross-departmental AI initiatives
- Shape internal narratives around responsible AI adoption
- Bridge governance standards and people systems using ISO 42001 as common language
The 12 modules (with all 144 chapters)
- Identifying AI use in recruitment tools
- Aligning job descriptions with AI ethics standards
- Onboarding teams on AI governance expectations
- Training developers on responsible AI use
- Integrating AI disclosures into employee handbooks
- Assessing vendor AI tools for compliance
- Building internal AI awareness campaigns
- Documenting AI use across departments
- Establishing feedback loops with HR teams
- Creating audit-ready people processes
- Linking performance reviews to AI ethics
- Scaling governance from pilot to org-wide
- Translating ISO 42001 for non-technical teams
- Creating glossaries for cross-functional use
- Running alignment workshops across departments
- Avoiding misinterpretation in policy rollouts
- Using common examples to explain risks
- Documenting decisions for consistency
- Standardizing incident reporting paths
- Building trust through clarity
- Simplifying compliance for broad adoption
- Mapping roles to governance tasks
- Clarifying ownership without hierarchy
- Reinforcing accountability across teams
- Drafting AI governance playbooks
- Building approval workflows for AI tools
- Creating standard operating procedures
- Versioning governance documents
- Designing intake forms for AI projects
- Developing stakeholder review cycles
- Generating compliance-ready summaries
- Using templates across departments
- Ensuring accessibility of artifacts
- Linking policies to training materials
- Automating document distribution
- Maintaining audit trails for updates
- Identifying key influencers in each team
- Framing AI governance as enabler, not barrier
- Running low-friction pilot programs
- Gathering early adopters from different units
- Sharing success stories across departments
- Aligning governance with team goals
- Using data to demonstrate value
- Reducing friction in compliance steps
- Building coalitions around standards
- Creating peer recognition loops
- Fostering ownership beyond central teams
- Sustaining momentum after launch
- Identifying AI decision makers
- Classifying influence and interest levels
- Tailoring messaging by role
- Scheduling touchpoints by team
- Preparing for leadership Q&A
- Anticipating legal and HR concerns
- Addressing engineering constraints
- Engaging compliance officers early
- Involving procurement in vendor reviews
- Coordinating with internal comms
- Tracking stakeholder sentiment
- Adjusting strategy based on feedback
- Designing post-implementation reviews
- Creating anonymous reporting channels
- Running pulse surveys on AI use
- Logging incidents and near-misses
- Triaging reports by severity
- Linking feedback to policy updates
- Sharing learnings across units
- Recognizing contributors publicly
- Reducing response time to issues
- Building trust in escalation paths
- Closing loops with reporting teams
- Measuring improvement over time
- Assessing team readiness for AI rules
- Building urgency without creating fear
- Creating vision for responsible AI
- Leading team-by-team rollouts
- Using champions to drive change
- Communicating milestones effectively
- Celebrating early wins
- Addressing resistance with empathy
- Aligning change to business goals
- Maintaining momentum over time
- Updating playbooks based on feedback
- Scaling change across regions
- Evaluating vendor AI ethics claims
- Reviewing third-party certifications
- Assessing data handling practices
- Defining contractual obligations
- Auditing AI model transparency
- Managing vendor onboarding workflows
- Creating vendor governance checklists
- Tracking compliance over time
- Handling non-compliance incidents
- Integrating vendors into audit cycles
- Reducing third-party risk exposure
- Building exit strategies for non-compliant tools
- Assessing knowledge gaps by team
- Designing role-based learning paths
- Creating interactive training modules
- Running live governance workshops
- Developing quick-reference guides
- Gamifying compliance learning
- Testing knowledge retention
- Certifying team preparedness
- Updating content quarterly
- Scaling training across regions
- Integrating with LMS platforms
- Tracking completion and impact
- Defining governance KPIs
- Tracking policy adoption rates
- Measuring incident reduction
- Auditing compliance across units
- Benchmarking against peers
- Identifying improvement areas
- Prioritizing updates based on risk
- Publishing governance dashboards
- Aligning metrics with leadership goals
- Reducing audit preparation time
- Driving accountability through data
- Updating ISO 42001 practices annually
- Defining AI incident types
- Creating response playbooks
- Assembling cross-functional teams
- Running tabletop exercises
- Communicating during incidents
- Documenting root causes
- Reporting to leadership
- Implementing corrective actions
- Sharing learnings organization-wide
- Updating policies post-incident
- Reducing recurrence likelihood
- Strengthening monitoring after events
- Integrating governance into performance goals
- Linking AI compliance to promotions
- Incorporating ethics into hiring
- Building governance into project lifecycle
- Reviewing AI use in strategy sessions
- Reporting on progress to leadership
- Recognizing governance champions
- Rotating accountability across teams
- Updating standards with new tech
- Maintaining momentum during turnover
- Scaling practices globally
- Owning the evolution of AI norms
How this maps to your situation
- Rolling out AI governance in multi-team environments
- Leading change without formal authority
- Aligning HR, legal, and engineering on AI rules
- Scaling compliance across departments
Before vs. after
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 45 minutes per module, designed to fit within existing workflow. Total time: 9-12 hours over 4-6 weeks.
How this compares to the alternatives
Unlike generic compliance courses, this program is tailored to practitioners expanding influence across people and technical functions. It combines ISO 42001 mastery with change leadership, avoiding consultant jargon in favor of actionable frameworks and real-world examples.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.