A tailored course, built for your situation
Mastering ISO 20000 for AI Automation & Architecture Leaders
Turn AI governance into premium engagements with structured service delivery
$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 projects stall without clear service ownership and compliance framing
The situation this course is for
Even advanced AI teams struggle to scale because their work lacks service management discipline. Without ISO 20000 alignment, AI initiatives appear experimental rather than operational, making it harder to secure funding, justify headcount, or lead beyond engineering.
Who this is for
Senior AI/ML leaders in global tech firms who own AI architecture and governance but lack formal service delivery frameworks
Who this is not for
Individual contributors focused only on model development, or practitioners without influence over AI service design or deployment decisions
What you walk away with
- Design AI services that meet ISO 20000 service delivery and support requirements
- Position AI projects as repeatable, auditable, and compliant offerings
- Lead cross-functional AI service rollouts with documented service level agreements
- Differentiate your AI architecture practice with certified service management maturity
- Unlock bigger budgets by aligning AI work with enterprise service governance
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO 20000 in AI Service Contexts
Understand how ISO 20000 applies to AI automation and why service management maturity increases engagement value.
12 chapters in this module
- Defining service management in AI-driven organizations
- Mapping AI automation workflows to service lifecycle stages
- Why ISO 20000 matters for AI architecture leaders
- Differentiating AI projects from AI services
- Case study: AI service rollout at a global telecom
- Key stakeholders in AI service delivery and support
- Common gaps in AI service ownership models
- Integrating AI governance with service management
- Benchmarking AI service maturity across industries
- The financial case for ISO 20000 in AI initiatives
- How service standards attract executive sponsorship
- First steps in aligning AI architecture with ISO 20000
Module 2. Service Strategy for AI Offerings
Learn to position AI capabilities as strategic services with defined value propositions and funding models.
12 chapters in this module
- Identifying internal customers for AI services
- Defining service portfolios for AI automation
- Creating value propositions for AI service lines
- Aligning AI services with business objectives
- Pricing models for internal AI service units
- Budgeting for AI service development and support
- Stakeholder engagement in service planning
- Risk assessment in AI service strategy
- Service portfolio management tools and templates
- From prototype to production: service funding paths
- Case example: AI service strategy at a Tier 1 vendor
- Documenting AI service strategy for leadership review
Module 3. Service Design and AI Integration
Design robust AI services with documented SLAs, availability plans, and compliance alignment.
12 chapters in this module
- Translating AI models into service specifications
- Designing service level agreements for AI automation
- Availability management for AI-powered services
- Capacity planning for scalable AI workloads
- IT service continuity in AI service design
- Design coordination across data, AI, and infrastructure
- Security considerations in AI service blueprints
- Supplier management for third-party AI components
- Documenting AI service designs for audit readiness
- Using ISO 20000-1 to structure AI service documentation
- Version control for AI service specifications
- Validating AI service designs with stakeholders
Module 4. Service Transition for AI Deployments
Manage the move from AI development to operational service with controlled release and change processes.
12 chapters in this module
- Change management for AI model updates
- Release and deployment planning for AI services
- Configuration management for AI environments
- Asset lifecycle tracking in AI service transitions
- Transition planning for multi-region AI rollouts
- Testing strategies for AI service validation
- Knowledge transfer from development to operations
- Service acceptance criteria for AI deployments
- Managing AI service rollback procedures
- Documentation requirements for AI transitions
- Case example: AI service rollout in regulated sector
- Avoiding common pitfalls in AI service launches
Module 5. Service Operation in AI Contexts
Operate AI services with defined incident, problem, and event management processes.
12 chapters in this module
- Incident management for AI service disruptions
- Problem identification in AI model performance drift
- Event monitoring for AI-powered systems
- Request fulfillment for AI service access
- Defining roles in AI service operations
- Managing AI service desk interactions
- Escalation procedures for AI incidents
- Daily health checks for AI services
- Logging and auditing AI service operations
- Using automation to streamline AI operations
- Balancing AI autonomy with human oversight
- Service operation reporting for leadership
Module 6. Continual Service Improvement for AI
Apply CSI principles to enhance AI services based on feedback, metrics, and business evolution.
12 chapters in this module
- The CSI register for AI service enhancements
- Measuring AI service performance over time
- Collecting feedback from AI service users
- Identifying improvement opportunities in AI workflows
- Prioritizing AI service improvements
- Implementing AI service changes incrementally
- Reviewing AI service KPIs and SLAs
- Benchmarking AI services against industry peers
- Using ISO 20000 CSI guidance for AI
- Documenting AI service improvement cycles
- Integrating user experience into AI service design
- Sustaining AI service relevance over time
Module 7. ISO 20000 Compliance for AI Services
Ensure AI services meet ISO 20000 requirements for certification and audit readiness.
12 chapters in this module
- Understanding ISO 20000-1:the current cycle clauses
- Mapping AI service processes to ISO 20000 controls
- Evidence collection for AI service audits
- Preparing for internal ISO 20000 assessments
- External audit preparation for AI services
- Common findings in AI-related ISO 20000 audits
- Corrective action planning for compliance gaps
- Maintaining ISO 20000 certification for AI units
- Integrating ISO 20000 with other frameworks
- Leveraging ISO 20000 for cross-functional credibility
- Training teams on ISO 20000 compliance
- Building a compliance culture in AI teams
Module 8. AI Service Governance and Leadership
Lead AI service initiatives with clear ownership, accountability, and strategic alignment.
12 chapters in this module
- Defining service ownership in AI projects
- Establishing AI service governance boards
- Aligning AI services with enterprise architecture
- Role of the AI Automation & Architecture Lead
- Decision rights in AI service management
- Reporting AI service performance to leadership
- Managing AI service budgets and resources
- Vendor governance for AI service components
- Ethical considerations in AI service delivery
- Sustainability metrics for AI services
- Succession planning for AI service roles
- Leading AI service transformation programs
Module 9. Integrating AI Services with ITIL Practices
Align AI service delivery with established ITIL service management processes.
12 chapters in this module
- Overview of ITIL service lifecycle
- Integrating AI with service strategy processes
- AI in service design and transition
- Operating AI services within ITIL frameworks
- Improving AI services using CSI
- Managing AI-related changes in ITIL
- Incident and problem management for AI
- Event management and AI monitoring
- Configuration management for AI systems
- Release management for AI updates
- Service level management for AI offerings
- Practical integration patterns for AI and ITIL
Module 10. AI Service Documentation and Artefacts
Create clear, compliant, and reusable documentation for AI services.
12 chapters in this module
- Documenting AI service strategy
- Service design packages for AI offerings
- SLA templates for AI automation
- Availability plans for AI services
- Capacity plans for AI workloads
- IT service continuity plans for AI
- Security policies for AI services
- Supplier agreements for AI components
- Change and release documentation
- Incident and problem records for AI
- CSI documentation for AI services
- Maintaining AI service knowledge base
Module 11. Stakeholder Engagement in AI Services
Engage business, IT, and compliance stakeholders in AI service design and delivery.
12 chapters in this module
- Identifying AI service stakeholders
- Communicating AI service value to leadership
- Engaging compliance teams in AI governance
- Collaborating with data privacy officers
- Working with security teams on AI controls
- Involving operations in AI service planning
- Managing expectations for AI capabilities
- Handling resistance to AI service adoption
- Building cross-functional AI service teams
- Facilitating AI service workshops
- Reporting AI service progress to stakeholders
- Sustaining stakeholder engagement over time
Module 12. Monetizing and Scaling AI Services
Scale AI services across the organization and unlock higher-margin engagements.
12 chapters in this module
- Identifying scalable AI service opportunities
- Packaging AI services for reuse
- Pricing models for internal AI services
- Funding strategies for AI service expansion
- Building internal AI service catalogs
- Marketing AI services to business units
- Measuring ROI of AI service offerings
- Scaling AI services across regions
- Managing demand for AI services
- Partnering with business units on AI
- Creating premium AI service tiers
- Positioning AI services for external offerings
How this maps to your situation
- Aligning AI automation with service management standards
- Designing AI services for compliance and scalability
- Operating AI services with defined SLAs and support
- Improving and monetizing AI service offerings
Before vs. after
Before
AI initiatives are seen as experimental projects without clear service ownership or compliance alignment
After
AI services are structured, auditable, and positioned for premium engagements and leadership visibility
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters total)
- 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 3 hours per module, designed for senior practitioners balancing delivery and learning.
If nothing changes
Without ISO 20000 alignment, AI services remain ad hoc, harder to fund, and less likely to scale beyond pilot stages.
How this compares to the alternatives
Unlike generic AI governance courses, this program focuses specifically on ISO 20000 integration, providing actionable frameworks for service delivery, compliance, and financial leverage in enterprise AI contexts.
Frequently asked
Who is this course for?
AI Automation & Architecture Leads, senior AI/ML architects, and technical leaders responsible for scaling AI services with governance and compliance.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this course cover other frameworks like ISO 27001 or SOC 2?
The focus is ISO 20000 for service management, but integration with complementary frameworks is addressed in relevant modules.
$199 one-time. Approximately 3 hours per module, designed for senior practitioners balancing delivery and learning..
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