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CMP0418 Mastering ISO/IEC TR 24028 for Implementation, Compliance and Audit Readiness

$199.00
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What is the ISO/IEC TR 24028 for Implementation course about?

Turn emerging AI trust requirements into repeatable, evidence-ready deployments across business units and technical teams Each order is checked and updated against the latest insights before delivery. That is why access takes up to 24 hours rather than being instant.

What situation is the ISO/IEC TR 24028 for Implementation for?

Teams spend 80+ hours stitching together compliance proof from disconnected development cycles, often missing alignment on what constitutes valid evidence for AI trustworthiness. This creates delays, rework, and exposure during internal or regulator-led reviews.

What do you take away from the ISO/IEC TR 24028 for Implementation course?

Produce audit-ready AI implementation evidence in under 6 hours Standardize compliance artefacts across product, risk, and engineering teams Reduce cross-functional rework during pre-audit cycles Demonstrate consistent application of ISO/IEC TR 24028 across regions and business lines Build reusable templates that survive regulator scrutiny.

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.

What does the ISO/IEC TR 24028 for Implementation cover on delivery and format?

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 6, 8 hours of focused learning, designed to be completed in short sessions over one to two weeks.

How does this compare to the alternatives?

Unlike generic AI ethics courses or high-level policy overviews, this course delivers implementation-grade detail focused on producing verifiable, audit-ready outcomes aligned with ISO/IEC TR 24028.

What does the ISO/IEC TR 24028 for Implementation cover on frequently asked?

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

How is the ISO/IEC TR 24028 for Implementation delivered?

The ISO/IEC TR 24028 for Implementation is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. A certificate of completion is issued by The Art of Service when you finish.

Closely related courses: ISO/IEC 17050-2, ISO IEC 38500 Implementation Checklist and Audit, ISO IEC 17020 Implementation and Audit Preparation, ISO IEC 17025 Implementation and Audit Preparation Mastery.

More answers: what you get with every course, refund policy, all help answers.

A tailored course, built for your situation

Mastering ISO/IEC TR 24028 for Implementation, Compliance and Audit Readiness

Turn emerging AI trust requirements into repeatable, evidence-ready deployments across business units and technical teams

$199 one-time
30-day money-back guarantee Verified against latest insights, updated access provided within 24h

Each order is checked and updated against the latest insights before delivery. That is why access takes up to 24 hours rather than being instant.

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.
Pre-audit scrambles with inconsistent AI implementation evidence across teams

The situation this course is for

Teams spend 80+ hours stitching together compliance proof from disconnected development cycles, often missing alignment on what constitutes valid evidence for AI trustworthiness. This creates delays, rework, and exposure during internal or regulator-led reviews.

Who this is for

Standards-focused practitioner in compliance, risk, or engineering roles implementing AI governance frameworks across multiple technical or business units

Who this is not for

Those seeking high-level overviews of AI ethics or policy without implementation detail

What you walk away with

  • Produce audit-ready AI implementation evidence in under 6 hours
  • Standardize compliance artefacts across product, risk, and engineering teams
  • Reduce cross-functional rework during pre-audit cycles
  • Demonstrate consistent application of ISO/IEC TR 24028 across regions and business lines
  • Build reusable templates that survive regulator scrutiny

The 12 modules (with all 144 chapters)

Module 1. Understanding ISO/IEC TR 24028 in the Context of AI System Lifecycles
Ground the standard in real-world AI deployment phases from concept to decommissioning.
12 chapters in this module
  1. Mapping TR 24028 guidance to stages of AI system development
  2. Differentiating TR 24028 from other ISO/IEC AI standards
  3. Key definitions and scope boundaries in practical terms
  4. How TR 24028 supports broader AI governance program design
  5. Integrating trustworthiness considerations at project initiation
  6. Identifying stakeholders impacted by TR 24028 implementation
  7. Common misinterpretations of the technical report’s intent
  8. Using TR 24028 to inform risk assessment scoping
  9. Linking AI fairness objectives to implementation controls
  10. Documenting assumptions in early-stage AI projects
  11. Establishing traceability from design to deployment
  12. Creating a living compliance register based on TR 24028
Module 2. Translating TR 24028 Principles into Operational Controls
Convert high-level trustworthiness principles into actionable team workflows.
12 chapters in this module
  1. Turning robustness requirements into testable engineering criteria
  2. Operationalizing explainability expectations for model teams
  3. Designing reproducibility checks across training environments
  4. Implementing data quality validation at ingestion points
  5. Setting thresholds for acceptable AI performance drift
  6. Creating audit trails for model versioning and updates
  7. Embedding human oversight mechanisms in deployment pipelines
  8. Defining fallback procedures for AI system failure
  9. Mapping security controls to AI-specific threat vectors
  10. Ensuring privacy-preserving techniques are implemented correctly
  11. Validating transparency documentation against stakeholder needs
  12. Building control ownership models across technical teams
Module 3. Designing Evidence Collection for Multi-Team Environments
Structure evidence gathering so it scales across product, data, and infrastructure units.
12 chapters in this module
  1. Identifying required evidence types per TR 24028 clause
  2. Assigning evidence ownership across dev, ops, and risk roles
  3. Creating standardized templates for control implementation proof
  4. Synchronizing evidence collection with sprint cycles
  5. Using version control systems to store compliance artefacts
  6. Automating evidence capture from CI/CD pipelines
  7. Validating completeness of evidence packages before audit
  8. Maintaining evidence confidentiality and access controls
  9. Linking evidence to specific risk treatment decisions
  10. Archiving evidence for long-term retention requirements
  11. Cross-referencing evidence across multiple standards
  12. Preparing evidence for internal and external reviewer access
Module 4. Implementing Consistent AI Risk Assessments Across Business Units
Apply TR 24028 risk guidance uniformly regardless of regional or functional differences.
12 chapters in this module
  1. Adapting risk assessment methods for different AI use cases
  2. Standardizing risk scoring criteria across departments
  3. Incorporating stakeholder values into risk evaluation
  4. Documenting risk acceptance decisions with justification
  5. Aligning AI risk thresholds with enterprise risk appetite
  6. Conducting risk assessments in agile development settings
  7. Integrating third-party model risks into assessments
  8. Updating risk profiles as systems evolve in production
  9. Using risk registers to prioritize mitigation efforts
  10. Reporting risk status to technical and non-technical audiences
  11. Ensuring risk documentation meets auditor expectations
  12. Reviewing and refreshing risk assessments on a defined cycle
Module 5. Building Compliance into AI Development Workflows
Embed TR 24028 requirements directly into engineering processes.
12 chapters in this module
  1. Introducing compliance checkpoints in project onboarding
  2. Creating mandatory documentation templates for AI projects
  3. Setting up automated linting for code and configuration files
  4. Requiring evidence submission as part of pull requests
  5. Conducting peer reviews focused on trustworthiness criteria
  6. Using checklists to verify implementation completeness
  7. Tracking compliance tasks in project management tools
  8. Enforcing approval gates before model promotion
  9. Integrating security scanning into build pipelines
  10. Validating data lineage and provenance automatically
  11. Monitoring adherence to ethical design principles
  12. Capturing lessons learned for future project improvements
Module 6. Creating Reusable Implementation Artefacts for Scalability
Develop templates and playbooks that maintain consistency across teams.
12 chapters in this module
  1. Designing modular compliance documentation packages
  2. Creating fill-in-the-blank templates for common AI patterns
  3. Developing reference architectures aligned with TR 24028
  4. Publishing approved patterns for model monitoring setups
  5. Standardizing data preprocessing documentation formats
  6. Building reusable risk assessment workbooks
  7. Maintaining a central repository for implementation guides
  8. Versioning artefacts to track changes over time
  9. Providing examples of completed compliance packages
  10. Training teams on how to adapt templates locally
  11. Gathering feedback to improve reusable assets
  12. Ensuring artefacts remain accessible and discoverable
Module 7. Validating AI System Trustworthiness Through Testing
Establish testing protocols that verify compliance with TR 24028.
12 chapters in this module
  1. Designing test cases for robustness under edge conditions
  2. Measuring model performance across diverse demographic groups
  3. Testing explainability outputs for clarity and usefulness
  4. Validating reproducibility of training runs
  5. Assessing system behavior under adversarial attacks
  6. Checking for unintended bias in model predictions
  7. Evaluating human-AI interaction design effectiveness
  8. Testing fallback mechanisms during system degradation
  9. Measuring response time and availability under load
  10. Verifying data integrity throughout the pipeline
  11. Auditing logging and monitoring coverage
  12. Documenting test results for audit purposes
Module 8. Preparing for Internal and External Audits
Structure readiness efforts to pass scrutiny with minimal disruption.
12 chapters in this module
  1. Understanding auditor expectations for AI systems
  2. Mapping TR 24028 clauses to common audit questions
  3. Compiling evidence packages in auditor-friendly formats
  4. Conducting mock audits to identify gaps early
  5. Training team members on how to respond to inquiries
  6. Scheduling audit prep activities in project timelines
  7. Identifying key contacts for different audit domains
  8. Handling requests for additional information efficiently
  9. Addressing findings and tracking remediation progress
  10. Maintaining independence and objectivity in self-assessments
  11. Using audit feedback to improve implementation quality
  12. Reporting audit outcomes to leadership stakeholders
Module 9. Scaling AI Governance Across Regions and Jurisdictions
Maintain consistency while adapting to local regulatory environments.
12 chapters in this module
  1. Identifying regional variations in AI expectations
  2. Harmonizing global standards with local legal requirements
  3. Managing translations of compliance documentation
  4. Applying TR 24028 consistently across cultural contexts
  5. Coordinating implementation across time zones
  6. Ensuring data sovereignty requirements are met
  7. Adapting risk assessments for local stakeholder concerns
  8. Centralizing oversight while enabling local execution
  9. Sharing best practices across regional teams
  10. Monitoring compliance across distributed operations
  11. Handling cross-border data flows in AI systems
  12. Building governance structures that support global scale
Module 10. Integrating TR 24028 with Existing Management Systems
Connect AI implementation efforts to established quality, security, and compliance frameworks.
12 chapters in this module
  1. Aligning TR 24028 with ISO/IEC 27001 controls
  2. Linking AI risk management to ISO 31000 processes
  3. Integrating with existing quality management systems (ISO 9001)
  4. Connecting to enterprise risk management frameworks
  5. Mapping controls to NIST AI RMF components
  6. Using SOC 2 criteria to strengthen AI assurance
  7. Incorporating findings into internal audit programs
  8. Reporting AI compliance status through existing dashboards
  9. Leveraging existing policy infrastructure for AI rules
  10. Training compliance officers on AI-specific considerations
  11. Ensuring consistency with corporate ethics guidelines
  12. Demonstrating alignment to board-level risk committees
Module 11. Training and Upskilling Teams on TR 24028 Implementation
Equip practitioners with the knowledge to apply the standard correctly.
12 chapters in this module
  1. Assessing team readiness for TR 24028 adoption
  2. Developing role-specific training materials
  3. Creating hands-on workshops for implementation practice
  4. Using case studies to illustrate key concepts
  5. Delivering just-in-time learning at project start
  6. Measuring knowledge retention through assessments
  7. Providing access to reference materials and FAQs
  8. Establishing communities of practice for support
  9. Capturing common questions and answers over time
  10. Updating training content as practices evolve
  11. Onboarding new team members efficiently
  12. Recognizing and rewarding implementation excellence
Module 12. Sustaining Continuous Improvement in AI Implementation
Create feedback loops that drive ongoing enhancement of compliance quality.
12 chapters in this module
  1. Collecting lessons learned from completed projects
  2. Analyzing audit findings to identify systemic issues
  3. Tracking key metrics for implementation effectiveness
  4. Benchmarking against industry peers and best practices
  5. Incorporating new research into implementation approaches
  6. Updating controls in response to emerging threats
  7. Revising templates and playbooks based on experience
  8. Sharing improvements across the organization
  9. Conducting periodic reviews of implementation maturity
  10. Engaging with standards development groups
  11. Planning for future revisions of TR 24028
  12. Celebrating successes and reinforcing positive behaviors

How this maps to your situation

  • Pre-audit evidence preparation
  • Cross-functional AI implementation
  • Regulatory scrutiny readiness
  • Scalable governance rollout

Before vs. after

Before
Spending weeks compiling inconsistent evidence from siloed teams before audits
After
Generating aligned, audit-ready packages in hours using standardized templates

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 6, 8 hours of focused learning, designed to be completed in short sessions over one to two weeks.

If nothing changes
Without structured implementation guidance, teams will continue to produce fragmented compliance evidence, leading to extended audit cycles, repeated findings, and increased exposure to regulatory scrutiny.

How this compares to the alternatives

Unlike generic AI ethics courses or high-level policy overviews, this course delivers implementation-grade detail focused on producing verifiable, audit-ready outcomes aligned with ISO/IEC TR 24028.

Frequently asked

Is this course technical or managerial in focus?
It is implementation-focused, designed for practitioners who need to apply the standard in real projects, whether in engineering, compliance, or risk roles.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will I receive practical tools with the course?
Yes , every module includes downloadable templates and worked examples, and you’ll receive a hand-built implementation playbook upon enrollment.
$199 one-time. Approximately 6, 8 hours of focused learning, designed to be completed in short sessions over one to two weeks..

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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