A tailored course, built for your situation
Mastering AI-Driven Marketing Governance for Global Technology Leaders
Build auditable, defensible marketing systems that stand up to scrutiny, with clear reasoning, sources, and real-world precedent
Who this is for
Senior marketing executives at global technology firms driving AI-integrated campaigns under heightened scrutiny. They own go-to-market strategy, cross-border execution, and compliance alignment, often without formal governance training.
Who this is not for
Entry-level marketers, agency freelancers, or teams operating in unregulated verticals without compliance review cycles.
What you walk away with
- Articulate the reasoning behind AI-driven marketing decisions with reference to established frameworks (e.g., OECD AI Principles, ISO/IEC 23894)
- Preempt campaign rework by aligning creative teams and legal stakeholders early using standardized evidence templates
- Defend strategy in cross-functional reviews with cited precedents from peer firms and published case studies
- Reduce governance friction cycles by 60, 80% using structured justification workflows
- Turn marketing governance from a checkpoint into a competitive narrative
The 12 modules (with all 144 chapters)
- From intuition to audit trail: the new expectation in marketing
- How public scrutiny reshaped campaign approval workflows
- The role of marketing in enterprise risk posture
- Why 'move fast' no longer excuses 'break things' in regulated tech
- Case study: A/B test that triggered a regulator inquiry
- Marketing’s new responsibility in data provenance
- When brand voice meets compliance thresholds
- How governance expectations differ by region and sector
- The cost of rework in peer organizations
- Building credibility before the first review cycle
- Integrating legal and ethics teams without slowing down
- Setting up your campaign evidence baseline
- Why OECD AI Principles anchor marketing decisions
- How ISO/IEC 23894 defines marketing risk boundaries
- NIST AI RMF: where marketing fits in the lifecycle
- Mapping framework clauses to campaign stages
- When to use EU AI Act guidance vs internal policy
- Translating technical frameworks for non-engineers
- Common misapplications of AI governance standards
- How to source the correct version of any standard
- Using frameworks to preempt jurisdictional conflicts
- Why 'AI ethics' isn’t enough without anchoring
- Framework overlap: when to defer, when to lead
- Maintaining version control across global teams
- Defining the minimum viable evidence package
- Naming the stakeholders who shape campaign governance
- Aligning creative briefs with compliance checkpoints
- Documenting model inputs and audience logic
- Capturing A/B test design with intent clarity
- Versioning for cross-team traceability
- How to tag decisions for future audits
- Building a governance glossary for consistency
- Using timestamps to show due diligence
- Structuring feedback loops from legal teams
- Integrating ethics review into sprint planning
- Automating evidence capture without slowing output
- Why 'because we tested it' fails in governance reviews
- Using precedent from prior campaigns as evidence
- How to cite internal policy correctly
- Referencing competitor practices without copying
- When to pull in external research for weight
- Structuring a reason chain: cause → data → decision
- Avoiding circular logic in justification narratives
- Using third-party benchmarks to reinforce choices
- Deflecting 'because we’ve always done it' arguments
- Standing firm when pushback lacks sources
- Handling emotionally charged objections
- Turning objection into co-creation
- Mapping the real approval stakeholders in your org
- When to loop in legal vs waiting for review
- Creating joint briefs to reduce rework
- Running alignment sessions that end in decisions
- Managing conflicting regional requirements
- Handling last-minute change requests
- Using RACI to clarify ownership without friction
- When to escalate vs absorb feedback
- Building trust with compliance beyond sign-offs
- Documenting alignment to prevent backtracking
- Running post-mortems that improve future cycles
- Integrating feedback loops into creative sprints
- What regulators really want to know about AI in marketing
- Building a timeline of intent and execution
- How to answer 'why this audience?' convincingly
- Documenting exclusion logic for sensitive segments
- Showing diversity in testing and targeting
- Proving fairness without overclaim
- Handling 'black box' model criticism
- Using explainability tools in non-technical formats
- Preparing for the second and third follow-up
- Avoiding over-documentation that invites scrutiny
- Balancing transparency with competitive secrecy
- Turning regulator questions into strategic refinement
- What makes a precedent usable in governance?
- Building a searchable repository of past campaigns
- Tagging decisions by risk, region, and outcome
- How to anonymize sensitive campaign data
- Using precedent to accelerate new campaign reviews
- Avoiding 'this is different' objections
- Updating precedent when context shifts
- Sharing precedent across regional teams
- When to retire outdated examples
- Legal considerations in storing decision logs
- Integrating precedent into onboarding
- Automating suggestion of relevant precedent
- Mapping the journey from brief to approval
- Identifying governance chokepoints to redesign
- Embedding evidence capture into creative tools
- Using checklists that guide, not obstruct
- Automating version control across assets
- Integrating approvals into project management tools
- Setting up audit-ready handoffs
- Reducing manual rework with smart templates
- Defining 'done' in campaign governance
- Measuring workflow efficiency gains
- Scaling workflows across global teams
- Building resilience into high-pressure cycles
- Tailoring communication to legal vs leadership
- Using visuals to simplify complex AI logic
- Writing summaries that invite confidence
- Avoiding jargon that triggers red flags
- When to show data vs tell story
- Using precedent to reduce explanation load
- Framing risk in terms stakeholders understand
- Managing expectations around innovation pace
- Responding to skepticism without defensiveness
- Building credibility through consistency
- Documenting communication for future reference
- Scaling comms across distributed teams
- Understanding regional governance expectations
- When to globalize vs localize campaign rules
- Managing translation of governance concepts
- Handling inconsistent legal interpretations
- Building flexibility into global templates
- Using regional leads as governance nodes
- Tracking jurisdiction-specific risk thresholds
- Avoiding one-size-fits-all pitfalls
- Scaling compliance without slowing local teams
- Cross-regional precedent sharing
- Managing time-zone delays in approvals
- Designing for future regulatory changes
- Defining marketing’s role in enterprise risk
- Assessing current campaign approval friction
- Measuring time spent on rework and justification
- Mapping stakeholder influence on decisions
- Identifying recurring pain points by cycle
- Benchmarking against peer organization practices
- Prioritizing high-impact governance upgrades
- Using data to justify governance investment
- Tracking improvement over time
- Communicating posture to leadership
- Preparing for external audits
- Integrating feedback into continuous refinement
- Designing onboarding for new team members
- Creating a living governance handbook
- Running regular knowledge-sharing sessions
- Incentivizing evidence-based reasoning
- Measuring the impact of governance maturity
- Recognizing team members who model best practice
- Scaling practices across new markets
- Integrating governance into performance reviews
- Updating standards in response to change
- Ensuring continuity through transitions
- Documenting lessons from past failures
- Setting the stage for next-cycle innovation
How this maps to your situation
- Campaign approval delays
- Regulator and legal scrutiny cycles
- Cross-functional rework
- Global governance variance
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: 90 minutes per week for 12 weeks (12 modules). Each module designed for deep-dive reading and immediate application.
How this compares to the alternatives
Generic AI ethics courses offer principles without practice. This course delivers actionable, source-backed methods used by leading tech marketing teams, specifically designed for real-world scrutiny.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.