Program · Executive Track

Executive
AI Leadership

Strategy, governance, and capital allocation for C-suite and board-level leaders - eight modules, self-paced, fully online.

What it is

A self-paced, eight-module certification for senior executives responsible for AI decisions across the enterprise. Fully online, no live sessions, no fixed cohorts. Personalised faculty feedback on submitted work.

Who it's for
  • C-suite and board members setting enterprise AI direction
  • Chief Risk, Compliance, and Legal officers
  • Heads of Transformation, Strategy, and Innovation
  • Investors and non-executive directors shaping AI-native portfolios
Curriculum

Eight modules
One executive standard

01 AI Foundations, Strategy & Operating Models
  • AI, Machine Learning and Generative AI: The Executive Landscape
  • Identifying Where AI Creates Durable Competitive Advantage
  • Designing the AI Operating Model: Centralized, Federated and Embedded Approaches
  • Technology and Deployment Choices: Cloud, Private and Edge
  • Executive AI Fluency: Judgment, Literacy and Emerging Regulatory Expectations
  • From the First 90 Days to an Enterprise AI Roadmap
  • Workforce Adoption, Operating Rhythms and Emerging Capabilities, Including AI Agents
02 AI Standards & Regulatory Frameworks
  • The Global Regulatory Landscape: ISO/IEC 42001, NIST AI RMF and the EU AI Act
  • Inside ISO/IEC 42001: Building a Certifiable AI Management System
  • The EU AI Act: Risk Classifications, Obligations and Compliance Timelines
  • Australia's AI Governance Environment: Guardrails, Privacy Reform and Government Standards
  • One Enterprise Control Framework, Multiple Jurisdictions
  • Third-Party AI and Vendor Accountability
03 Trusted Data & Decision Integrity
  • Data as the Foundation of Trustworthy AI
  • Linking Data Quality to Financial Performance
  • Evaluating AI Outputs: A Framework for Executive Scrutiny
  • Achieving AI-Ready Data: Quality, Lineage and Provenance
  • Data Governance as an Enterprise Operating Model
  • Monitoring, Reporting and Safeguarding Customer Trust
04 AI Risk Management, Assurance & Resilience
  • The Executive AI Risk Landscape: Six Core Exposures
  • AI Security: Managing the New Attack Surface
  • Assurance Frameworks That Satisfy Boards, Regulators and Auditors
  • Human Oversight and the Path to Autonomy
  • Guardrails, Safety Nets and Designing for Failure
  • Incident Response, Recovery and Organizational Resilience
05 AI Investment Strategies
  • AI as a Capital Allocation Discipline
  • Build, Buy or Partner: Sourcing Strategies and Stage Gates
  • Constructing Investment-Grade AI Business Cases
  • Measuring Return: A Practical ROI Framework for AI
  • Scaling from Pilot to Profit and Loss
  • Portfolio Governance and Value Realization
06 Board Oversight & Accountability
  • The Board's Role in the Age of AI
  • Directors' Duties, Oversight Structures and AI Expertise
  • What Boards Must Know, Approve and Demand
  • Executive Accountability and Clear Ownership
  • Board Reporting: Dashboards, Metrics and Escalation Thresholds
  • The Questions Every Director Should Ask
07 Enterprise Transformation, Talent & Change
  • Leading AI-Driven Organizational Transformation
  • Designing AI Teams and Enterprise Structures
  • Decision Rights, Governance and Ways of Working
  • Talent Strategy: Build, Buy, Borrow and Redeploy
  • Structured Change Management for AI Adoption
  • Adaptive Leadership and Building a Learning Culture
08 Ethics, Trust & Reputation
  • Trust as a Strategic Asset
  • From Principles to Practice: Ethics Backed by Controls and Evidence
  • Recognizing and Preventing Common AI Failure Patterns
  • Transparency, Explainability and Recourse
  • Protecting Reputation and Stakeholder Confidence at Scale
Tuition
USD$1,280

All-inclusive. Covers learning materials, faculty feedback, the formally issued AIACI™ certificate, LinkedIn-shareable digital badge, direct academic support throughout, and annual recertification at no extra cost.

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