AI Strategy for Leaders: Generative AI, Risk & Governance

This course contains the use of artificial intelligence.

Artificial Intelligence is no longer just a technical experiment—it is a fundamental driver of business transformation. Designed specifically for executives, directors, and business leaders, this rigorous course cuts through the hype to provide a clear, strategic roadmap for AI adoption. Led by Mana, this program bridges the gap between high-level business strategy and technical reality, equipping you with the mental models needed to evaluate opportunities, drive innovation, and lead your organization into the future.

Spanning four comprehensive parts delivered through a fast-paced, presentation-driven format, you will explore everything from core machine learning concepts and multimodal systems to complex governance frameworks and economic impact. Learn how to map AI to critical business value drivers, evaluate the Build vs. Buy vs. Partner dilemma, calculate accurate ROI, and navigate the rapidly shifting landscape of global regulations like the EU AI Act.

Beyond technology and strategy, true leadership in the AI era requires managing human change. Discover how to address data privacy, mitigate hallucinations and bias, redesign workflows, and upskill your workforce to foster a culture of continuous innovation. Whether you are preparing your first Proof of Concept or redefining the C-suite’s role in the age of intelligent agents, this course gives you the executive clarity needed to lead with confidence.

This course contains the use of artificial intelligence.

Curriculum Outline

Foundations of AI and Generative AI for Executives

• Demystifying AI, Machine Learning, and Deep Learning
• The Generative AI Revolution: What Makes Today Different
• Core Capabilities: Text, Image, Audio, and Multimodal Systems
• Separating Hype from Reality: Capabilities and Limitations
• The Economic Impact and Productivity Promise
• Executive Mental Models for AI Adoption

Strategic Integration and Use Case Identification

• Mapping AI to Business Value Drivers
• Identifying High-Impact Internal and External Use Cases
• Build vs. Buy vs. Partner: The Strategic Technology Decision
• Data Readiness: The Fuel for Generative AI
• The Proof of Concept (PoC) Lifecycle
• Calculating ROI and Managing Innovation Portfolios

Governance, Risk, Ethics, and Compliance

• Navigating AI Risks: Hallucinations, Bias, and Toxicity
• Data Privacy, Confidentiality, and Enterprise Security
• Copyright, Intellectual Property, and Legal Landscapes
• Establishing an AI Governance Framework and Ethics Board
• Global Regulation: EU AI Act and Emerging Policies
• Transparency, Explainability, and Trust

Leading Organizational Change and Future Innovation

• The Human Element: Change Management for the AI Era
• Upskilling and Reskilling the Workforce
• Redesigning Workflows and Job Roles
• Fostering a Culture of Continuous AI Innovation
• The Evolving Role of the Executive and the C-Suite
• Looking Ahead: Agents, AGI, and Next-Decade Strategy

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