Strategic AI Governance and Policy Development

Course Overview

Artificial intelligence is reshaping how organizations and governments make strategic decisions, develop policy and drive innovation. As AI adoption accelerates, leaders must know how to align AI initiatives with organizational objectives while ensuring responsible governance, regulatory compliance and ethical use of the technology.

This Strategic AI Governance and Policy Development course equips executives, policymakers and senior professionals with the knowledge needed to lead AI-driven transformation. Participants explore AI technologies, strategic AI adoption, governance frameworks and the regulatory considerations that shape responsible AI implementation. Delivered by Mercury Training Center, it leaves participants with practical insight into building AI strategies, implementing governance and guiding their organizations toward effective, responsible AI adoption.

Course Objectives

• Assess how AI affects organizational leadership, strategy and decision-making
• Understand regulatory frameworks, ethical considerations and responsible AI practices
• Identify AI opportunities and align AI initiatives with organizational goals
• Recognize AI-related risks and apply methods to manage them responsibly
• Guide AI adoption and support AI-driven innovation within the organization

Who Should Attend

• Chief Information Officers (CIOs) and Chief Technology Officers (CTOs)
• Digital transformation managers
• AI strategy managers
• Risk and compliance managers
• Innovation managers
• Policymakers and senior leaders responsible for AI initiatives

Course Outline

Day 1: Foundations of AI Strategy and Leadership

• AI fundamentals and terminology: machine learning, NLP and predictive analytics
• AI technologies transforming organizations and their strategic importance for leadership
• The role of the Chief AI Officer (CAIO) and AI leadership responsibilities
• AI-driven decision-making and integrating AI into executive strategy
• Workshop: identifying AI opportunities in the organization

Day 2: AI Strategy and Strategic Roadmap

• Developing an AI strategy aligned with business objectives
• Identifying AI use cases and assessing AI readiness
• Data infrastructure requirements
• Building AI implementation roadmaps
• Workshop: designing a strategic AI roadmap

Day 3: AI Governance, Ethics and Regulation

• Responsible AI principles, governance frameworks, transparency and accountability
• Ethical AI development and trustworthy AI systems
• Global AI regulations, data protection and privacy laws
• Intellectual property in AI and regulatory compliance
• Case study: ethical challenges in real-world AI deployments

Day 4: AI Risk Management, Security and Policy

• AI safety risks, algorithmic bias and fairness
• Cybersecurity in AI systems and risk assessment frameworks
• Incident response strategies for AI
• Policy frameworks for AI deployment
• Workshop: conducting an AI risk and regulatory impact assessment

Day 5: AI Transformation, High-Performing Teams and Generative AI

• AI adoption strategies, change management and building AI-ready organizations
• Creating a data-driven culture and overcoming resistance
• AI talent strategy, AI team structures and cross-functional collaboration
• Generative AI capabilities, AI-driven innovation and future trends in AI leadership
• Exercise: developing an AI adoption framework and identifying generative AI opportunities