AI Knowledge & Policy Forums

Why This Course

As Artificial Intelligence continues to transform economies, societies, and institutions, the need for informed, collaborative, and responsible policy development has never been greater.

Leaders and policymakers must understand the intersection between AI innovation, ethics, and governance to ensure that technology serves the well-being of humans and society.

This program provides a platform for participants to explore global AI governance frameworks, policy challenges, and strategic opportunities.

Through expert-led sessions, case studies, and roundtable discussions, participants will gain the insights necessary to shape AI policies, strategies, and multi-stakeholder dialogues that strike a balance between innovation, compliance, and trust.

What You’ll Learn and Practice

By joining this program, you will:

• Understand global trends and frameworks in AI policy, regulation, and governance.
• Analyze ethical, legal, and socio-economic implications of AI adoption.
• Learn how governments, industries, and institutions collaborate to shape AI strategies.
• Gain tools for developing national and organizational AI policies.
• Engage in policy simulation exercises and multi-stakeholder discussions on AI futures.

The Program Flow

Day 1: The Global Landscape of AI Policy & Governance

• The evolution of AI governance — from innovation to regulation.
• Overview of global AI policy frameworks: OECD AI Principles, UNESCO Recommendations, EU AI Act, U.S. AI Executive Order, and GCC AI strategies.
• Key governance themes: accountability, fairness, transparency, and human oversight.
• Case study: comparative analysis of national AI strategies from leading economies.
• Forum discussion: “Who owns AI policy — governments, industry, or society?”

Day 2: AI Ethics, Regulation, and Legal Frameworks

• The ethical foundations of AI policymaking.
• Emerging regulatory instruments: data privacy (GDPR), algorithmic transparency, and auditability.
• AI risk classification and conformity assessment requirements.
• Role of legal frameworks in enabling innovation responsibly.
• Group activity: analyzing an AI regulation draft and identifying its strengths and gaps.

Day 3: National Strategies & Institutional Policy Development

• Building a national AI strategy: vision, objectives, and governance structures.
• Policy design for data infrastructure, education, innovation, and public trust.
• Institutional mechanisms for AI coordination and implementation.
• Aligning national AI goals with sustainable development and digital transformation agendas.
• Workshop: drafting an outline for a national or sectoral AI policy roadmap.

Day 4: Public-Private Collaboration & Global Governance

• Role of multi-stakeholder collaboration in AI governance.
• Partnerships between governments, academia, industry, and civil society.
• Global coordination challenges — interoperability, standardization, and accountability.
• Regional perspectives: EU, GCC, Asia-Pacific, and Africa.
• Simulation: designing a multi-stakeholder AI policy forum and negotiation scenario.

Day 5: The Future of AI Policy — Innovation, Trust & Human-Centric Development

• Responsible innovation: aligning AI policy with ethical and social goals.
• Emerging frontiers: generative AI, autonomous systems, and global governance.
• Measuring AI readiness and policy impact.
• Creating adaptive, agile AI policies for the future.
• Roundtable workshop: developing an AI policy declaration and strategic action plan.

Individual Impact

• Gain a deep understanding of global AI policy frameworks and trends.
• Strengthen the ability to analyze and influence national and institutional AI policies.
• Build communication and negotiation skills for multi-stakeholder engagement.
• Develop critical thinking in balancing innovation, ethics, and compliance.
• Contribute meaningfully to global discussions on AI governance and sustainability.

Work Impact

• Strengthen institutional readiness for AI governance and compliance.
• Enhance strategic positioning in national and global AI policy dialogues.
• Improve decision-making on AI adoption and regulatory alignment.
• Foster collaboration with policymakers, regulators, and industry stakeholders.
• Support responsible innovation and public trust through informed governance.

Training Methodology

This program emphasizes dialogue, collaboration, and strategic insight through real-world analysis and interactive discussions.

Learning methods include:

• Expert-led sessions with global AI governance case studies.
• Policy simulation exercises and collaborative workshops.
• Group debates and stakeholder negotiation scenarios.
• Interactive forums with policy templates and global strategy toolkits.
• Roundtable discussions on future AI governance directions.

Beyond the Course

Upon completion, participants will be equipped to actively contribute to AI policy development, governance dialogues, and cross-sector initiatives.

They will leave with a clear understanding of how to shape AI strategies and frameworks that drive innovation responsibly — ensuring technology advances human values, trust, and societal progress.