AI Literacy for Decision-Makers

Why This Course

Artificial Intelligence is no longer a futuristic concept — it is an operational necessity shaping competitiveness, governance, and innovation across every sector.

For leaders, understanding how AI works, where it adds value, and how to manage its risks is critical to making informed and confident decisions.

This program provides a practical and accessible foundation in AI concepts, capabilities, and strategic implications.

It empowers decision-makers to align AI initiatives with organizational goals, ethical principles, and long-term sustainability while driving innovation and responsible transformation.

What You’ll Learn and Practice

By joining this program, you will:

• Understand the core principles and applications of Artificial Intelligence.
• Learn to evaluate AI opportunities and risks in business and policy contexts.
• Gain insight into data-driven decision-making and digital transformation.
• Explore governance, ethics, and compliance frameworks for AI adoption.
• Develop strategies to lead teams and organizations confidently in the AI era.

The Program Flow

Day 1: Understanding Artificial Intelligence

• What AI is — and what it is not.
• The evolution of AI: from automation to generative and cognitive systems.
• Key AI technologies: machine learning, natural language processing, and computer vision.
• The role of data in AI — how quality, bias, and governance shape outcomes.
• Workshop: Identifying where AI is already transforming your industry.

Day 2: The Strategic Value of AI

• How AI creates value in public and private sectors.
• AI use cases in finance, healthcare, manufacturing, and government.
• Linking AI initiatives to organizational strategy and KPIs.
• Evaluating the business case for AI investment and ROI assessment.
• Case study: successful AI-driven transformation in a leading organization.

Day 3: Risks, Ethics, and Responsible AI

• Understanding AI risks: bias, security, privacy, and reputational impact.
• Principles of responsible and ethical AI — fairness, transparency, accountability.
• Overview of major global frameworks (NIST RMF, EU AI Act, OECD, UNESCO).
• Balancing innovation with regulation and stakeholder trust.
• Group activity: assessing the ethical and strategic risks of an AI project.

Day 4: Governance, Data Strategy, and Change Management

• Building organizational readiness for AI adoption.
• Data governance and infrastructure for trustworthy AI.
• Defining roles, accountability, and cross-functional collaboration.
• Managing organizational change and workforce reskilling.
• Workshop: Creating an AI governance model aligned with your organization’s vision.

Day 5: The Future of AI Leadership and Decision-Making

• Emerging trends: generative AI, automation, and human-AI collaboration.
• Leading AI innovation while managing uncertainty and disruption.
• Fostering an AI-literate culture within your organization.
• Developing your roadmap for sustainable and ethical AI adoption.
• Action session: building a strategic AI decision-making framework for your role.

Individual Impact

• Gain the knowledge to evaluate and guide AI initiatives effectively.
• Strengthen the ability to make data-driven and ethically informed decisions.
• Build confidence in communicating AI opportunities and risks to stakeholders.
• Enhance strategic thinking in leading innovation and digital transformation.
• Develop a clear vision for responsible AI leadership within your organization.

Work Impact

• Strengthen executive understanding and oversight of AI initiatives.
• Align AI adoption with strategic objectives and compliance requirements.
• Reduce risks through informed governance and responsible implementation.
• Build a culture of AI literacy and digital confidence across departments.
• Improve innovation capacity and long-term organizational resilience.

Training Methodology

This program blends strategic insight, case-based learning, and collaborative discussion to deliver clarity and actionable understanding for non-technical leaders.

Learning methods include:

• Executive-level lectures and practical demonstrations.
• Global case studies of AI implementation success and failure.
• Group discussions and ethical decision-making exercises.
• Strategic planning and governance framework workshops.
• Practical toolkits and checklists for responsible AI decision-making.

Beyond the Course

Upon completion, participants will be equipped to make informed, strategic, and ethical decisions about AI adoption and governance.

They will leave ready to lead AI-driven initiatives with confidence, ensuring innovation aligns with organizational goals, societal values, and long-term sustainability.