Artificial Intelligence (AI) is reshaping public sector operations, decision-making processes, and service delivery on a global scale.

This instructor-led live training, available both online and onsite, is designed for public sector leaders who have little or no prior background in AI. The course aims to help participants grasp the fundamentals of AI, assess its strategic importance, and explore how it can be ethically and effectively adopted within government organisations.

Upon completion of this training, participants will be able to:

• Understand core concepts and terminology in artificial intelligence.
• Evaluate the opportunities and risks associated with AI in public sector contexts.
• Explore ethical and regulatory considerations pertinent to AI use in government.
• Develop informed perspectives on AI-related policy, procurement, and strategy.

Course Format

• Interactive lectures and discussions.
• Real-world case studies from the public sector.
• Guided group reflection and policy exercises.

Course Customization Options

• For requests to customize this training, please contact us to arrange.

Course Outline

Introduction to Artificial Intelligence

• What is AI? Key terms and technologies.
• Differences between AI, machine learning (ML), and automation.
• Trends in AI adoption within the public sector.

AI Use Cases in Government

• Service delivery: chatbots, document automation, and predictive analytics.
• Policy and planning: modelling, forecasting, and simulations.
• Examples from public safety, healthcare, and citizen engagement.

Risks, Ethics, and Bias in AI

• Understanding algorithmic bias and fairness.
• Ethical decision-making in AI systems.
• Transparency, accountability, and explainability.

AI Governance and Regulatory Landscape

• The EU AI Act, GDPR, and global regulatory developments.
• National AI strategies and governance frameworks.
• Considerations regarding public trust and citizen impact.

Procurement and Implementation Strategies

• What leaders need to know before investing in AI.
• Evaluating vendors, pilot projects, and partnerships.
• Inter-agency collaboration and data infrastructure readiness.

Strategic Planning for AI Adoption

• Building internal AI literacy and forming cross-functional teams.
• Aligning AI initiatives with mission outcomes.
• Roadmapping AI adoption within a department or agency.