Introduction:

Artificial Intelligence (AI) is reshaping how governments deliver services, manage resources, and interact with citizens. At its core, AI involves computational techniques that can analyze data, recognize patterns, and make predictive decisions. In the public sector, AI holds the potential to increase efficiency, strengthen transparency, and enable more citizen centered services. This training program introduces participants to the essential concepts, technologies, and governance considerations of AI. It provides structured frameworks to understand AI basics, explore its technical underpinnings, and recognize the critical role of data and ethics in sustainable adoption.

Program Objectives:

At the end of this program, participants will be able to:

• Analyze core AI concepts, scope, and value propositions for public service.

• Distinguish major AI technologies and public sector application domains.

• Classify data governance, privacy, and security requirements enabling AI.

• Evaluate responsible AI principles for trust, fairness, and accountability.

• Outline operating models, policies, and roadmaps for an AI-ready public sector.

Target Audience:

• Public sector leaders and program managers.

• Digital government and e-services teams.

• Data, analytics, and statistics units.

• IT and cybersecurity personnel.

• Policy professionals exploring AI use cases.

Program Outline:

Unit 1:

Foundations of AI in Government:

• Core definitions of Artificial Intelligence and its public sector relevance.

• Methods of distinguishing myths from realities in AI adoption.

• Frameworks for interpreting the role of AI in decision making.

• Processes for aligning AI with government priorities.

• Approaches to ensuring basic literacy in AI across institutions.

Unit 2:

AI Technologies and Data Foundations:

• Techniques of machine learning, natural language processing, and computer vision.

• Methods of applying chatbots and automated assistants in government services.

• Structures for data governance in public institutions.

• Approaches for ensuring privacy, security, and ethical handling of citizen data.

• Frameworks for open data as an enabler of AI solutions.

Unit 3:

Ethics, Trust, and Institutional Readiness:

• Processes for embedding transparency and accountability in AI systems.

• Strategies for aligning AI with public values and fairness.

• Frameworks for institutional policy and capacity development.

• Models of partnerships and sustainable adoption pathways.

• Approaches for fostering an AI ready culture in the public sector.