‘Agentic AI’ is promoted as the next step in digital transformation of work, life, and learning. Such systems are often based on the hugely popular and successful GenAI and Large Language Models (LLM). However, due to their reliance on other technologies, automated communication and coordination, and in certain cases delegated actions, they bring their own set of new, pressing and peculiar risks and threats to security, identity management, privacy and data protection. This course provides a solid basis on the topic and technological foundations of agentic AI for non-technical audience; it brings clarity, context, and meaning to the plethora of recent local and international guidelines and discussion papers. This comprehensive overview is critical for audience in charge of governance, strategies, and decision making around agentic AI, who need to go beyond the flashy headlines to apply careful thought about introducing or allowing such new, pervasive, and invasive technology.

This course complements our What to look out for when procuring an AI Solution - Legal and Technology Essentials course and our Deep Learning Essentials course. It provides the foundation for our Agentic AI Risk Assessment course / workshop.

Who should attend?

• Privacy / Software Engineers, Technical Staff, Developers, Data Analysts, Data Architects, and Project / Risk Managers
• Data Protection Officers (DPOs), Compliance Professionals
• Executives, Managers, and Staff involved in the management, collection, use or other processing of personal data

Course Details

Course Details

• Key terms​
  • Agent
  • Artificial Intelligence (AI), Machine Learning (ML), Model
  • AI Agent, agentic AI, agentic AI system
  • Inference, Reasoning, Computation
  • GenAI, LLM, ‘next word prediction’, prompting, Chain-of-Thought, ReAct
• Basic architectures
  • AI agent components
  • Agent ‘action and communication’
  • Single Agent versus Multi-Agent
  • Work and data flow
  • Automation and Autonomy in view of Identity Management, Authentication & Authorisation​
• Technology and Governance
  • Risks
  • Threat Models
  • Example: Agentic Risk & Capability Framework (ARC)
• Overview on Guidelines and References
  • IMDA Model AI Governance Framework for Agentic AI
  • CSA Securing Agentic AI
  • WEF AI Agents in Action: Foundations for Evaluation and Governance
  • OWASP and others

Course Facilitator

Albert Pichlmaier  Senior Cybersecurity and Privacy Engineer Senior Learning Technology Designer, Drew Data Protection & Cybersecurity Academy