From GenAI to Agentic AI
How agentic systems differ from conversational GenAI and traditional automation
EMERGING AI PROGRAM
Understand AI agents, agentic workflows, enterprise applications, human oversight and implementation considerations without requiring a developer background
CURRICULUM
How agentic systems differ from conversational GenAI and traditional automation
Goals, reasoning, planning, tools, memory, actions and feedback loops
Single-agent and multi-step workflows, orchestration and task execution
How agents may interact with tools, data sources, APIs and enterprise applications
Approval points, escalation, intervention and accountable human oversight
Illustrative use cases across operations, service, productivity and knowledge workflows
Autonomy risk, permissions, security, data exposure, errors, monitoring and controls
Use-case suitability, process readiness, governance, evaluation and adoption considerations
LEARNING OUTCOMES
Explain what Agentic AI is and how it differs from standard Generative AI
Describe the building blocks of an agentic workflow
Recognise enterprise use cases suited to agentic approaches
Understand why human oversight and permissions matter
Identify common implementation risks and guardrails
Participate more confidently in business discussions about enterprise agents
WHO SHOULD ATTEND
Basic awareness of Generative AI concepts is helpful; coding is not required
Instructor-led explanation, scenarios, demonstrations and guided exercises focused on professional application

PROGRAM LEAD
Senior program management professional and PMP® certified professional with 20+ years of technology-industry experience across program delivery, governance, stakeholder management and transformation initiatives
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