Agentic AI for Operations
About This Course
Agentic artificial intelligence (AI) is changing how operational work is designed, staffed and governed. Unlike conventional automation, AI agents can plan tasks, call tools, interact with systems and execute multi-step workflows. This shifts operations management from improving human-only processes to designing hybrid workflows where people and AI agents work together under clear oversight.
This course is designed for operations leaders, process owners, business transformation teams and workforce planners who need to redesign processes for AI-enabled operations. Participants will learn how to decompose workflows, allocate tasks between humans and agents, define exception pathways, plan agent-supported capacity and set operational key performance indicators (KPIs) for accountable performance.
Participants will apply the course frameworks to a selected operational process and leave with a practical redesign concept that can be adapted for workplace discussion, pilot planning or transformation roadmap development.
What You'll Learn
- Decompose a process and allocate steps correctly between human and agent
- Identify the judgement threshold where human oversight remains non-negotiable
- Avoid common redesign failure modes such as removing oversight too early
Fleet-Level Workforce Planning
- Build a workforce plan that treats agent capacity as a resourced, budgeted asset
- Design human-agent collaboration models appropriate to different risk levels
- Resolve organisational design questions of fleet ownership and accountability
Operational Key Performance Indicators (KPIs) and the Operating Model
- Define operational KPIs for agentic processes, including exception handling metrics
- Design exception-handling pathways and escalation thresholds
- Present an integrated operating model redesign for a process in their own function
Entry Requirements
- Participants should have at least two years of experience in operations management, business process ownership, process improvement, transformation, service delivery, workforce planning or team leadership.
- Basic digital literacy is expected, but coding, data science or artificial intelligence (AI) engineering experience is not required.