Customers no longer judge field service only on whether the job gets done; they expect proactive communication, accurate ETAs, personalized recommendations, and seamless handoffs between channels and touchpoints. Agentic AI makes this possible by orchestrating end to end workflows – from intelligent triage and dispatch to technician guidance and follow-up – while keeping humans in control of key decisions. For leaders, the opportunity is to use AI agents to create a more predictive and customer centric service experience without adding complexity for frontline teams.

• How agentic AI can make service more proactive, personalized, and customer-centric4Where AI can improve service performance, from scheduling and dispatch to first-time fix and faster resolution
• What leaders need to measure and govern to scale AI with confidence

Agentic AI is moving beyond hype in field service, taking on real work across triage, dispatch, and knowledge that directly improves uptime and customer experience. This session will unpack concrete use cases where autonomous and semi autonomous AI agents classify incidents, recommend next best actions, and match the right technician, parts, and time window without breaking existing workflows. We’ll discuss what it takes to connect these agents to clean data, robust knowledge bases, and governance so they can be trusted by technicians, planners, and leaders. Attendees will leave with a practical view of where agentic AI delivers measurable ROI today, what pitfalls to avoid, and how to design a realistic roadmap from pilot to scaled deployment

Key discussions include:

• Exploring concrete agentic AI use cases in triage, scheduling, and support
• Integrating AI into existing workflows without breaking them
• Benchmark where you are on the agentic AI maturity curve