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

• Developing strategies to break down silos between contact centers and field service, and aligning KPI’s and support workflows that minimize customer effort
• Utilizing AI and knowledge to streamline, not dehumanize
• Creating a practical blueprint to shift your contact center and technical support from reactive firefighting to proactive customer support models

As organizations rush to deploy AI tools, most professionals are left to figure out ChatGPT, Claude, and Copilot on their own — and the results are predictable. Some experiment and thrive; most try once, get mediocre results, and quietly abandon the tools. The missing ingredient isn't better training content — it's a sustained, peer-driven learning structure. This workshop shows leaders how to launch Professional Learning Groups (PLGs) that build real AI fluency across teams by having people learn together at a shared screen, bring their own work challenges to live prompting sessions, and collectively discover the AI use cases that actually matter to their business — not just the ones that look good in a vendor demo.

• Designing and launching a Professional Learning Group of 6–12 members with rotating facilitation, shared norms, and a regular meeting cadence that turns AI experimentation from a solo struggle into a supported team practice
• Using structured "live prompting labs" and use-case discovery protocols where group members work directly in AI chat interfaces with real business problems — learning from each other's approaches, building prompt literacy, and surfacing high-value applications grounded in their actual workflows
• Creating a practical PLG charter and first-quarter learning agenda that connects peer-driven AI exploration to measurable business outcomes — shifting your team from passive AI awareness to active, accountable capability building

Most service organizations say knowledge is their advantage, but their "knowledge base" is really a combination of PDFs, emails, and tribal tips stuck in technicians' heads. In this session, John Tocado, Principal Analyst, Systems Development at JLG Industries, shares how his team is building a practical "knowledge spine" that connects voice to text debriefs from the field, structured service content, and AI tools into one system techs actually rely on.

• Developing practical methods to capture tribal knowledge via mobile, voice-to-text, and quick debriefs so technicians can contribute without extra admin work
• Transforming raw notes, photos, and fault information into structured, AI-ready knowledge
• Creating tactics to incentivize ongoing knowledge sharing and usage

In many organizations, contact and support centers still operate on legacy scripts, static FAQs, and disconnected ticket systems, forcing agents to chase information and hand work off multiple times before a job is done. This panel brings together leaders who are using AI powered knowledge bases, workflow automation, and integrated field service platforms to give agents a single view of the customer, asset, and work order—and to guide them step by step from diagnosis to dispatch to closure. Speakers will discuss how they curate and govern knowledge so answers stay trusted. Attendees will hear where digital transformation has truly reduced handle time, repeat calls, and fallout in the field—and where cultural and process change has been just as important as the tech

• Designing and maintaining a knowledge layer that supports agents and customers across channels while directly linking into work order, scheduling, and asset systems
• Developing best-in-class change management practices—governance, training, and metrics—that build agent trust in new tools and ensure knowledge and digital capabilities actually get used in daily operations