From automating dispatch to enabling predictive maintenance, AI is making waves in field service, yet for many organizations, the path forward is unclear. In this practical discussion, service leaders who’ve taken the leap will share how to start small, scale responsibly, and ensure AI implementations are effective, secure, and trusted. Panelists will kick off the panel sharing one low-risk high impact AI use case they recommend as a starting point, highlighting what they did, how they pitched it and early results. Additional discussion topics include:

• Making the case to leadership by framing AI adoption in terms of business outcomes, customer benefit, and operational efficiency to gain executive buy-in and resourcing
• Managing risk and IP concerns by protecting proprietary knowledge and mitigating AI risk in highly technical environments
• Practical strategies for launching pilot programs on a budget and focusing on targeted use cases like knowledge retrieval, ticket routing, or predictive diagnostics
• Measuring success to assess value from early efforts, tracking adoption, accuracy, and time savings to justify continued investment