Experience the difference. Meet your peers, talk with analysts, build your network and turn insights into action.
Kim Hedlin
Director Analyst
Gartner
Speaker Topics
- Driving Continuous AI Improvement
- Reinventing Workflows For AI‑Enabled Operations
- Selecting The Right AI Tools
Speaker Bio
Kim Hedlin is a Director, Research in Gartner's Customer Service and Support practice. She researches the way that service and support organizations improve their operational efficiency and deliver value to customers with the help of technology. She is particularly interested in knowledge management, including how people create, organize, and disseminate information in the age of AI.
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Sessions
Wednesday, November 04, 2026 03:15 PM - 03:35 PM MST
Get Up to Speed: 2026 Technology Trends for Customer Service and Support
Kim Hedlin,
Director Analyst, Gartner
Gartner's annual technology trends report analyzes proprietary survey data from more than 150 service and support leaders about their current and anticipated technology investments. Join this session to explore what's gaining traction, what's being phased out and what these technology trends mean for your organization.
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Thursday, November 05, 2026 10:30 AM - 11:15 AM MST
Roundtable: Share Agentic AI Best Practices and Lessons Learned
Kim Hedlin,
Director Analyst, Gartner
This roundtable is designed for service and support leaders already deploying or piloting agentic AI. Compare real-world experiences, share lessons learned and surface what’s actually working in production. The discussion will focus on practical challenges, emerging patterns and how organizations are evolving their approaches as agentic capabilities scale.
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Thursday, November 05, 2026 03:45 PM - 04:30 PM MST
Roundtable: Modernize Knowledge Management for the AI Era
Kim Hedlin,
Director Analyst, Gartner
Knowledge management (KM) is a critical driver of AI success, operational efficiency and improved customer experience. However, organizational realities — content that’s not machine readable, ambiguous data ownership, fractured tech architectures and unstandardized processes — often get in the way. This discussion tackles today’s most pressing challenges in KM and best practices to overcome them.
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