As enterprises rapidly shift from AI experimentation to production deployment, IT leaders face a critical challenge: How do you ensure your LLM-powered applications deliver reliable performance, measurable adoption, and cost-effective operations?

Join Mark Beccue, principal analyst at Omdia, and Chris Blaisure, senior director of field technology, AI & analytics at Elastic, for an essential discussion on AI observability.

Discover how leading organizations are tackling the most pressing challenges in AI model lifecycle management — from performance monitoring and response accuracy to cost optimization and ROI measurement.

In this session, you’ll learn:

• Real-world AI use cases driving field productivity and customer experience
• Practical approaches to monitoring GenAI workloads for performance, usage, and reliability
• Critical signals for tracking conversation quality, response accuracy, and adoption metrics
• The hidden success factor: why your data foundation matters more than the model itself
• Common pitfalls in AI observability and how to avoid them
• Actionable benchmarks for measuring AI application success