How Do You Monitor AI Agents in Production Without Breaking Incident Response?

As AI systems move rapidly from experimentation into production, organizations are discovering that adoption alone is not the hard part, understanding, governing, and trusting AI in live environments is. In this episode of the Tech Transformed, Shubhangi Dua speaks with Camden Swita, Head of AI, New Relic, about why AI observability has become a critical requirement for modern enterprises, particularly as agentic AI and AI-driven operations take on increasingly autonomous roles. The discussion explores how traditional observability models fall short when applied to probabilistic systems, why many AI ops initiatives stall at proof-of-concept, and what security and IT leaders must prioritize to safely scale AI in production. Be the first to see how intelligent observability takes you beyond dashboards to agentic AI with business impact at New Relic Advance, February 24, 2026. Key Takeaways 1. AI adoption is accelerating in enterprise environments. 2. Organizations face complexities in productionizing AI features. 3. Natural language querying is a common AI application. 4. AI agents are increasingly used in IT operations. 5. Observability is crucial for understanding AI systems. 6. Traditional observability solutions are evolving to include AI monitoring. 7.Incident response teams struggle with alert noise and context gathering. 8.AI can assist in incident management and root cause analysis. 9. Future trends include more reliable AI agents and monitoring solutions. 10. Organizations need to invest in AI observability to succeed. Chapters 01:20 The Current State of AI Adoption 02:28 Purposeful AI Usage in Organizations 04:40 Observability in the Age of AI 08:05 Evolving Observability Solutions 11:36 Challenges in Incident Response 16:04 Integrating AI in Operations 23:33 Future Trends in AI Monitoring 30:29 Investment Strategies for AI Solutions