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The 53-point gap: AI Adoption Has Outpaced Trust

About this event

AI workloads are fundamentally changing observability, from cost structures to operational strategy.

The Observability Imperative Report, based on insights from 500 engineering and platform practitioners, reveals that 49% of teams say AI workloads now drive half their observability bill, while most organizations still struggle with visibility, trust, and data fidelity.

Join Chris Churilo, VP of Marketing at groundcover, and Chris J. Preimesberger, veteran tech journalist, for a live discussion on how engineering teams are adapting observability practices for the AI era.

In this session, we’ll explore the growing gap between AI adoption and operational confidence, why traditional sampling approaches are breaking down, and what leading teams are prioritizing as agentic AI systems move into production.

Attendees will learn:

  • Why AI workloads are dramatically increasing observability costs
  • Why aggressive sampling creates operational blind spots
  • How observability-driven development (ODD) is emerging in modern AI operations
  • What practitioners running AI workloads in production are changing right now

groundcover

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