AI Log Volume Surge Forces Enterprises to Rethink Observability — Dynatrace, Inc.

Event summary

Dynatrace's 2026 report finds AI workloads drove a 93% increase in log volume over the past year.
Enterprisess use an average of seven different tools to manage logs and telemetry.
80% of organizations report that turning telemetry into actionable insights is negatively impacting customer experience and delaying AI initiatives.
Organizations exclude an average of 86% of log data to manage costs and system limitations.
Nearly three-quarters of respondents say AI workloads demand a platform-based approach to log management.

The big picture

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, forcing enterprises to rethink how they manage and analyze telemetry data. This shift is critical for maintaining visibility, controlling costs, and supporting AI at scale. The fragmentation of tools and the high costs associated with log management are emerging as key barriers to the reliability and trustworthiness of AI systems.

What we're watching

Platform Adoption: How quickly enterprises will shift from fragmented log management tools to unified observability platforms.
Cost Optimization: Whether organizations can balance the need for comprehensive log data with the rising costs of log management.
AI Reliability: The pace at which enterprises can make AI systems reliable and trustworthy with unified telemetry data.