AI Improves Reliability but Fails to Cut Costs or Speed Incident Response, Dynatrace Study Finds

AI technologies are meeting enterprise expectations for improving reliability and developer productivity, but are falling short on lowering costs and reducing mean time to resolution, according to Dynatrace's new State of SRE and Platform Engineering 2026 study. 

 

The global survey of 919 IT leaders found that gap points to a need for greater system-level intelligence and workflow orchestration, rather than simply adding AI tools to existing environments, the company said.

Dynatrace said the findings help explain why it recently announced its intent to acquire Arize. According to the study, 67% of site reliability engineers now name AI model monitoring their top use case, and monitoring for model performance and accuracy is already the most common AI-powered capability among SREs, at 58%. 

 

The company added that the demand for AI evaluation is outpacing the tools built to handle it, with more than a third of platform engineers citing tool integration as their biggest barrier.

Steve Tack, chief product officer at Dynatrace, said the acquisition is meant to close that gap directly. "AI engineering teams have been evaluating in one set of tools while operations teams monitor in another, and that gap is no longer sustainable as AI moves deeper into enterprise production," he said. "SRE and platform engineering laid the groundwork for modern digital reliability, but AI is rewriting the rules. Enterprises need to now move from managing systems to orchestrating them, connecting observability, automation, and agentic AI to operate at the speed these initiatives demand, turning insight into action at scale."

The study found SRE and platform engineering are now firmly established across large enterprises, according to Dynatrace, with 92% of organizations reporting executive leadership support for SRE initiatives. Among organizations practicing platform engineering, 89% have implemented an internal developer platform, the study found, with 60% reporting broad adoption across departments. Seventy-three percent of SRE and platform engineering teams now collaborate and share responsibilities across reliability and platform domains, according to Dynatrace, which cited Gartner projections that 80% of enterprises will adopt SRE practices by 2028, up from just 30% in 2024.

More than a third, or 37%, of platform engineers report that integrating with existing tools and systems is their top challenge, according to the study, and only 40% of platform engineers report embedding observability across all deployment stages. Nearly half of SRE respondents said too many data sources and metrics hinder their ability to define and manage effective service-level objectives, Dynatrace found.

Half of SREs now use AI-powered capabilities for automated incident response, according to the study, a shift Dynatrace said signals a move toward agentic operations in which observability must act as the control plane governing when and how autonomous actions are taken. Among platform engineers, 55% prioritize enabling developers with AI-powered tools such as coding copilots and chatbots, the study found.