While AI adoption is accelerating, concerns about reliability and trust make it challenging to transition initiatives from concept to production, according to a new report from Dynatrace.

To address this, business leaders are prioritising observability solutions to scale their AI projects, with more than two-thirds (70%) saying observability budgets have increase in the past year.

Dynatrace released findings from a global survey of 842 CIOs, CTOs, and other senior technology leaders involved in IT operations and DevOps management in large organisations.

The survey found that 100% of business leaders are using AI as part of their operations today, with top use cases including data management (57%), AI governance (50%), and security operations (46%).

AI use cases such as sustainability (27%) and logs management (29%) present exciting opportunities for organisations to expand adoption and unlock greater efficiency and ROI.

The two major categories where business leaders anticipate AI-powered automation delivering significant value are real-time detection of and response to security risks (37%) and anomaly detection (41%).

When it comes to AI governance, trust and security, Dynatrace found that one in four business leaders believe improving AI governance and trust should be their highest priority.

For leaders in charge of data governance, their top two areas of concern with AI reliability are related to data quality and predictability (50%) and data privacy (45%).

More than two thirds (69%) of AI-powered decisions still include human-in-the-loop processes to verify accuracy.

Nearly all (98%) business leaders reported using AI to manage security compliance in some capacity, with a combined 69% seeing increased budgets for AI-powered threat detection in the past year and expecting budgets to increase next year.

“Enterprise IT software and applications must evolve from simply adding AI to existing systems toward building truly AI-native experiences,” said Alois Reitbauer, chief technology strategist at Dynatrace.

“This shift introduces new challenges for observability, as organizations must ensure their AI-driven systems are transparent, reliable, and scalable.

“Observability becomes the critical foundation, providing the shared intelligence needed to navigate these challenges, make smarter decisions, and drive safe, efficient automation at scale.”

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The report also found that more than 50% of business leaders see automated real-time observability solutions to enhance customer experience within the next year.

Nearly half (46%) of all business leaders anticipate the greatest ROI of AI-powered observability will come from optimising AI model configurations.

By 2030, 50% of business leaders expect to have adopted AI-powered data encryption, risk assessments, and threat detection capabilities.

Seven in ten (70%) of those surveyed say observability budgets have increased in the past year, and three-quarters (75%) expect budgets to increase in the next fiscal year.

“Observability is shifting from reporting telemetry about application health to informing the decisions that run the business,” said Alois Reitbauer, chief technology strategist at Dynatrace.

“As more of those decisions are supported by AI, observability becomes the key to unlocking the full potential of AI‑driven decision support, providing the trustworthy context, guardrails, and feedback loops leaders need to act with confidence at scale.”