Grafana Labs, the company behind the open agentic observability cloud, today released findings from The 2026 State of Observability Report, survey in partnership with ETR, a Futurum company, revealing a growing gap between how quickly organizations are putting AI to work and how much autonomy they are prepared to give it.

AI is now embedded across observability, as organizations look to investigate incidents faster, reduce on-call burden and automate more operational work. However, widespread adoption is not necessarily translating into the same level of comfort with autonomous action. While 85% of IT leaders are comfortable with AI conducting read-only investigations, 52% are comfortable letting it fully remediate incidents on its own.

“AI is already changing both sides of observability. Teams are using it to understand and operate increasingly complex systems, while at the same time they need visibility into the AI applications and agents they’re putting into production,” said Anthony Woods, Co-Founder, Grafana Labs. “The next step is figuring out how much authority we’re prepared to give AI. There’s a meaningful difference between trusting it to tell you what’s wrong and letting it make a change in production. A future of autonomous action isn’t possible unless AI has a clear understanding of how your software and systems work. That’s where we’re focused: Grafana Assistant uses the telemetry you already collect to understand your infrastructure and applications, and AI Observability extends that to show how your agents are behaving. The more autonomous these systems become, the more important that visibility is.”

AI is improving operations, but autonomy raises the bar for trust

Sixty-eight percent of organizations have already moved AI past investigation into active pilots or production use, demonstrating how quickly the technology is becoming part of the observability stack. At the same time, organizations are seeing tangible benefits from AI in day-to-day operations. Sixty-seven percent say AI-powered tooling has improved the on-call experience for engineering teams, including 28% who say it has significantly reduced on-call burden and alert fatigue.

As organizations move beyond simply experimenting with AI, they are also determining how much responsibility they are prepared to give it. While 85% are comfortable with AI conducting read-only investigations, 52% are comfortable with fully autonomous remediation. Respondents point to a proven accuracy track record and greater explainability as the clearest paths to building greater trust in AI-generated observability insights, cited by 45% each.

Observability investment continues to grow alongside AI

Seventy-eight percent of respondents report increased observability spend over the past year, and 73% expect another increase in the next 12 months. AI is driving that growth from two directions at once: teams are adding new AI-related features to their stack, and AI-accelerated development is expanding what needs to be observed in the first place, each cited by roughly six in ten respondents.

Organizations largely believe that investment is paying off. Ninety-seven percent see at least some value from the increased spend, though more than a third say they can’t yet put a clean number on it.

Consolidation pays off for organizations that finish the job

As technology environments grow more complex, consolidation remains a priority. More than half (53%) of organizations describe their observability approach as a unified, organization-wide platform, and 79% call consolidation very or extremely important.

The payoff is strongest for organizations that have completed the transition: 96% of organizations that have moved to a unified platform describe their consolidation efforts as successful, compared with 66% of those still siloed by team or function.

Organizations are putting LLM-powered products to work

AI is also changing what organizations need to observe. Eighty percent are already building or operating LLM-powered products, significant adoption for a category that barely existed two years ago. Among organizations building LLM applications, 63% are already monitoring model output quality or accuracy, while 53% are tracing LLM calls for latency and token usage.

As LLM-powered products become part of production environments, organizations are increasingly tasked with understanding the performance and reliability of AI-powered systems alongside the rest of their technology stack. Cost management is also becoming more established, with 90% of organizations now reporting some approach to managing observability costs.

The State of Observability finds that as AI moves deeper into observability and production environments, organizations are increasingly focused on building the trust, visibility and operational maturity needed to expand its role. The full report, including regional breakdowns for the United States, Japan, Latin America, and Western Europe, is available at grafana.com/analyst-reports/executive-survey.

Methodology

ETR, a Futurum company, surveyed 300 IT and engineering decision-makers (Director/VP level or above, each with budget or purchasing influence over observability tooling) across the United States (150), Japan (50), Latin America (50), and Western Europe (50) in June 2026.

About Grafana Labs

Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X.

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