Survey Finds Most Organizations Are Not Ready for Autonomous IT

Organizations are rapidly embracing agentic AI as the next phase of enterprise automation. Business leaders see AI-powered operations as a strategic priority and expect autonomous IT environments to become increasingly important over the next several years.

According to The State of Autonomous IT Operations survey, most companies remain far from that goal. Only a small percentage of IT operations are currently automated, enterprise-wide AI deployments remain rare, and many organizations lack the data quality, observability, and infrastructure needed to support autonomous decision-making.

Security and trust concerns remain major adoption barriers

This gap between ambition and readiness creates significant operational risks. Many organizations are reluctant to allow AI systems to make decisions without human approval, citing concerns around security, compliance, operational disruptions, and inaccurate outcomes. Moreover, technical teams also struggle with fragmented monitoring tools and incomplete visibility across networks, endpoints, cloud services, and AI workloads. Without reliable oversight, organizations risk deploying autonomous systems they cannot fully monitor, govern, or trust.

Additionally, a lack of visibility into AI performance and costs could create governance challenges as AI agents gain access to business-critical processes. This survey suggests that executive enthusiasm for agentic AI may outpace the operational realities faced by IT teams responsible for deploying and managing these technologies.

Data, observability, and governance are key success factors

This report argues that organizations should focus on three foundational capabilities before pursuing large-scale autonomous IT operations. First, enterprises need high-quality, real-time data that AI systems can trust for operational decisions. They should also invest in unified observability platforms that provide visibility across the entire technology stack. It’s also recommended to reduce tool sprawl and integrate disconnected systems to improve efficiency while giving AI platforms access to more complete operational data.

This study also highlights the growing importance of AI observability and governance. Continuous monitoring, policy controls, cost management, and oversight of AI agents will likely become essential requirements as organizations expand their use of autonomous technologies.

Agentic AI promises faster operations, improved productivity, better system reliability, and reduced manual effort. However, keep in mind that organizations may need to invest heavily in data modernization, governance frameworks, observability tools, and operational controls before they can safely increase AI autonomy.

Overall, enterprises seeking the efficiency gains of autonomous IT cannot simply deploy more AI. They must first establish the visibility, governance, and trust mechanisms needed to ensure autonomous systems operate safely and predictably. The companies that balance automation with strong oversight are likely to be best positioned to realize the long-term value of agentic AI.