The report surveyed 603 industrial security leaders across critical infrastructure sectors globally, finding that despite high self-assessed maturity levels (88%), only a minority (21%) have complete OT asset inventories. OT integration into centralized security operations and continuous monitoring of IoT devices are also insufficient. AI tools are commonly used for threat detection (72%), continuous monitoring (68%), and asset inventory (59%), but autonomous AI use is limited (23%). The report highlights the operational risks of AI automation without proper governance, stressing the importance of human oversight to avoid unintended consequences affecting uptime, equipment, or safety.

The disconnect between perceived OT security maturity and actual asset visibility and monitoring capabilities increases operational risks, including prolonged downtime and high financial losses following OT cybersecurity incidents. Incident rates vary by sector, with energy, utilities, and maritime sectors experiencing the highest incident frequencies. The limited use of autonomous AI means most AI deployments currently assist human analysts rather than independently respond to threats, reducing potential risks from premature automation but also limiting rapid autonomous response capabilities.

No specific vulnerability patch or fix applies. Organizations should prioritize completing OT asset inventories and enhancing integration of OT into centralized security operations centers. As AI adoption grows, clear decision rights, human oversight, and thorough testing of AI-driven responses are essential to prevent operational risks. Honeywell advises well-governed AI automation to strengthen visibility and response without compromising uptime, equipment, or safety.