Honeywell: 99% expect AI to shape OT cybersecurity in next 2-3 years

US News 22 September 2026 17:11 (UTC +04:00)
Honeywell: 99% expect AI to shape OT cybersecurity in next 2-3 years
Laman Zeynalova
Laman Zeynalova
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BAKU, Azerbaijan, September 22. AI-enabled capabilities are already widely used in operational technology (OT) security, although fully autonomous applications remain relatively uncommon, according to Honeywell Technologies’ 2026 OT Cybersecurity Benchmark Report.

“AI-enabled threat detection leads at 72%, followed by continuous monitoring at 68% and asset inventory at 59%,” the report said.

At the same time, most AI capabilities continue to assist human analysts rather than operate independently. “In total, 23% report autonomous or agentic operation for threat detection, and 23% also report it for continuous monitoring,” according to the report.

Separately, 19% of respondents reported autonomous or agentic operation for asset inventory.

The report said the level of autonomy is an important indicator of OT security maturity, particularly in terms of “how much authority AI systems are given, how their actions are governed and whether operators can trust them in live production environments.”

Asset inventory provides a further indication of the current level of AI maturity in OT security. Among organizations reporting strong asset visibility, 22% said they use autonomous inventory capabilities, compared with 8% among organizations with weak visibility.

The report noted that the data does not establish whether AI improves asset visibility or whether organizations with stronger foundations are simply better positioned to adopt advanced automation. However, it shows an association between stronger asset visibility and greater use of autonomous AI capabilities.

“99% of respondents expect AI to affect OT security within the next two to three years,” Honeywell said.

The company added that as AI develops from assisting analysts toward taking action, organizations will require clear decision rights, human oversight and testing that accounts for the operational consequences of incorrect responses.

“The goal of well-governed AI automation is to strengthen visibility and response without creating new risks to uptime, equipment or safety,” the report said.

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