Cyberattacks targeting OT environments have surged sharply. Recent data shows that 73% of organizations reported intrusions affecting OT systems in 2024, up from 49% just a year before. What’s more concerning is the rise of AI-enhanced attacks—threats that leverage automation and machine learning to carry out operations faster and on a larger scale. These AI-powered attacks now cut the time needed to deploy sophisticated ransomware from hours down to mere minutes.
Traditional cybersecurity strategies are struggling to keep up, especially given the unique challenges OT environments face—outdated equipment, limited patching options, and the need to avoid operational downtime at all costs. Against this backdrop, AI-driven threat detection has become a crucial pillar of modern OT security.
AI’s Role in Enhancing OT Security
Efficiency Gains Through AI
- Reduced Alert Fatigue: AI filters out false alarms and focuses attention on genuine threats. For example, Siemens Energy reported a 40% drop in false alerts after deploying AI-based detection.
- Faster Threat Detection: In mature environments, AI has cut average breach detection times from over 200 days to under 40, giving teams a crucial time advantage.
- Augmented Human Expertise: Automating routine investigations and triage lets security staff focus on strategic tasks. Some manufacturing clients have seen a 25% reduction in incident management time after introducing AI tools.
What Leading Enterprises Are Doing
Across industries like manufacturing, energy, utilities, and logistics, organizations are quietly but steadily adopting AI-driven OT security solutions. Drawing from both our client work and wider industry observations, here’s how AI is being used effectively to secure OT environments in critical sectors:
- At a major European logistics hub, an AI system correlates data from OT equipment—such as crane controllers and fuel systems—with IT security signals. This enables the security team to significantly reduce investigation times and proactively block credential misuse attempts before they escalate into operational disruptions.
- A large utility provider in the Middle East uses passive network monitoring powered by AI to safeguard legacy SCADA systems that cannot be patched. We’ve supported a similar client in deploying this approach, achieving near real-time threat detection across hundreds of substations while keeping systems online.
- In North America, one manufacturer’s AI-driven analytics flagged an unusual pattern in robotic arm movements—not as a mechanical error, but a possible cyber manipulation. Several of our manufacturing clients have since adopted similar AI capabilities to deepen their visibility and response.
- Organizations operating under European NIS2 and GCC’s NCA and NDMO frameworks are increasingly turning to AI not only to enhance security but also to meet regulatory expectations and lower cyber insurance costs.
The Path Forward
But putting AI to work in OT isn’t just about adopting new technology. It’s about knowing where it fits, how it behaves around legacy systems, and what risks actually matter on the plant floor or control room.
That’s where Utthunga’s cybersecurity solutions make a real difference. Working with leading industrial clients, we deliver AI-powered threat detection capabilities built specifically for complex OT environments. From passive monitoring of legacy systems to intelligent threat correlation across IT and OT, our cybersecurity solutions are helping organizations stay a step ahead of threats while keeping operations secure and resilient.