Key Takeaways:
- The convergence of IT and OT systems, as well as the integration of AI in OT, are creating new and complex cyber attack surfaces that legacy OT security models were not designed to handle.
- The shift to hybrid (central-decentral) security architectures, the rise of zero trust microsegmentation, and the enduring criticality of firewalls in IT/OT convergence are key trends shaping OT cybersecurity.
- AI is becoming a core component in OT security workflows, helping to streamline OT anomaly detection and response.
- The new focus on securing AI workloads in OT is emerging, requiring model-level security controls to protect AI models, their training data, and autonomous actions.
- Regulatory drivers such as Europe’s Network and Information Security 2 (NIS2) Directive and Cyber Resilience Act are compelling organizations to elevate cybersecurity maturity from an operational task to a board-level priority.
Introduction to OT Cybersecurity
The increasing importance of OT cybersecurity is a pressing concern, as industrial executives cite AI and IT/OT convergence as the most promising future developments. However, these technologies also create new and complex cyber attack surfaces that legacy OT security models were not designed to handle. IoT Analytics’ 49-page OT Cybersecurity Insights Report 2026 identifies several trends related to IT/OT convergence and AI integration affecting OT security. This article discusses five of these trends, which are crucial for cybersecurity vendors and enterprises to understand in order to remain competitive and assess their cyber posture.
The Importance of OT Cybersecurity
The convergence of IT and OT systems, as well as the integration of AI in OT, are creating new opportunities for efficiency and productivity. However, they also widen the cyber attack surface, making OT security a top cybersecurity topic. Cybersecurity companies are placing a specific focus on OT security, and technology giants like Microsoft are dedicating a portion of their security blog to IoT and OT security and threat intelligence. The increasing focus on OT security is driven by the growing number of cybersecurity regulations worldwide to mitigate cyber threats to data and national infrastructure.
Foundational Context: The Purdue Model
The Purdue Model is the long-standing architectural framework for industrial control systems (ICSs). The model segments the industrial network into distinct hierarchical levels, creating a logical separation between enterprise (IT) and operational (OT) functions. Understanding the Purdue Model is essential for grasping the context of OT cybersecurity and the trends shaping the industry. The model’s distinct levels, ranging from Level 0 (physical processes and the field) to Level 5 (internet-facing demilitarized zone), provide a framework for analyzing OT security.
5 Key Trends Shaping OT Cybersecurity
The five trends discussed in this article are: the shift to hybrid (central-decentral) security architectures, the rise of zero trust microsegmentation, the enduring criticality of firewalls in IT/OT convergence, AI’s growing role in OT security, and the new focus on securing AI workloads in OT. These trends represent a fundamental shift away from static, perimeter-based defenses and toward a more dynamic, intelligent, and layered security posture. Hybrid security designs are improving resilience and oversight, while zero trust microsegmentation is reducing legacy system risk. Firewalls remain a critical control layer, especially at the IT/OT convergence point, and AI is becoming a core component in OT security workflows.
The Future of OT Security
The future of OT security lies in hybrid architectures that balance central visibility with local resilience, enforce granular control through zero trust principles, and leverage AI to both defend the network and secure its own operational role. Regulatory drivers such as Europe’s Network and Information Security 2 (NIS2) Directive and Cyber Resilience Act are compelling organizations to elevate cybersecurity maturity from an operational task to a board-level priority. As OT has several messaging protocol layers below the standard Internet protocol layer of IT, vendors are working to extend OT security down to the serial and analog layers to capture relevant data for real-time security monitoring.
Conclusion
In conclusion, the convergence of IT and OT systems, as well as the integration of AI in OT, are creating new and complex cyber attack surfaces that legacy OT security models were not designed to handle. Understanding the trends shaping OT cybersecurity, including the shift to hybrid security architectures, the rise of zero trust microsegmentation, and the enduring criticality of firewalls, is crucial for cybersecurity vendors and enterprises to remain competitive and assess their cyber posture. The future of OT security lies in hybrid architectures that balance central visibility with local resilience, enforce granular control through zero trust principles, and leverage AI to both defend the network and secure its own operational role.
