Securing IT-OT Convergence: A Benchmark Analysis of Zero Trust, AI, and NIS2 Compliance

Executive Summary

The convergence of IT (Information Technology) and OT (Operational Technology) is reshaping critical industries such as manufacturing, energy, transportation, and infrastructure. While this integration enhances operational efficiency, it also exposes industrial environments to new cyber threats originally confined to IT networks.

The NIS2 Directive, Zero Trust Architecture (ZTA), and AI-driven security solutions are now at the forefront of securing IT-OT environments. However, AI's non-deterministic nature and the unique real-time constraints of OT introduce new challenges that must be addressed strategically.

Key Insights

• Major IT-OT Cybersecurity Risks
• NIS2 Compliance and its Impact
• Zero Trust and AI in IT-OT Security

Key Takeaway

Organizations must adopt a multi-layered security approach, combining Zero Trust segmentation, AI-enhanced monitoring, and PLM-driven risk management to ensure NIS2 compliance and IT-OT resilience.

Companies that integrate these frameworks effectively will not only improve cybersecurity but also achieve regulatory alignment, operational safety, and long-term business continuity in an evolving digital threat landscape.

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Why IT-OT Security is a Critical Challenge in 2025

The convergence of IT (Information Technology) and OT (Operational Technology) is reshaping industries—manufacturing, energy, transportation, and critical infrastructure—but it is also exposing them to new cyber risks.

Key concerns:

• Ransomware and nation-state attacks targeting industrial control systems (ICS).
• Supply chain vulnerabilities and remote access risks in OT environments.
• Unpatched OT assets operating on legacy, insecure networks.
• The unpredictability of AI-driven security, which conflicts with real-time OT safety.

To counter these threats, organizations must align their IT-OT cybersecurity strategy with Zero Trust Architecture (ZTA), AI-enhanced monitoring, and the EU’s NIS2 Directive.

This benchmark analysis explores:

• Top IT-OT security weaknesses and real-world cyberattacks.
• How NIS2 compliance mandates are shaping industrial cybersecurity.
• Zero Trust and AI’s role in mitigating OT cyber risks.
• Industry-leading solutions (Dragos, Siemens, PTC, Dassault Systèmes) and their effectiveness.
• Actionable recommendations for security leaders.

1. IT-OT Security Weaknesses and Real-World Cyberattacks

IT-OT convergence brings efficiency but also expands the attack surface. Here is how major security gaps have led to real-world cyber incidents:

• Lack of IT-OT Network Segmentation
• Weak Remote Access and Supply Chain Risks
• Legacy OT Vulnerabilities and Unpatched Systems
• Lack of Visibility on OT Assets

Key Insight: Industrial cyberattacks often succeed because IT-OT networks remain flat, OT assets are invisible, and legacy systems lack updates.

2. Benchmarking Industry Solutions: How They Address NIS2 Compliance

This section evaluates leading cybersecurity solutions based on how well they align with NIS2 compliance and IT-OT security needs.

Dragos: The Leading OT Cybersecurity Platform

How Dragos Supports NIS2 Compliance:

• Real-time OT Threat Detection (ICS-IDS) aligns with NIS2’s cyber risk monitoring requirement.
• Threat Intelligence Feeds ensure compliance with Article 21 risk assessments.
• Passive OT Asset Discovery meets NIS2’s mandatory asset inventory rules.

Limitations:

• Needs Zero Trust enforcement to prevent initial breaches.
• Lacks direct integration with OT asset management (PLM systems).

Siemens, PTC, and Dassault Systèmes PLM for NIS2 Compliance

How PLM Tools Address NIS2:

• Centralized OT Asset Inventory ensures compliance with NIS2’s asset risk management rules.
• Supply Chain Security Integration enforces vendor compliance tracking.

Limitations:

• PLM solutions do not provide real-time cybersecurity monitoring.
• Must be integrated with Zero Trust and Dragos detection tools for active threat mitigation.

3. The AI Debate: Can AI Help or Hinder NIS2 Compliance?

AI has both potential benefits and risks in securing IT-OT environments.

Where AI Supports NIS2 Compliance:

• AI-based anomaly detection (Dragos, Nozomi) enhances risk monitoring.
• Predictive maintenance (Siemens, Dassault) reduces cyber-physical risks.

Where AI Fails to Meet NIS2 Compliance:

• AI introduces unpredictability—NIS2 compliance requires deterministic security controls.
• False positives in OT anomaly detection can disrupt industrial operations.

Solution: AI should be used for monitoring and insights, but Zero Trust should handle security enforcement.

4. References

• European Union Agency for Cybersecurity (ENISA). (2023). NIS2 Directive: Strengthening Europe’s Cyber Resilience. https://www.enisa.europa.eu
• Dragos Inc. (2023). ICS/OT Cybersecurity Threat Report 2023. https://www.dragos.com
• MITRE ATT&CK for ICS. (2023). Industrial Control Systems Threat Matrix. https://attack.mitre.org/matrices/ics/
• Siemens AG. (2023). Industrial Security: Protecting Critical Infrastructure. https://www.siemens.com
• Symantec. (2018). Triton: The First ICS Cyberattack Targeting Safety Systems. https://www.broadcom.com
• Zetter, K. (2014). Countdown to Zero Day: Stuxnet and the Launch of the World's First Digital Weapon. Crown Publishing.

5. Glossary

• ICS (Industrial Control Systems): Automated control systems used in industrial operations (e.g., SCADA, PLCs).
• MITRE ATT&CK for ICS: A cybersecurity framework mapping cyberattack tactics and techniques against industrial control systems.
• Zero Trust Architecture (ZTA): Security model that eliminates implicit trust and enforces strict access controls.
• NIS2 Directive: EU cybersecurity regulation for essential and important entities, enforcing stronger security requirements.
• PLM (Product Lifecycle Management): Software for managing the lifecycle of industrial assets, integrating cybersecurity.
• ZTNA (Zero Trust Network Access): Security framework that ensures only authenticated users can access resources dynamically.
• Time-Sensitive Networking (TSN): Technology ensuring deterministic, low-latency data transfer in OT environments.