Cyber officials in the U.S. and six other countries have issued joint guidance on Secure Integration of AI in Operational Technology (OT)for rolling out AI tools in industrial settings, such as factories and critical infrastructure.
In many industrial and manufacturing sectors, security tools have historically been set up and left to run for years or even decades without upgrades. This approach is infeasible moving forward due to the advent of AI in adversarial tactics and techniques. The guidance highlights the importance of governance, model assurance, data integrity, continuous monitoring, and incident response in I/OT environments when integrating AI. One basic recommendation is to consider factors such as security risk, performance, complexity and cost, and whether the organization truly has the capacity to continually assess cyber risks as AI tools evolve.
Now let’s dive deeper into CISA’s guidance.
I/OT environments are adopting AI faster than they’re securing it. CISA’s new joint guidance on “Secure Integration of Artificial Intelligence in Operational Technology” makes one point painfully clear: AI doesn’t reduce cyber risk in I/OT; it magnifies it. Unless you have disciplined governance, validated data pipelines, secure model operations, and continuous monitoring wrapped around every integration, your I/OT security poses significant risk. In reality, most organizations are nowhere near ready for the risk.
At CyberMSI, this is exactly where we differentiate.
1. AI + I/OT Threat Detection That Actually Works:
AI in I/OT introduces new attack surfaces through model poisoning, data integrity compromises, manipulation of inference pipelines, and list goes on. Our MDR is built on behavioral analytics that don’t rely solely on AI models. We baseline I/OT behaviors, correlate across Microsoft Defender XDR and Sentinel telemetry, and detect manipulation patterns long before an AI-driven I/OT system responds in unsafe ways.
2. Visibility Across the Entire AI/OT Stack:
CISA stresses the need for lifecycle governance of models and the data feeding them. Most SOCs can’t see inside these workflows. Ours can. We ingest and monitor signals across:
- I/OT assets and ICS protocols
- Data ingestion points used by AI models
- Model hosts (cloud, edge, or hybrid)
- Identity pathways that can be exploited to manipulate AI-driven automation Total stack visibility is non-negotiable. We deliver it.
3. Hardening AI Workloads the Same Way We Harden Critical I/OT:
I/OT systems demand deterministic security controls. AI systems demand guardrails against unpredictable model behavior. We apply configuration benchmarking, access control validation, and attack-path analysis directly to AI-assisted OT workloads, which are aligned with CISA’s principles for secure model deployment.
4. Real-Time Containment When AI Systems Misbehave:
When AI interacts with physical processes, response speed is everything. Our agent+analyst MDR model cuts off malicious actions to identity abuse, unauthorized model changes, poisoned data flows—all in under 30 seconds. Automation plus human analysis and response ensures no AI-driven I/OT action turns into a safety or reliability incident.
5. Guidance That Doesn’t Hide Behind Buzzwords:
CISA’s document is clear about the need for practical, measurable controls. Same with us. We translate AI and I/OT security into concrete configuration posture, validated telemetry, and enforceable response actions.
If you’re integrating AI into I/OT, you don’t need dashboards. You need a partner who can actually secure the stack.
CyberMSI’s MDR services close that gap with 24/7 monitoring, advanced detection, and agent+analyst responses. Let’s show you how we cut off #cyberattacks in less than 30 seconds before these wreak havoc.