Operational technology environments—power grids, manufacturing systems, HVAC networks—were built without the assumption that autonomous AI agents would need to interact with them. As enterprises increasingly deploy AI for predictive maintenance, anomaly detection, and optimization in OT networks, the gap between IT-style machine identity governance and OT-specific security requirements is becoming a critical risk.
Traditional OT security was built on air-gap principles and implicit trust. If a device was on the network, it was trusted. Authentication was minimal because physical access to the network itself was considered a sufficient control. This model is incompatible with AI agents that need programmatic, rapid access to sensor data, control systems, and operational parameters.
The challenge of agentic identity in OT is compounded by three unique constraints. First, OT devices have limited compute resources and cannot perform complex cryptographic operations. A PKI-based identity system must be lightweight. Second, OT networks often have stricter latency requirements—an authentication protocol that adds 500ms of delay can disrupt real-time control systems. Third, OT systems may operate for 15-20 years without updates, making it impossible to deploy modern IAM solutions across the infrastructure.
Corsha and similar vendors are addressing this gap by creating identity solutions specifically designed for OT contexts: lightweight certificate-based authentication, zero-latency integration with legacy PLC and SCADA systems, and identity verification that works within OT’s operational constraints.
The key insight is that machine identity in OT is not a problem to be solved by lifting IT best practices wholesale. OT-specific identity systems must understand the domain: they must recognize which identities are expected to communicate with which devices, flag anomalous patterns specific to industrial processes, and enforce access controls without introducing the latency penalties that could impact critical operations.
As AI increasingly manages OT environments—from predictive maintenance agents to autonomous optimization systems—enterprises cannot afford to delay implementation of machine identity governance. The risk of compromised agents with implicit OT access is too high.
Source: TipRanks