AI is moving from generating content to controlling physical machines.
Anthropic is developing a Model Hardware Standard that allows AI agents to discover and operate different types of equipment through a common interface. The research preview has been demonstrated with robotic arms, microscopes, liquid handlers and laser systems.
The technology could make it easier to connect AI systems to physical equipment without building separate integrations for every machine. That could accelerate the use of AI in laboratories, manufacturing and other environments where software needs to control physical processes.
Connecting an AI agent to a machine is only part of the problem. The agent also needs to establish which machine it is talking to.
An authorised AI system could send a legitimate instruction to the wrong device if that endpoint had been impersonated, replaced, cloned or compromised. In a digital environment, that could expose data or systems. In a physical environment, the consequences can extend to the equipment and processes being controlled. This puts machine identity alongside AI identity as a core security requirement.
AI security typically focuses on the agent. Organisations need to know which system is acting, what it can access and what it is authorised to do.
The question becomes even more important when AI operates in a continuous feedback loop. A machine produces information, the AI analyses it and the AI then decides what the machine should do next. If the original device cannot be trusted, the data it provides may not be trustworthy either. That creates a direct link between machine identity, data integrity and AI decision-making.
Device Authority’s technology addresses this area through hardware-rooted device identity. Its Dynamic Device Key Generation approach is designed to distinguish genuine devices from cloned or substituted equipment. That identity can then support authentication, authorisation and credential management.
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