How to Make Autonomous Industrial AI Safer
Industrial AI is moving beyond predictive analytics and other narrowly defined applications. Advances in foundation models, physical AI, and agentic AI are opening the door to systems that can take on more complex tasks across industrial environments. That progress also raises the stakes: unlike AI confined to digital settings, industrial AI can interact with physical equipment and processes, where mistakes may have real-world consequences. Building a safer path to autonomy means addressing the risks that come with giving AI a greater role in industrial operations. As companies explore more capable systems, safety must remain central to how these technologies are developed and deployed. The challenge is not simply to automate more, but to do so in ways that account for the physical environments AI operates in and help ensure that increased autonomy does not come at the expense of reliability.