Building a safer path to autonomous industrial AI

Industrial AI is entering a new phase driven by advances in foundation models, physical AI, and agentic AI.

Foundation models are large AI systems trained on vast amounts of data that can perform a wide range of tasks, while physical AI refers to AI systems designed to interact with real-world machinery and equipment.

Agentic AI systems can make decisions and take actions autonomously.

Unlike digital-only AI, industrial AI interacts directly with physical systems, such as factory equipment or power grids, where mistakes can have serious safety or economic consequences.

According to AVEVA’s chief technologist Arti Garg, the challenge is balancing these new capabilities with safety, reliability, and human oversight.

The adoption of industrial AI has accelerated rapidly, with a reported 78% increase over the past two years, reflecting growing confidence in its potential despite its risks.