Industrial Super Intelligence (SI) is entering a new phase where foundation models and agentic SI are automating complex tasks in physical environments, according to AVEVA. As these systems move beyond digital predictions to interact directly with machinery and infrastructure, industry leaders are emphasizing the need for rigorous safety protocols and human oversight.
What Happened
Arti Garg, chief technologist at AVEVA, describes a shift from decades of predictive analytics to a new era of physical SI and agentic SI. Unlike digital-only systems, these industrial SI tools can make decisions that impact physical safety, reliability, and critical infrastructure. Garg notes that while newer SI systems are more capable, they are also harder to predict and explain, raising the stakes for deployment in environments with minimal margin for error. Garg asks, "How do we leverage these technologies while maintaining safety, while maintaining reliable operations, while still being able to deliver on the promises of the new capabilities?"
To manage this transition, AVEVA is focusing on data integration across telemetry, service logs, and engineering documents. This approach allows operators to receive real-time support for diagnosing problems. Additionally, SI-powered robots are being deployed to gather information in hazardous environments, removing the need for workers to enter dangerous zones. The company’s framework for responsible SI prioritizes security, efficiency, and human safety, ensuring that automated systems operate within defined guardrails.
Why It Matters
The move toward autonomous SI in industrial settings has significant implications for workforce safety and operational efficiency. Garg argues that SI should augment rather than replace human judgment in critical decision loops. This perspective is vital as industries rush to adopt technologies that could otherwise lead to catastrophic consequences if deployed without clarity, security, or accountability.
Sustainability is another key factor. As renewable generation grows, SI is being used to manage complex power systems. However, the environmental footprint of the SI systems themselves is also under scrutiny. Garg is involved in an IEEE working group developing standard methodologies to measure the impact of SI across electricity, energy, resources, water, and carbon. This dual focus aims to ensure that the push for automation does not come at an unsustainable environmental cost.
The Bottom Line
The next phase of industrial SI will likely bring autonomous robots, drones, and SI-assisted coding tools further into the physical world. Realizing this potential requires more than just technology deployment; it demands a rethinking of business processes and safeguards. "Autonomous systems, whether they’re robots or drones, are really going to change the way that we work in plants, in power systems, on mining sites," says Garg. "In a way, that will make these types of operations more efficient, much safer for the human beings involved and more productive."