AI and Process Safety: How Schneider Electric is Pioneering the Future

AI and Process Safety: How Schneider Electric is Pioneering the Future

Artificial Intelligence (AI) is making its way into the world of process safety, revolutionizing how industries approach hazard analysis, risk mitigation, and operational efficiency. Chris Stogner, Senior Director of Offer Management at Schneider Electric, shares insights on how AI reshapes safety lifecycle management and why the industry must embrace these advancements.

A New Era for Process Safety with AI

Schneider Electric has secured a patent for a groundbreaking approach that applies AI-driven reinforcement learning to process safety. While there is no commercial product yet, this innovation has the potential to automate hazard analysis, enhance safety studies, and streamline compliance with global standards.

According to Chris Stogner, AI can significantly improve the efficiency and accuracy of hazard and operability (HAZOP) studies. Traditionally, these safety assessments require teams of highly skilled experts who often introduce biases based on past experiences. AI eliminates this issue by providing an objective, data-driven analysis that continuously improves through reinforcement learning models.

How AI Works in Process Safety

The methodology which has been patented is a reinforced learning model with two AI agents—one designed to identify potential failures and another to prevent them. After running numerous iterations, the system identifies all possible risks and outlines protective measures, ensuring more thorough and standardized safety assessments.

Key benefits include:
– Objective hazard identification – AI eliminates human bias from safety assessments.
– Continuous learning – Reinforcement learning adapts over time, improving accuracy.
– Enhanced operational efficiency – Automating safety assessments saves time and resources.

Bridging the Skills Gap with Automation

One of the biggest challenges facing the energy and industrial sectors is the shrinking workforce of experienced safety professionals. As veteran engineers retire, companies struggle to find replacements with the same depth of expertise. AI-driven safety solutions can capture institutional knowledge and ensure process continuity, allowing businesses to maintain high safety standards despite workforce shifts.

Expanding Beyond Traditional Industries

While chemical and oil & gas industries have relied on process safety for decades, new energy sectors like hydrogen and nuclear face unique challenges. Unlike established sectors, these industries lack decades of safety data and best practices. AI can fill this gap by offering scalable, adaptive solutions that enhance safety protocols from the start.

Furthermore, AI-driven safety solutions could extend to transportation, electrification, and infrastructure projects, ensuring that safety measures evolve alongside the rapid expansion of smart grids and electric vehicle networks.

The Road Ahead for AI in Process Safety

While AI is a game-changer, adoption challenges remain. Many industrial companies acknowledge the need for innovation but are hesitant to be early adopters. To build trust, Schneider Electric advocates for an approach where AI acts as a checkpoint rather than a full replacement for human oversight. Combining AI insights with expert validation, this hybrid model will help companies gradually transition to AI-driven safety practices.

As global safety standards evolve, AI will likely play a critical role in regulatory compliance. By automating safety lifecycle management, companies can reduce costs, enhance compliance, and improve risk mitigation strategies.