A curated collection of research, papers, and published resources organized across 11 categories, 20 RBPS elements, and every major AI discipline.
As interest in artificial intelligence (AI) accelerates across safety-critical industries, organizations face a growing challenge: distinguishing meaningful, process safety–relevant applications from general-purpose automation and hype.
psm.ai addresses this gap by organizing research and insights across the elements of CCPS Risk-Based Process Safety (RBPS), providing a structured, vendor-neutral view of how AI is being applied—while progressively expanding coverage across all 20 RBPS elements as relevant research and practical applications emerge.
Explore how AI is being applied in process safety disciplines →
With the recent concern about AI agents “going rogue”, we thought it would be useful to look at current research on AI Agents as they relate to process safety.
The first paper attempts to “measure the safety” of AI agents–a likely precursor to declaring something safe or not.
The paper by Gong et al. proposes a risk taxonomy to assessing agents in industrial usage.
And, finally, the paper by Devarajan et al. covers a comprehensive review of the use of Machine Learning for leak detection, predictive maintenence and other plant applications.