palletcentral

Pallet C e nt ral • Ma rch -Ap r il 2 0 26 4 3 Following up on Keeling's emphasis on using technology to enhance safety, the House Education & Workforce Committee has held a series of hearings on using Artificial Intelligence (AI) to enhance workplace safety. At a hearing on February 11, 2026, the House Workforce Protections subcommittee examined how AI and other advanced technologies are improving efforts to keep America's workers safe and healthy. is was the third hearing in a series on the subject. Witnesses included former OSHA Chief Doug Parker, and representatives from the National Association of Wholesalers and Distributors (NAWD) and construction trades. e NAWD representative specifically discussed "disembodied AI," which refers to technology that perceives, analyzes, or generates insights about its environment without directly controlling physical actions or machinery. is technology can be used to observe work environments and make operations-related suggestions. Most notably, wholesalers and distributors are deploying disembodied AI through computer vision technologies. Computer vision is a technology that integrates both cameras and AI models to observe warehouse operations in real time. In many cases, computer vision capabilities can be built upon existing cameras or closed-circuit systems within a location. Another use of AI technology in warehousing/logistics application involves "predictive AI." is approach uses data to detect risk patterns that are not visible in real time. For example, predictive AI may be used to predict equipment failures (e.g. forklift, conveyor belt, etc.) before a potential breakdown creates a disruption or hazard. The most common application of predictive AI for warehouse equipment is the use of digital twins, or virtual replicas of actual warehouse operations and equipment. A digital twin is created by integrating sensors placed on warehouse equipment with software that continuously monitors performance. Over time, the system learns what normal, safe equipment operation looks like. is enables predictive AI tools to identify irregularities that may signal mechanical wear, malfunction, or safety risk. As discussed in my previous article on this topic, AI technology can provide a multitude of worker safeguards including, but not limited to, the detection of near misses between workers and warehouse equipment such as forklifts, identification of missing Personal Protective Equipment (PPE), recognition of unsafe conditions or behaviors, and the creation of visual tools (i.e., heat maps) highlighting high- risk zones within facilities. AI-powered safety tools move safety management from a reactive, incident-based approach to a preventive, data-driven model. Wearable sensors on personal protective equipment can monitor hazards—like heat stress and exposure to hazardous materials—and alert workers before conditions become dangerous. Predictive analytics can forecast where accidents are most likely to occur, catching hazards before those hazards lead to accidents rather than afterwards. e impact could be immense. Fewer injuries mean healthier workers, increased worker recruitment and retention, lower costs, and stronger business operations, all while ensuring America's workers receive the highest standard of safety on the job. However, witnesses warned Congress that employers should take the necessary steps to understand best practices and proper implementation. ese tools can be invaluable for augmenting worker safety, but there must be space for human oversight, and employers should be wary of delegating ultimate

• Cover