Now that we have a basic understanding of datasets and open and closed AI (see article published August 06, 2025, on the RJR Safety Inc website) , let’s look at how AI is transforming occupational safety. Safety professionals tasked with protecting workers, ensuring compliance, and fostering a culture of safety, are increasingly turning to AI to enhance their capabilities. From predictive analytics to real-time hazard detection, AI offers a suite of tools that can change how safety is managed across various sectors. AI can be used by safety professionals to perform their duties more efficiently, proactively, and intelligently.
One of the most impactful uses of AI in safety is predictive analytics. By analyzing historical data, AI algorithms can identify patterns and forecast potential risks before they materialize. Safety professionals can use these insights to pinpoint high-risk areas or activities, forecast the likelihood of specific incidents based on environmental or behavioral factors, and prioritize inspections and interventions. For example, AI models trained on past incident reports and environmental data can predict when and where specific incidents are most likely to occur, which then allows safety professionals to implement targeted preventive measures before incidents happen.
AI-powered sensors and Internet of Things (IoT) devices enable real-time monitoring of workplace conditions. These systems can detect anomalies such as excessive heat or toxic gas levels, unsafe machine operation, and/or unauthorized access to restricted areas. AI algorithms process this data instantly and can trigger alerts to safety professionals or production personnel or automatically shut down equipment to prevent harm. In manufacturing plants, for example, AI can monitor vibration patterns in machinery to detect early signs of malfunction, reducing the risk of mechanical failure and the potential for injury.
Computer vision, which is a part of AI, uses cameras and image recognition to identify unsafe behaviors or conditions. Safety professionals can deploy computer vision systems to monitor workers for compliance with personal protective equipment use requirements, detect unsafe practices, such as improper lifting techniques or distracted driving, or identify hazards like spills, obstructions, or fire risks. These systems can operate continuously and provide objective, consistent assessments. An example would be in construction, drones equipped with AI-powered cameras can scan sites for unsafe conditions or potentially hazardous conditions, reducing the need for manual inspections and improving coverage.
Natural Language Processing (NLP) enables AI to understand and process human language and writing styles. Safety professionals can use NLP tools to analyze incident reports for trends and root causes, automate the categorization and prioritization of safety issues, or translate safety documentation into multiple languages for diverse workforces. AI can also assist in creating more accurate and comprehensive reports by prompting users for missing information or suggesting relevant details based on previous entries. This improves the quality of data available for analysis and decision-making.
AI-driven virtual reality (VR) and augmented reality (AR) platforms offer immersive training experiences for workers. Safety professionals can use these tools to simulate hazardous scenarios in a controlled environment, teach proper responses to emergencies like fires, chemical spills, or equipment failures, or assess worker readiness and identify areas for improvement. These simulations are more engaging and effective than traditional classroom training, and they allow for safe practice of high-risk procedures. AI can personalize training based on individual performance.
Regulatory compliance is a critical aspect of occupational safety. AI can streamline compliance tasks by automatically updating safety protocols, procedures, and policies based on new regulations, generating audit-ready documentation, and tracking training completion and certification status. AI systems can also cross-reference multiple data sources to ensure that safety procedures align with legal requirements. This reduces the administrative burden on safety professionals and minimizes the risk of non-compliance.
AI can analyze behavioral data to assess the safety culture within an organization. By examining factors such as frequency and nature of safety violations, employee engagement with safety programs, and feedback from safety surveys. Safety professionals can gain insights into organizational attitudes toward safety. AI can identify departments or teams that may need additional support or training, helping to foster a proactive and positive safety culture.
AI tools can evaluate workplace ergonomics by analyzing posture, movement, and workstation design. Safety professionals can use these insights to reduce musculoskeletal disorders, optimize workstation layouts, and recommend ergonomic interventions. Wearable devices and computer vision systems can monitor workers in real time, providing feedback on posture and movement. This helps prevent injuries and improves overall worker well-being.
After an incident occurs, AI can assist in the investigation process by aggregating and analyzing data from multiple sources (e.g., video footage, sensor data, reports), identifying contributing factors and root causes, and suggesting corrective actions based on similar past incidents. This accelerates the investigation process and improves accuracy, enabling safety professionals to implement effective preventive measures.
AI-powered platforms can facilitate communication among safety teams, management, and workers. Some ways that AI can facilitate communication include chatbots that answer safety-related questions, automated reminders for safety meetings or inspections, and collaborative dashboards that visualize safety metrics. These tools ensure that safety information is accessible and actionable, promoting transparency and accountability across the organization.
While AI offers numerous benefits, safety professionals must also consider potential challenges. Data privacy and security is one consideration. The monitoring systems must protect worker privacy and comply with data protection laws. We must ensure that AI models we use must be trained on trusted and diverse data to avoid biased outcomes. To get successful implementation, it requires buy-in from stakeholders and integration with existing systems. Safety professionals must work closely with IT and legal teams to address these concerns and ensure ethical AI use.
Artificial Intelligence (AI) is rapidly changing the field of occupational safety. By enabling predictive analytics, real-time monitoring, automated reporting, and immersive training, AI empowers safety professionals to be more proactive, efficient, and effective. As AI technologies continue to evolve, their integration into safety practices will become increasingly essential.
Part 3 of this series of articles will review, basically, some AI programs that I have become acquainted with. Part 3 will be published in early September.
As I stated in part 1, as the author, I now that this is by no means an exhaustive explanation of AI and its use in occupational safety, actually it is a very basic summary. I plan to continue to learn, experiment with, and use AI as I see and understand the uses. This is just the beginning of my journey to better understand how artificial intelligence (AI) is being used and can be used by Safety Professionals. I am learning that as safety professionals responsibly embrace AI, understanding its many uses will improve workplace safety.
For more information and/or assistance, contact:
Wayne Vanderhoof CSP, CIT
Sr. Consultant/President
RJR Safety Inc.