AI Emerges as the GPS of Workplace Safety, Guiding Professionals Toward Smarter Risk Management
Just as GPS moved from skepticism to indispensability, AI is becoming an essential tool for EHS professionals—transforming hazard detection, incident analysis, and safety culture through real-time insights and smarter decision-making.
- By Greg Duncan
- Sep 29, 2025
Today, the Global Positioning System (GPS) is used by virtually everyone on earth and GPS technology is integral to an unimaginable number of systems that humans rely on in our daily lives. It’s hard to imagine life without GPS but if we look back to the 1970s when GPS technology first emerged, early users in the aerospace industry and military were highly skeptical. Believe it or not, those early users notably questioned the practicality, value, accuracy, reliability, and security of GPS systems. Similar concerns cropped up as civilian use of GPS for navigation and geolocation became widespread, with users hesitant to trust a digital co-pilot that “might be wrong.” Fast forward nearly 50 years, and while some of these concerns persist, GPS has become so deeply embedded in our lives that it’s nearly impossible to imagine travel, logistics, research, commerce, and any number of critical aspects of our society without it.
AI appears to be following a similar trajectory of adoption, especially within the field of workplace safety. For Environment, Health, and Safety (EHS) professionals, AI represents a transformative tool that, much like GPS, has the potential to fundamentally change how they navigate risk, control workplace hazards, and steer organizations toward safer outcomes. The question is not whether AI will become an indispensable safety management tool, but how that adoption will occur and how fast.
That’s why EHS professionals need to act now to understand how AI is currently being applied in the field of workplace safety and how it can help them work faster, smarter, and drive safer outcomes. Otherwise, EHS professionals are at risk of being left behind in this rapidly changing technology landscape.
Overcoming Fear: From Skepticism to Trust
The most common concerns we hear from EHS professionals around AI are analogous to those once held about GPS. They include fears about losing human control over critical safety decisions, about the “black box” nature of some AI models and exactly how AI systems generate important safety-related information and insights, the accuracy of data and calculations, especially when it comes to compliance reporting, and about the privacy and security of sensitive worker data. These concerns have one thing in common, they’re rooted in the concept of trust and where the safety of workers is concerned, that trust must be earned.
When GPS first emerged, users feared that trusting technology to make decisions about navigation could lead them astray. Yet over time, GPS proved highly reliable, efficient, accurate, and even a life saver when it came to search and rescue activities. AI in EHS is on a similar path. To accelerate adoption, AI providers must design models purpose-built for EHS use cases, embed human expertise, and establish safeguards that ensure people remain in command, particularly in life-and-death decisions. Doing so supports the trust necessary to drive adoption and reinforce a culture that embraces AI, rather than fears it.
AI as a Navigation Tool for Safety
You can think of AI as a navigation system for improving workplace safety. Just as modern GPS apps on your smartphone process data from millions of vehicles to update traffic conditions and guide drivers around hazards toward their destinations along the fastest route, AI can analyze massive volumes of incident reports, near misses, and hazard IDs to detect patterns invisible to the human eye, assimilate them into actionable insights for users, and direct EHS professionals toward safer decisions.
Where traditional EHS processes and management systems can struggle under the weight of data, AI thrives spotting emerging risks, flagging potential hazards, and recommending interventions in real-time. Like GPS, AI does not take the wheel; it offers a suggested course of action. The safety professional remains firmly behind the wheel, deciding which route to help follow. It’s important to reinforce this perspective of AI as a vigilant and untiring assistant that helps reduce uncertainty and accelerate preventive action, rather than an autonomous driver that replaces the decision making power and professional judgement of the EHS professional.
AI is Already at Work in EHS
While some EHS professionals may still view AI as something of the future, it’s already being deployed in ways that directly enhance safety. Predictive analytics, for instance, are being used to identify potential serious injury or fatality (PSIF) risks by analyzing near-misses and incident data, uncovering and targeting hazards before they escalate. In the field of ergonomics, AI-powered 3D motion capture is transforming musculoskeletal disorder (MSD) risk assessments, delivering highly accurate risk scoring and tailored control recommendations based on historical control effectiveness and embedded ergonomics expertise.
Incident management is another area where AI is already proving invaluable. By using AI natural language processing (NLP) and EHS expertise embedded into the AI model, AI improves the quality of incident descriptions from which the AI can automatically categorize hazards and suggest corresponding root causes and corrective actions. AI is also playing a crucial role in contractor safety, automating the review of contractor safety and qualification documents to speed onboarding without compromising compliance. Even in chemical management, AI is making strides by enabling EHS professionals to scan entire SDS libraries to flag hazardous and regulated ingredients, and pinpoint chemicals of concern instantly so companies can gain greater oversight of chemical inventories.
AI also strengthens Job Safety Analysis (JSA). Many JSAs fall short when hazards are miscategorized or when critical controls are overlooked, leaving organizations vulnerable. By flagging weak assessments or missing controls, AI helps professionals intervene earlier, when prevention is less costly and more effective, rather than after incidents occur.
These are just a few examples why AI should be seen as an enabler for EHS professionals rather than a threat. By reducing administrative load, accelerating analysis, and improving consistency, AI allows safety leaders to focus their time and expertise on higher-level decision-making.
Lessons from GPS Adoption: Mindset and Process Shifts
In its time, successful adoption of GPS necessitated a cultural shift: trusting technology without abandoning human judgment. Users ultimately had to get comfortable with a digital co-pilot that might occasionally be wrong, but the benefits far outweighed the risks. As long someone was still “behind the wheel” to evaluate the information the system provided and the final decision where to go, the risks were controlled. Adoption of AI in EHS requires the same level of human oversight.
Organizations which embrace AI-assisted EHS decision-making must also maintain a “trust but verify” culture. AI may suggest a control or highlight a trend, but the EHS professional has the final say-so. The cultural hurdle is not about surrendering expertise, but about learning to accept help. Just as GPS users eventually realized the time savings, simplicity, and improved navigation, EHS professionals are likely to view AI as indispensable once they experience its value first-hand.
Building Trust Through Transparency and Ethics
Trust, transparency, and ethics in AI cannot be afterthoughts or hollow promises. They must be built directly into AI systems by design, from the get-go. That means providing clear and obvious explanations of data outputs like risk scores and control recommendations, providing explicit human-in-the-loop controls and override capabilities, and establishing strong data governance to protect privacy and secure sensitive information. Ethical AI models are essential to guard against bias and ensure that the mission always remains focused on safety, not automation for its own sake. When safeguards are visible and auditable, organizations can embrace AI with confidence, knowing it augments human EHS expertise rather than replacing it.
Taking the First Step: Start Small, Scale Responsibly
For safety leaders wondering where to start, the key is to remember the old saying that “Rome was not built in a day.” The most effective path forward is to begin with a focused pilot project in one high-priority area of the EHS program. That might be incident analysis to detect PSIF risks, high-speed scanning of historical incident records to uncover emergent risks or using AI to strengthen the quality and reliability of JSAs.
Success should be measured using clear metrics such as the speed of risk detection, the clarity of prioritization, and the effectiveness of AI-recommended controls. Once confidence builds, organizations can expand into adjacent areas like ergonomics or contractor safety, where proven AI capabilities already exist.
This “start small, scale responsibly” approach creates immediate value while laying the groundwork for long-term, responsible adoption.
The Road Ahead
Like GPS, AI in workplace safety will soon shift from “nice to have” to a necessity. Before you know, it will become unthinkable to manage safety programs without the speed, insight, and efficiency AI provides. The journey requires trust, transparency, and cultural adaptation, but the destination is clear: safer workplaces, fewer incidents, and empowered safety professionals who spend less time buried in data and more time protecting workers.
AI is not here to take the wheel. It is here to guide, illuminate, and enhance the path forward. For workplace safety professionals, the opportunity to embrace AI as the GPS of the 21st century is one that will help them navigate the complexities of modern risk management and lead their organizations to safer outcomes.