On Feb. 19, 2026, the ASSP Artificial Intelligence (AI) Task Force released its white paper, “AI and the Evolving Role of EHS Professionals.” To expand on the paper’s key themes, task force members are sharing their unique perspectives in this new weekly series in ASSP News.

Five Key Reasons to Adopt Safety Tech in Your Organization

By Tom West, vice president and global practice leader, MākuSafe

EHS professionals today are at a pivotal moment. Sensors, data and associated safety technology are no longer abstract ideas; they are actively helping organizations identify risks and prevent injuries. EHS professionals are now enabled to make data-driven decisions that keep people from getting hurt.

The goal remains the same as it always has been: to collect and interpret meaningful data to focus efforts where they matter most. But we must be mindful that we are experiencing a fundamental change in how we manage safety, now that technology and AI can visualize patterns, highlight exposures, and provide predictive value in assessing and understanding who might be at highest risk.

Here are five key reasons why adopting safety technology in your organization can prevent accidents and illnesses, reduce costs and enhance productivity.

1. The transformation shift from lagging to leading indicators

   Historically, safety programs have relied on lagging indicators that tracked who got hurt in the recent past, with EHS professionals responding afterward. That’s a reactive model. Today, we’re seeing a transformational shift from reactive approaches to proactive, preventative safety management.

   When a safety leader can see trends in heat exposure, noise, ergonomic strain, slips and falls, it’s game-changing. The focus shifts from the worker to the work. Leading indicators reveal exposures and risk patterns before incidents occur. It’s not about “who’s at fault?”; it’s about “what’s going on?” and “how do we fix it?”

   Operations leaders have used sensors to optimize productivity for decades. What has often been missing in EHS programs is this kind of data-driven insight — understanding how people interact with their environment, where risk builds and how to intervene early. That’s the next evolution of safety management.

2. The use of data and AI to work smarter

   Data fluency, maturity and technology competence are critical. EHS professionals need to become data literate by learning how to use data and AI to work smarter, not harder.

   AI enhances what we do. It allows us to identify hazards, analyze risk and evaluate results based on evidence rather than gut feelings. We no longer have to wonder whether a safety intervention worked or assume that it did because nobody’s gotten hurt yet. Instead, we can see, in real time, whether corrective actions are achieving the desired outcomes. That is continuous improvement in safety, powered by data.

   Integrating leading indicator data with historical and risk assessment data can be a force multiplier. Good data in, good results out. If we want AI to help make better decisions, we must feed it the right kind of data.

3. Human-centric, privacy-first technology focuses on the work, not the worker

   Whenever you say “wearable,” people often assume it’s about tracking them. In personal life, people are fine with devices like Apple Watches or Fitbits, but when issued by a company, perceptions change.

   A construction industry 2023 study published in the journal Engineering looked at OSHA data over a one-year period and concluded that wearable sensing devices could have prevented 34% of deaths and fatalities in construction. However, the study also found that 46% of construction labor are not willing to use biometric wearable sensing devices, and 59% of construction labor are not willing to use tracking wearable sensing devices.

   That’s why technology must focus outward — on exposures and experiences — not inward on the worker. Privacy must be protected, and personally identifiable information or biometrics avoided. Environmental data points such as sound exposure, air quality, heat index and ergonomic risk factors (twisting, turning, pushing, pulling and repetitive motion) are what matters.

   The goal isn’t to hold workers accountable; it’s to give organizations actionable insights to prevent injuries. When reporting tools are simple — for example, allowing workers push-to-talk capability to communicate an observation or near miss — participation soars. People want to be part of the solution; they just need tools that fit naturally into their workday.

4. Worker receptiveness and trust in technology drives safety culture

   Technology adoption is ultimately about trust and culture. A safety manager who can champion an idea internally with confidence and clear communication makes all the difference. When trust is built, resistance decreases.

   There will always be early adopters and laggards. Some hesitate about AI or new technology out of fear or misunderstanding. Transparency helps by showing workers what data are collected and used, and how the data benefits them. I’ve seen labor and management come together once they understand that the data are about preventing harm, not assigning blame. That is the environment where technology thrives.

   Safety tech should feel like another form of PPE — a proactive tool, not a mechanism for surveillance. The more we make it about people, the faster adoption follows.

5. The positive, real-world impact of data-driven insights

   Results build belief. Organizations using data-driven insights have identified root causes of musculoskeletal strain, implemented changes and eliminated incidents for multiple years — even during peak business seasons.

   Some companies have achieved their best workers’ comp years ever after acting on leading indicators. Costs dropped by as much as 60% within a year. Productivity saw improvement of up to 6%, too. Across a large operation, that represents millions of dollars saved while keeping people safer. These results prove that when data informs decisions, both people and organizations benefit.

The sad fact — and the big opportunity

Despite available solutions, adoption of safety technology remains low. Accidents and illnesses can be prevented or even eliminated. Costs can be reduced. Productivity can be improved. Yet, industrial EHS teams are often understaffed, underfunded and not trained in technology or analytics.

That’s exactly why we need to start. The tools exist today to help us work smarter, faster and with measurable results. We just need to lean in, learn and lead the way.

Moving forward

Driving AI and technology adoption requires storytelling and transparency. Real-world examples and case studies from practitioners are critical. Competency in data fluency is essential. Leaders must inspire confidence and communicate clearly about what’s changing and why.

Professional associations like ASSP can play a key role by encouraging knowledge sharing among practitioners, vendors and researchers in a transparent, educational way. The goal isn’t to sell technology, but to share what works, what doesn’t, and how we can all improve.

The future is already here. Technology exists today to solve problems that have challenged us for decades. Organizations that embrace it by targeting the work rather than the worker will keep people safer and operate more competitively.

For me, the mission is simple: make safety smarter and more human to help our profession move from “hope and react” to “predict and prevent.”