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.

Aligning AI Use with Organizational Priorities: A Practical Perspective for EHS Professionals

By Natasha Porter, chief customer officer, Benchmark Gensuite

Over the last five years, our team has been deeply engaged in advancing practical AI solutions for environmental, health and safety (EHS), sustainability and compliance professionals. Even before AI became the buzzword it is today, we were exploring how this technology could be applied in the field to improve safety outcomes, streamline compliance and reduce administrative burden. It’s been exciting to see how far things have come — and even more exciting to help guide how organizations can use AI responsibly and effectively.

Before I ever wrote a line of code or talked about software, I was an EHS professional myself. I started my career working on manufacturing floors and in field service environments, side by side with teams to implement programs and maintain compliance. The reality is that EHS professionals are constantly managing an overwhelming volume of activities such as reporting, inspections, audits, corrective actions and training, and often with limited resources. I remember wishing there were tools to automate some of those repetitive tasks, so I could spend more time on prevention and less time on paperwork.

That’s part of what drew me to this work. When we started focusing on AI five years ago, one of our earliest projects targeted potentially serious incidents and fatalities (PSIF). The idea was simple: Could we help organizations automatically identify high-risk situations without requiring hours of manual classification and review? The results were powerful, and it was clear AI had practical value. Honestly, if I’d had access to these tools when I was in the field, I would’ve saved years of work.

The rapid shift toward AI in EHS

Over the past few years, I’ve had the opportunity to present on AI at several American Society of Safety Professionals (ASSP) events. Each time, I start by asking the audience to raise their hands and share where they are on their AI journey: learning, piloting or fully implementing. The change in responses has been dramatic. A year ago, maybe 25% of attendees said they were actively piloting or deploying AI. This year, that number was closer to 50%.

That’s an enormous shift in just 12 months and it reflects the speed at which AI adoption is accelerating across industries. Curiosity is high, but so is apprehension. And that’s understandable. Many EHS professionals want to make sure they can trust these systems before relying on them for safety-critical work. My advice is always the same: Be curious, but don’t stand still. Learn by doing. If you wait until everything feels “safe” and “certain,” you’ll be left behind while others move forward.

Start with priorities, not technology

When I talk to organizations about AI, I always encourage them to start with their business priorities, not the technology itself. Take a step back and ask: What are the top two or three challenges in your EHS program right now?

Maybe you’re struggling with data quality in incident reporting. Maybe it’s the time it takes to complete root cause analyses or perhaps sustainability data management. Whatever those top issues are, start there. Too often, people get excited about AI for its own sake. They pick a technology that sounds interesting, like ergonomics AI, even though ergonomics isn’t one of their core challenges. Then they can’t get the leadership buy-in to move the technology forward. When you align AI use with your top organizational priorities, you’re more likely to secure support, funding and long-term adoption.

If you’re not sure where to start, that’s okay, too. In those cases, you might explore partnerships with your IT team, an external consultant, or even organizations like ASSP, which can help you identify credible use cases and frameworks.

Building trust in AI

Trust doesn’t come overnight, it’s built. I like to think of it as a three-layer pyramid.

At the base is education. You can’t trust what you don’t understand. So step one is building a solid foundation of knowledge about what AI is, how it works, and what it can (and can’t) do.

The middle layer is real-world evidence. Seeing live demonstrations or case studies where AI has been implemented successfully helps people visualize its potential.

At the top is peer-to-peer experience. Hearing from a fellow EHS or sustainability professional who has used AI and seen results is incredibly powerful. I can present all the data in the world, but if a peer says, “This saved me two hours a day,” that’s what resonates.

Those three pieces — education, examples and experience — build trust and accelerate adoption.

Embedding AI in the workflow

Over the past five years, we’ve developed more than 20 different AI “bots,” all designed to integrate directly into users’ workflows. Here are two examples.

The first is Describe It AI. One of the biggest frustrations EHS leaders share is inconsistent or poor-quality incident descriptions. We created a bot that gives real-time feedback as users type, similar to how a password strength checker works. As you describe an incident, the AI provides a quality score and prompts you with suggestions to improve clarity and completeness. The result? Better data the first time, no follow-up emails, no chasing down missing information. It’s a small change with a huge behavioral impact.

The second example is AI-assisted root cause analysis. After an incident, the system can generate a draft investigation summary using the data already entered. Users can then review, edit and rate the quality of the output, which helps the AI continuously improve. These kinds of tools don’t replace human expertise—they amplify it, saving time while improving consistency and accuracy.

Partnering for broader impact

We also partner with other AI providers that specialize in areas like wearables. We’re not a hardware company, but we know those tools can be lifesaving. For instance, if a wearable detects a heat stress event, that data can automatically feed into our EHS software, triggering a notification for the site leader. Instead of manual data entry or delayed reporting, the information flows in real time. AI integration really shines when it enables faster, smarter decisions that protect people.

Communicating AI’s value across the organization

One last thought: Communication is key. When rolling out AI, remember that every audience is different. Your CEO might be an early adopter who wants to know how AI drives strategic value. A frontline worker might be anxious about what it means for their job or privacy.

AI can help bridge those communication gaps. Even tools like ChatGPT can be used to craft messages in different languages or tones, tailored to specific audiences. That’s part of making AI adoption equitable, ensuring everyone understands the “why” and feels included in the change.

AI isn’t the future, it’s now. And for EHS and sustainability professionals, aligning AI with organizational priorities isn’t about chasing trends. It’s about solving real problems faster, safer and smarter. Start with what matters most, build trust through education and experience, and integrate AI directly into the work people already do. That’s how you turn curiosity into capability and deliver lasting value for your organization.