March 30, 2026
As the AI solutions lead for Dix & Eaton, I appreciated the opportunity to serve as the moderator of a recent in-person discussion on “AI in Action: Real Applications for EHS & Sustainability Leaders.” This late March regional networking event was held at Avery Dennison headquarters near Cleveland and was sponsored by Avery Dennison, Dix & Eaton, Haley & Aldrich and the National Association for Environmental Management (NAEM).
One of the early takeaways from the event was how many AI use case possibilities exist for the EHS&S profession. They are organized into categories such as compliance, regulatory and product management; digital intelligence monitoring; safety and workflow management; worker health and well-being; and workforce training.
Of course, no matter your field, the potential to integrate AI into daily workflows is everywhere. In corporate communications, for example, the list includes communications planning, best practices research, peer and competitor benchmarking, messaging, content development, data visualization, administrative support and more.
Considering the potential applications, our leadoff speaker, Mike Colarossi, head of enterprise sustainability for Avery Dennison, challenged everyone to be “possibilists” (optimists who focus on what’s possible) to explore how AI and other emerging tools can be used to help solve problems. “A possibilist is a person who asks, ‘What can I do now to make good happen?’” Colarossi explained previously as the keynote speaker of the Greater Cleveland Partnership’s Corporate Sustainability Summit.
Our other speakers were Megan Pedersen, senior director of EHS for Avery Dennison, and Victoria Buhler, data specialist for Haley & Aldrich.
Our three speakers and the audience of more than 30 EHS, sustainability and corporate communications professionals covered a lot of ground in 90 minutes, and these were among the key takeaways:
- To get the buy-in and momentum you need, AI implementation should focus on solving a problem, not simply changing a project or process that is already working. In some cases, you may solve a problem you didn’t know you had.
- Rather than relying solely on individual effort, the best AI use cases come from partnering with someone – in a similar role, from a different function or with an outside partner.
- It’s a mistake to assume that any AI tool can solve problems for you. The “humans in the loop” are the problem solvers; AI is a catalyst that should help make that process more efficient, repeatable and durable.
- Pilot projects should be the standard – they break down complex situations into individual tasks and workstreams, allow you to get to go/no-go faster, and provide direction for future problem-solving.
- AI enables accelerated and more complete data gathering and analysis, including the ability to collect and act on leading indicators rather than waiting on lagging indicators that may be available on a monthly, quarterly or annual basis.
- An AI exploration and integration agenda should be viewed through a change management lens as it alters the way people work. Like any change management initiative, it requires a plan, a set of rules and expectations, engagement with the participants and training.
Not sure where to start? Interested in learning more about AI training and change management? Email me and let’s connect!
