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Expert insights on cutting through the clutter   

By Benita Mehta, ISHN Chief Editor

Be more specific
    Porter noted that AI can be particularly effective in addressing specific safety challenges, such as ergonomic injuries or the need for more comprehensive risk assessments. For example, AI-powered computer vision can be used to analyze security camera footage and identify potential safety risks, while AI-driven tools like chatbots can help streamline the creation of training materials and procedures.
    In addition to aligning AI solutions with business needs, Porter also emphasized the value of conducting small-scale proof of concept projects to test the effectiveness of AI in a real-world context. By starting with a more limited scope, organizations can better assess the potential impact of AI and build a stronger business case for further investment.
    “You don’t need to go wild and invest millions in this,” Porter said. “Just do a small proof of concept to say, okay, is this truly going to move the needle on that critical business need or risk that I’m trying to analyze? And if so, let’s see if we can prove it and then also help support the business case for what you want to do to move forward.”

Addressing concerns and challenges
    While AI presents a range of opportunities for improving safety and reducing risk, Porter also acknowledged the potential challenges and concerns that can arise, particularly around data privacy and security. She noted that some organizations may be hesitant to adopt AI due to concerns about how sensitive data will be used and shared.
    To address these concerns, Porter recommended taking a proactive approach to data privacy and exploring AI solutions that offer more robust data protection. She also highlighted the importance of transparency and communication with employees about how AI will be used and what data will be collected.
    “There are ways, I think, that people can still leverage the technology in a protected way,” Porter said. “So, for example, we set up, and there’s a number of companies that have done this, they will use the back-end portion of ChatGPT and connect in through an API.”
    There’s also a growing trend of organizations moving towards more closed, internal AI systems that offer greater control over data privacy and security, Porter said. For example, Gensuite has recently transitioned to using Amazon’s AWS Bedrock platform, which provides a more secure and compliant environment for AI development and deployment.
    “We made a decision to move, for example, to AWS Bedrock, which is fully internal. And it uses Claude, which is a different gen AI solution that I think competes essentially with ChatGPT. But we can meet all of our data privacy requirements and expectations using that solution,” Porter explained.

A thoughtful approach
    Overall, Porter emphasized the need for a strategic and thoughtful approach to AI adoption in the safety space, with a focus on driving tangible business outcomes and addressing specific safety challenges.
    “I think you have to really ground yourself on asking yourself what problem you trying to solve, because otherwise you just get overwhelmed,” she said. “You have to align it with something that’s specific for your business, what you’re trying to achieve and where you are and your program maturity curve — that’s what I typically recommend.”
    AI has the potential to improve overall safety outcomes, and Porter pointed to the use of AI in data analysis and decision support as key areas where businesses can see significant improvements.
    “AI has the power to analyze documents and data and produce summaries and trends,” Porter said. “This can help EHS leaders spend less time chasing bad data and more time focusing on actionable insights.”