Artificial Intelligence (AI) is one of those topics that seems to pop up everywhere at the moment — including in environment, health and safety conversations. From dashboards and predictive analytics to automated reporting, it’s often presented as the next big thing.
But is AI genuinely helpful for EHS, or is it another buzzword that risks distracting us from the basics?
What do we actually mean by “AI” in EHS?
In simple terms, AI in EHS usually refers to systems that can analyse large amounts of data and identify patterns faster than a human could. That might include:
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Reviewing incident and near-miss data to highlight trends
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Flagging high-risk activities based on previous events
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Supporting inspections or audits through digital checklists and analysis
It’s less about robots replacing safety professionals, and more about software that helps make sense of information we already have. Some examples include Serenity EHS, Glynt AI and Visionify.
Where AI can be genuinely useful
One of the biggest challenges in EHS is not a lack of data, but what to do with it. Many organisations collect reports, inspection records and observations that are never fully explored.
Used well, AI tools can:
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Highlight recurring issues that might otherwise be missed
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Support more informed risk assessments
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Help prioritise actions where resources are limited
For organisations managing multiple sites or complex operations, this can be particularly helpful. It allows patterns to emerge without relying solely on manual review.
But it’s not a silver bullet
AI can only work with the information it’s given. If data is inconsistent, incomplete or poorly recorded, the output will reflect that.
There are also wider considerations, including:
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Trust: Will people rely too heavily on automated outputs?
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Transparency: Do we understand how conclusions are reached?
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Cost: Is the investment proportionate to the benefit?
And, importantly, AI cannot replace experience, judgement or conversations on the ground. It can support decision-making, but it can’t understand context in the same way people can.
Human judgement still matters
EHS has always been about more than numbers. Understanding why something happens often requires talking to people, observing work, and recognising pressures that data alone doesn’t show.
AI might help identify where to look, but people still need to understand why something is happening and what to do about it.
In that sense, AI works best as a support tool — not a decision-maker.
Is AI right for every organisation?
For some organisations, AI-based systems may offer real value. For others, improving the quality of existing data, simplifying processes, or strengthening safety culture may deliver far greater benefits.
There’s no single “right” answer. The key is being clear about the problem you’re trying to solve, rather than adopting technology for its own sake.
A conversation worth having
AI in EHS is an interesting development, and it’s likely to keep evolving. Used thoughtfully, it has the potential to support better decisions and more proactive approaches to risk.
The question is not whether AI is good or bad — but how, and whether, it fits into your organisation’s approach to environment, health and safety.
What’s your view?
Have you seen AI used well in EHS, or does it feel over-promised at this stage?
