Every safety leader knows the value of hazard and near-miss reporting. The challenge isn’t convincing people that reporting matters, it is making the process easy and valuable enough that employees consistently do it.
When hazards, near-misses, and process safety events go unreported or lack detail, organizations miss critical opportunities to prevent future incidents. Investigations drag on, root causes become harder to identify, and safety teams waste valuable time chasing missing details instead of reducing risk.
Artificial intelligence (AI) offers a way to change this dynamic. Rather than replacing people, AI helps frontline workers capture higher-quality information the moment it matters most, leading to stronger investigations and more reliable preventive data.
The reporting challenge: Quality over volume
Many organizations have invested heavily in digital safety programs, yet reporting quality remains inconsistent. Sphera’s recent AI + Safety Culture survey highlighted this gap: while 94% of frontline workers say it is easy to report incidents, only 57% describe it as very easy. More importantly, 10% of workers admitted to withholding a reportable safety event within the previous six months.
The reasons are revealing:
- Some workers felt the issue wasn’t serious enough.
- Others feared negative consequences.
- Many didn’t believe reporting would lead to actual improvements.
For EHS leaders, this leaves hazards invisible until an injury occurs. Furthermore, even when reports are submitted, they often lack critical context. A vague entry like “employee slipped” or “chemical leak occurred” leaves investigators with more questions than answers. To find root causes, investigators need to know the specific tasks, equipment, environmental conditions, and barriers involved, details that are just as vital for daily worker safety as they are for high-consequence process safety incidents.
Better investigations begin with better first reports
Frontline workers usually complete incident reports under pressure and may not know exactly what information investigators need. As a result, EHS teams must spend hours tracking down employees, supervisors, and contractors to reconstruct the event before they can even begin a root-cause analysis.
Sphera’s First Report AI agent was designed to remove this friction. The AI guides frontline workers in real time as they fill out a report. It instantly identifies missing information and improves clarity, ensuring reports are complete, consistent, and investigation-ready before submission.
The result is higher-quality reports from the start, faster investigations, and more time spent preventing incidents instead of correcting paperwork.
Data-driven safety decisions
When incident reports follow a consistent structure across all sites, organizations build a more reliable safety data foundation. Patterns and recurring hazards become visible, allowing leaders to prioritize corrective actions based on evidence rather than assumptions.
This consistent data structure is highly valuable for managing both occupational and process safety risks:
- For worker safety: Cleaner data reveals recurring unsafe behaviors, contractor trends, or equipment flaws before injuries increase.
- For process safety: It helps identify the “weak signals” that precede major accidents—such as recurring equipment failures, barrier degradation, procedural deviations, or minor hazardous material near-misses.
These insights allow EHS leaders to shift from reacting to incidents to proactively managing risk across the entire enterprise.
Turning reporting into prevention
The strongest safety cultures are built on trust, participation, and learning. Every documented hazard, near-miss, and process safety event creates the visibility needed to identify risks early and strengthen operational resilience.
By helping workers submit complete, investigation-ready reports right from the start, AI removes a major barrier to safety performance. For EHS leaders, this means better data, stronger insights, and the confidence that risks are being mitigated before they become serious incidents.
