Digital safety programs have made reporting easier and more accessible. Most frontline workers know when and how to report safety concerns, yet some still hesitate to speak up.

Safety professionals must help turn frontline reporting access into consistent participation. Every unreported observation is a signal EHS teams cannot evaluate, learn from, or act on. That hinders their ability to proactively protect workers.

Artificial intelligence (AI) can help safety teams identify patterns, surface emerging risks and intervene before incidents occur. But those capabilities are only as useful as the safety information available to support them.

For EHS leaders, that makes frontline participation a risk management priority. When workers consistently share observations, near misses and other safety signals, organizations gain a more complete view of workplace risk and opportunities to act before someone gets hurt. Building that participation also creates a stronger foundation for AI and other digital tools to improve safety outcomes.

Why Digital Safety Programs Still Miss Frontline Signals

In an April 2026 Sphera survey of 500 U.S. frontline workers at enterprise organizations, 94% said it is easy to consistently and honestly report incidents, near misses, and other safety observations. Yet one in 10 said they failed to report an incident or observation they should have reported in the previous six months. Among those who did not report, 33% said the issue didn’t seem important or severe enough, 22% worried about negative consequences, and 20% didn’t believe reporting would lead to improvements.

Each unreported incident or observation represents a data point that never enters the safety system, limiting EHS teams’ ability to identify trends, inform corrective actions, or support predictive analytics. While 96% of respondents agree they know how and when to report a safety risk or concern, the findings suggest that knowing how to report does not guarantee every concern will be raised.

That distinction matters as organizations look to strengthen digital safety programs. Frontline participation encompasses more than reporting incidents and near misses, but when safety observations go unreported, EHS teams have a less complete view of workplace risk.

Incomplete reporting sits alongside a broader data visibility challenge. The survey found EHS software adoption has reached 62%, but only 33% of respondents report real-time visibility into safety-critical data. Just 44% document or report in the field in real time. Nearly 40% still use spreadsheets, while 25% rely on paper-based processes.

This shows digital adoption does not necessarily mean complete visibility. An organization can have software in place and still miss signals because workers don’t report them, information arrives too late, or inputs remain fragmented across workflows. Access can create another blind spot. The survey found only 35% of contractors are allowed to report incidents, potentially excluding part of the workforce from the safety data organizations rely on.

The problem becomes even more consequential as safety programs incorporate AI. Predictive applications depend on consistent, high-quality inputs such as near-miss reports, hazard observations, training data, and audit completion.

Those inputs give models enough depth to identify emerging patterns, flag anomalies, and prioritize risks before incidents occur. But when frontline participation is incomplete, even the most sophisticated analytics can’t act on signals that never entered the system. 

How EHS Leaders Can Turn Frontline Trust into Participation

Organizations don’t need workers to trust every new safety technology on day one, but they do need to give them reasons to trust the safety process around it. That starts with three priorities.

1. Show workers what happens after they speak up.

Reporting is only half of the equation. Workers also need to see evidence that their concerns are being heard and acted on. Only 20% of frontline workers say knowing their feedback leads to action motivates them to participate in workplace safety programs, and less than half strongly agree their participation makes a difference in safety outcomes.

EHS leaders need to make the connection between reporting and outcomes more visible. When a near miss prompts a corrective action, an observation changes a procedure, or repeated reports reveal a broader hazard, leaders need to communicate the action back to the workforce.

The feedback loop is especially important for information organizations use to identify risk before incidents occur. Inputs such as permit-to-work compliance, fatigue and exposure, hazard observations, and risk heatmaps become more valuable when workers see why contributing them matters.

Over time, visible follow-through can change reporting from a compliance task into proof that frontline input influences how safety is managed.

2. Build trust into the reporting process.

Ease of use reduces friction, but it doesn’t address workers’ concerns about what happens after they speak up. Among workers who withheld a report, 22% worried about negative consequences.

Leaders can address that uncertainty by making the reporting process more transparent. They should clearly communicate how reports are reviewed, who can access safety data, how that information is stored and protected and what safeguards are in place to prevent retaliation for raising safety concerns.

That transparency becomes especially important as organizations introduce AI into safety programs. Thirty-one percent of workers say clearer communication about how safety data is used would encourage their participation in AI-powered programs, while 27% point to clarity around how information is stored and protected. Employers can respond by explaining what data an AI-powered tool uses, what it is used to identify or recommend, who reviews its outputs and where human oversight remains part of the process.

3. Make AI prove its value on the front line.

Frontline workers are not rejecting AI outright. Eighty-three percent say they are interested in using an AI assistant for safety-related tasks within the next six months. At the same time, only 19% believe employees should have full trust in AI as part of workplace safety programs. That combination should tell EHS leaders something important: Interest does not equal trust.

The best way to build confidence is to show workers how AI can make their jobs safer. Start with applications where the benefits are immediate and tangible, such as identifying potential hazards or risks, receiving real-time safety alerts and recommendations, getting answers to safety questions and reporting incidents or near misses. These are practical use cases tied directly to the work rather than abstract promises about AI transformation.

AI can only strengthen safety programs when the processes supporting it capture timely, reliable information. Many organizations are investing in predictive maintenance, automation and AI-supported analytics while core processes still depend on spreadsheets, paper and disconnected systems. Layering advanced technology onto incomplete or fragmented processes can leave EHS teams with the same blind spots they had before.

AI earns credibility when workers can see the connection between their input and a safer outcome: a hazard identified sooner, a risk surfaced before work begins, or a safety question answered when it matters. That proof creates a stronger basis for expanding AI into more predictive applications over time.

Digital Safety Starts with Frontline Trust

EHS teams have more technology and more data at their disposal than ever before. The opportunity now is to make sure the people closest to workplace risk remain part of the progress.

When workers understand how their input is used, see evidence that it leads to action, and experience technology making their jobs safer, participation is easier to sustain. Stronger frontline participation gives EHS teams a more complete view of workplace risk and a stronger foundation for using digital and AI-powered tools to improve safety outcomes.