Haven Safety AI has been named one of three finalists for the 2026 Edison Award by the Edison Electric Institute, one of the electric power industry’s highest honors recognizing leadership, innovation, and contributions to the advancement of the industry.

For Haven, this recognition is an important milestone. It affirms the role AI can play in helping organizations move beyond traditional safety reporting and toward a more continuous, consistent, and proactive system of learning.

The Edison Award is rooted in the electric power industry. But the significance of Haven’s recognition extends well beyond.

Across high-risk industries, safety leaders are facing the same challenge: how to learn faster from incidents, near misses, and lower-severity events so they can prevent serious harm before it happens.

That challenge exists in construction, energy, manufacturing, oil and gas, logistics, transportation, mining, field services, and other complex operating environments where risk changes quickly and safety decisions depend on the quality of information available to frontline teams and leaders.

Haven was built for that reality.

From documenting incidents to learning from work

For decades, safety systems have focused heavily on documentation. Organizations collect incident reports, complete forms, conduct investigations, assign corrective actions, and close cases.

Those activities are necessary. But documentation alone does not create learning.

True safety learning requires organizations to understand what happened, why it happened, what conditions shaped the event, and what actions will reduce the likelihood of recurrence. It requires investigators to move beyond surface-level conclusions and identify systemic contributors, failed or missing controls, and patterns that may exist across sites, teams, and operations.

That is where Haven is changing the model.

Haven’s AI-native platform helps organizations structure evidence, standardize root cause analysis, and link corrective actions to defensible reasoning. The result is faster investigations, more consistent analysis, and stronger insight into the conditions that create risk.

At AES, where Haven has been deployed in real-world safety operations, the platform has demonstrated measurable impact, including up to an 80 percent reduction in investigation labor effort, compression of investigation timelines from weeks to hours, and expanded investigation coverage across incidents, near misses, and lower-severity events.

“Instead of spending time compiling reports behind a desk, our teams can now focus on understanding risk on site,” said Chantz Horman, Director of U.S. Operations and Construction Health & Safety at The AES Corporation. “We have seen an 80% reduction in root cause analysis safety investigation labor time with the adoption of Haven Safety AI. With its intuitive interface, Haven has quickly become a force multiplier. It’s helping us capture better information from the field, structure investigations more consistently, and learn faster.”

Why this recognition matters beyond the electric power industry?

Utilities are among the most complex and safety-critical operating environments in the world. Crews work across distributed assets, changing field conditions, high-energy systems, contractor networks, regulatory requirements, and time-sensitive operational demands.

That makes the electric power industry an important proving ground for safety innovation.

But the questions Haven is helping answer are cross-industry questions:

• How do we reduce administrative burden without reducing investigation quality?

• How do we learn more from near misses before they become serious events?

• How do we identify recurring control weaknesses across sites and teams?

• How do we make corrective actions more targeted, practical, and defensible?

• How do we help frontline teams capture better information without adding friction to their work?

These questions are not confined to one sector. They are the questions every high-risk organization must answer if it wants to move from reactive safety management to proactive risk reduction.

That is why this recognition matters. Although the Edison Award is a electric power industry award, the significance of Haven’s selection is much broader. It reflects a larger shift in how organizations are thinking about safety, data, and prevention.

AI is no longer just a back-office tool or an experimental technology. Used responsibly, it can strengthen the core workflows safety teams rely on every day. It can help organize evidence, surface missing information, identify patterns, and challenge thin explanations such as “human error” or “procedure not followed.”

The goal is not to replace safety professionals. The goal is to give them better tools for learning, judgment, and prevention.

Building a system of safety intelligence

Haven combines structured evidence capture with advanced causal analysis through integrated modules and AI agents. This enables organizations to identify systemic risks, standardize investigation quality, and generate corrective actions grounded in operational and regulatory context.

That matters because safety performance depends on more than whether an investigation is completed. It depends on whether the organization learned the right lesson.

A modern safety intelligence system should help teams:

• Capture frontline insight while details are still fresh.

• Build timelines based on evidence, not assumptions.

• Identify failed, missing, degraded, or impractical controls.

• Connect individual events to broader risk patterns.

• Generate corrective actions that address causes, not symptoms.

• Support human review, accountability, and defensible decision-making.

This is the future Haven is building: a future where investigations are not just records of what went wrong, but engines for understanding risk and preventing harm.

A milestone for Haven, and a signal for the future of safety

Haven’s selection as an Edison Award finalist underscores the growing importance of AI-native safety solutions in strengthening safety performance, improving regulatory defensibility, and enabling more resilient operations.

The Edison Award finalists are selected by a review committee composed of industry experts, with final winners determined by a panel of former EEI chairs and senior electric industry leaders. The winner will be announced during EEI 2026, EEI’s annual conference and thought leadership forum.

For Haven, this recognition is both a milestone and a reminder of the work ahead.

The future of safety will not be defined by more paperwork, more disconnected tools, or more isolated corrective actions. It will be defined by how quickly organizations can learn, how consistently they can apply that learning, and how effectively they can prevent harm before it occurs.

That is the work Haven is leading.

And this recognition from EEI is another signal that the future of safety is moving from reporting to learning, from hindsight to prevention, and from fragmented data to intelligence that helps organizations act before people get hurt.