For frontline teams, reporting hazards often starts with describing what happened, what was observed, and why it matters. In practice, that process depends heavily on time, writing clarity, and individual experience—especially when reports must be completed during inspections, incident investigations, or routine safety observations.

According to the 2026 EHS Benchmarking Report, 90% of EHS leaders surveyed believ workplace incidents, hazards, or near misses are going underreported, while nearly half point to obstacles such as time required, limited systems, and tedious reporting processes as key barriers.

When details are incomplete or inconsistent, EHS teams lose valuable context and often spend additional time clarifying observations that should have been captured correctly from the start.

How Manual Hazard Reporting Creates Blind Spots Across Sites

Traditional reporting often relies on workers translating what they see into written descriptions. That means identifying hazards, explaining surrounding conditions, and documenting context manually—sometimes under time pressure and in environments where writing speed, language, or reporting experience vary.

This creates inconsistencies in how risks are documented. Similar hazards may be described differently across sites, key environmental details may be omitted, and report quality often depends on who is completing the entry.

Autonomous AI Agents simplify this process by interpreting visual information directly within existing workflows. Instead of starting with manual text entry, teams can begin with what they already capture naturally: an image. AI then structures visual observations into clear, usable reporting language that supports faster follow-up and stronger visibility.

Learn more about Genny AI Automation Agents and how they streamline complex workflows.

How the Genny AI Image Helper Works

The Genny AI Image Helper begins working as soon as an image is attached within a reporting workflow. Built directly into Benchmark Gensuite applications with attachment functionality, it follows a simple, repeatable process:

1. Upload an image during reporting
   A photo is added during a concern report, injury report, incident investigation, or inspection.
2. Analyze visible hazards and conditions
   The Agent reviews the image to identify hazards, unsafe conditions, objects, environmental cues, and potential risk factors.
3. Generate a structured description
   A polished summary is created automatically, describing what is visible in clear, standardized language.
4. Support review before submission
   Workers can review or refine the generated description in seconds before completing the report.
5. Strengthen reporting consistency across sites
   Because the same structured logic is applied each time, reporting becomes more consistent regardless of worker experience, language, or writing ability.

Changing Day-to-Day Concern Reporting for EHS Leaders

By transforming images into structured reporting language, the Genny AI Image Helper introduces a new digital co-worker for frontline reporting—one that helps teams capture clearer information without slowing down the reporting process.

Instead of relying entirely on manual write-ups, teams gain faster documentation, clearer descriptions, and stronger consistency across reports. This supports richer operational visibility as hazards are reported in real time.

Built to work alongside frontline teams and EHS professionals, the Genny AI Image Helper supports faster reporting while keeping review, judgment, and decision-making with the people responsible for managing risk and protecting operations. With clearer information entering the system from the start, EHS leaders can focus less on clarifying reports and more on acting on what matters.

See the Genny AI Image Helper in Action

Explore how one image can move hazard reporting from manual description to structured insight—helping teams report faster, capture more detail, and strengthen visibility across operations.

The post Making Hazard Reporting Easier with Image-Based AI appeared first on Benchmark Gensuite.

This growing strain is what our latest EHS Benchmarking Report defines as the 2026 EHS Pressure Point: the moment when rising operational complexity collides with shrinking time, attention, and resources.

Based on insights from more than 260 EHS professionals in the broad market, the 2026 EHS Benchmarking Report captures how surveyed leaders are experiencing a moment of increasing pressure, where expectations, visibility, and capacity are converging. Download the report today to access the full data set.

EHS Safety Trends Report 2026: Rising Complexity Across Modern EHS Programs

Over the past few years, EHS leaders have been balancing competing priorities. In our 2025 Benchmarking Report, 45% of professionals said new responsibilities had intensified the complexity of their roles, limiting their ability to focus on core safety functions.

What’s different in 2026 is the volume and velocity of those demands. Half of respondents now report taking on additional data collection and stakeholder reporting, effectively positioning the EHS function as a central hub for compliance, ESG metrics, and operational insights.

In just one year, the pressure has intensified significantly. So much so that many leaders interviewed now cite increased workload and competing demands as a primary driver of workplace injuries.

Today’s teams are expected to manage:

• Expanding regulatory requirements across regions
• ESG disclosures and sustainability metrics
• Workforce volatility and skills gaps
• Real-time expectations from executive leadership

Rather than appearing as isolated challenges, these demands are converging into a broader shift in how safety performance is experienced. Across the benchmarking responses, nearly half of leaders reported injury rates rising significantly, in some cases two to three times year over year, reflecting the growing strain many teams describe.

Biggest Risks Facing EHS Teams Today: Workforce Strain and Operational Risk

Hiring challenges, high turnover, and inconsistent training environments are increasingly shaping how work is performed on the ground. In the 2026 EHS Benchmarking Report, respondents consistently link these factors to higher risk exposure, missed controls, and slower hazard response. This strain is further compounded by a persistent industry challenge: underreporting.

Many respondents described a decline in frontline visibility, with a staggering number of leaders saying workplace incidents, hazards, or near misses go underreported, up from the previous year. According to EHS leaders, the challenge is often rooted in process friction. Nearly half of respondents say workers avoid reporting because the process is time-consuming, systems are insufficient, or the steps feel tedious.

In addition, more than half of the leaders interviewed say frontline workers are reluctant to speak up for a range of reasons outlined in the report—an important dynamic that raises questions about how much risk data ultimately reaches formal reporting systems.

What makes this trend particularly complex is how it develops over time, often without immediate or obvious indicators. Workforce instability rarely causes immediate spikes in incidents. Instead, it can erode safety margins over time. By the time issues appear in lagging indicators, opportunities for early intervention may already be limited.

The issue isn’t just that incidents occur. It’s how often teams say, “We didn’t see it coming,” even though the signals were there—they just weren’t captured by existing tools.

See how an AI-powered frontline safety software transforms reporting.

The Resource Gap: Why Many EHS Teams Are at a Turning Point

Beyond workforce instability and reporting gaps, another pressure point appears consistently across the data: limited resources. The benchmarking study shows that lack of budget, people, and support is the number one concern keeping EHS professionals up at night.

This shortage is unfolding at the same time responsibilities are expanding, reporting demands are increasing, and safety programs are expected to deliver faster, more precise insights to leadership.

With more than a third of surveyed organizations still relying heavily on manual processes and spreadsheets, some EHS leaders described feeling pulled into reactive work, spending more time locating or reconciling information than acting on it. Over time, that dynamic can reduce the space teams have for proactive safety leadership.

Are EHS Leaders Using Generative AI? How EHS Workflows Are Evolving

As expectations continue to grow, many leaders are beginning to explore how technology can help extend team capacity—particularly in environments where headcount and resources may not scale at the same pace as demand.

Many surveyed leaders describe actively using AI to support reporting workflows, analyze large volumes of data, and reduce administrative burden across their programs.

According to the benchmarking study, 92% of respondents are personally using generative AI in at least some part of their day-to-day EHS work. Rather than replacing existing processes, these tools are often being applied to support tasks such as summarizing incident narratives, preparing documentation, building dashboards, or identifying patterns within existing data sets.

Early examples from Benchmark Gensuite subscribers illustrate how organizations are exploring these capabilities. In just two quarters, Benchmark Gensuite’s Genny AI helped companies reclaim more than 15,900 hours of work.

The benchmarking findings suggest that AI is becoming one of several approaches surveyed leaders are evaluating as they rethink how EHS work gets done.

Future of EHS in 2026: Key Takeaways from the Benchmarking Report

Across the responses gathered in the 2026 EHS Benchmarking Report, it’s possible that many leaders are navigating a moment of transition. Rising expectations, evolving workforce dynamics, and growing data demands are reshaping how safety programs operate, often faster than traditional approaches can adapt.

For leaders trying to understand where the pressure is coming from, and how peers are responding, the full report offers deeper context, additional data points, and practical perspectives from more than 260 EHS professionals.

Download the full 2026 EHS Benchmarking Report to explore the complete findings and key trends shaping the future of EHS.

The post The 2026 EHS Pressure Point: Why Rising Complexity and Shrinking Resources Demand an AI-Native EHS Strategy appeared first on Benchmark Gensuite.

Seeing Risk Earlier: How Wearable Data and Shared Innovation Strengthen Workplace Safety

For Aanna Hoch, Director of Partner Ecosystem at MākuSafe, one of the most important shifts happening in workplace safety is how organizations are learning to act before incidents occur. As more companies look for ways to strengthen prevention, wearable technology and real-time data are helping safety teams uncover risks that traditional observations often miss, especially those tied to repetitive motion, physical strain, and day-to-day work exposure.

Through MākuSafe’s work with industrial organizations, Aanna has seen how leading indicators can change the way decisions are made by helping companies identify unseen hazards earlier and provide clearer insight into what frontline workers experience every day. This is also one of the reasons their partnership with Benchmark Gensuite has developed so naturally: both organizations are focused on helping safety teams act earlier, make better operational decisions, and turn better data into decisions that protect workers.

Key Takeaways from Aanna Hoch for Proactive Safety Programs

• Leading indicators reveal what routine observation often misses: wearable technology helps organizations uncover unseen risks before they become injuries.
• Better data strengthens prevention: rich frontline insights give safety teams clearer visibility to act proactively and improve worker wellbeing.
• Partnership grows through shared priorities: stronger outcomes emerge when organizations and their partners focus on solving real operational challenges together.
• AI becomes more valuable with stronger inputs: meaningful recommendations depend on reliable exposure data that reflects what workers experience every day.

What changes have you seen in how organizations view wearable safety technology?

Aanna: Adoption of wearable technology has been interesting. It’s definitely been a journey. MākuSafe is nine years old, and we went to market about five years ago, so we’ve seen a steady increase in understanding the impact of wearable technology—the impact of the data we’re collecting and how it can affect decisions not only for the safety and well-being of employees, but also for the well-being of the organization.

Before, there was concern about a “Big Brother” watching over frontline workers. Now we’re seeing this amazing amount of data that can actually protect frontline workers by providing insights that help make work better for employees. That evolution has really been fun to be part of.

What do the organizations that adopt technologies like MākuSafe tend to have in common?

Aanna: I think that’s actually what attracted us to Benchmark, because we saw many of the same characteristics in your subscribers that we see in some of our successful clients.

It’s people who want to be collaborative, who are innovative—and I know those are big buzzwords—but it truly is part of their cultural ethos. These are organizations where safety has a seat at the table, where it has the ear of the C-suite, and where safety is viewed not as a fractional part of the business or something thought about on the side, but as an integral part of how they operate.

Explore how shared innovation helps organizations strengthen safety performance

What led your company to begin exploring a relationship with an EHS software provider?

Aanna: We’ve been associated with Benchmark Gensuite for several years. We had been following what Benchmark Gensuite was doing and were really impressed.

About three years ago, we engaged because we thought, “Here’s an organization that’s responding to industry trends and seems to be very collaborative with other organizations.”

We’re a technology alliance member of Benchmark, and what we’ve really focused on is how to solve problems for your subscribers and for our clients. The genesis of that started with our “My Voice Feature.”

Part of our technology enables frontline workers to see something and report it immediately through our wearable. One of your subscribers saw that this was possible and said, “Hey, what if we use this data from the frontline worker to automatically populate concern reporting? How amazing would that be?” That’s really what started our collaboration, and we’ve continued growing from there.

Is there an example that best illustrates the kind of risk wearable technology can uncover?

Aanna: Early on, we ran a pilot with a company, and they called us and said, “We think your system is broken. This just absolutely can’t be. There are two women whose only job is to move these big gallons from point A to point B every day, just back and forth. But the data is showing that they have high physical motion, and that this one part of their job is very physical, and we just don’t see it.”

I said, “Well, let’s observe—we want to come and see what’s going on.” What we discovered was that moving the barrels from point A to point B was not the physical part of their job. But the beauty of wearable technology is that you start to see things you otherwise wouldn’t see.

What they were missing was that before moving the barrels, these women had to wrench open one part of the barrel every day, and there was really high physicality and a high risk of an MSD. Our solution picked up on this unseen task that these workers did every day, something they weren’t complaining about, but that eventually was going to cause an MSD or another injury.

By identifying that risk, they got a motorized wrench to open the barrel, fell off the caution list, and were able to do the job without that risk anymore. I love this story because it speaks to those unseen risks and how we can help uncover them.

Learn how wearable technology helps teams act before injuries occur

What role do you see AI playing as EHS technology continues to evolve?

Aanna: We can provide such rich, robust data, and that really helps AI work. We can tell the story of what’s happening to workers—their exposures and experiences—and the amount of rich data that can go into these systems for AI to analyze and create meaningful recommendations and trends that make an impact on worker wellbeing is really exciting for us.

That’s what it comes down to, right? Caring about your frontline workers and making sure they go home safely every day. It’s great to be part of that journey.

Discover how AI helps organizations identify trends and act earlier on workplace risks

What stood out early in your relationship with Benchmark Gensuite that made the partnership feel like the right fit?

Aanna: I think that’s really what led us to partner with Benchmark Gensuite. From our first interactions with people at an ASSP conference or NSC show, to our co-founder sitting down with top leadership, everybody has been so kind, but also generous with their time and collaborative in innovative discussions.

When it comes down to it, our partnership is really about solving problems. It’s not just about being added to a long list of great vendors you have an association with, but really about how partner solutions support what your subscribers are trying to do. How does it fill that void? How does it support the overall goal of making work better for so many people?

Being associated with Benchmark is great; everyone here is lovely. This is a fun community.

Final Reflections: Making Safety Decisions Earlier with Better Data

Aanna Hoch’s experience highlights how the future of workplace safety depends on seeing risks earlier and acting on better information. Technologies that capture real-time exposure data—from wearable devices to integrated EHS platforms—give organizations a clearer understanding of what workers experience every day. When those insights are paired with partners who share the same focus on solving real operational challenges, companies can move beyond reactive incident response and toward proactive prevention. Ultimately, stronger data and collaborative innovation help organizations protect their workforce while making smarter decisions about how work gets done.

The post Partner Spotlight Q&A with Aanna Hoch, Director of Partner Ecosystem at MākuSafe appeared first on Benchmark Gensuite.

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In 2025, Benchmark Gensuite reached an important inflection point: Genny AI became natively enabled across every subscriber instance globally. This shift marks the transition from AI as an innovation initiative to AI as embedded operational infrastructure within EHS and Sustainability platforms.

For EHS and Sustainability leaders, the implications are significant.

Quantifying the Operational Impact of AI in EHS & Sustainability

Across 2025, enterprise usage of Genny AI generated:

• 187,855 AI-assisted interactions
• 13 minutes saved per interaction (observed average)
• 40,702 total hours returned to organizations

This equates to:

• 5,088 eight-hour workdays
• 1,017 workweeks
• 19.6 full-time employees’ worth of capacity

At a conservative enterprise labor rate of $45/hour, the productivity impact totals:

$1.83 million in annual enterprise value

These figures are not modeled projections. They reflect realized usage patterns across active customer environments using AI embedded within EHS management software.

For EHS and Sustainability VPs managing constrained budgets and expanding regulatory mandates, the takeaway is clear:

Embedded AI in EHS software can unlock enterprise capacity at scale without increasing headcount.

AI Adoption in EHS: A Structural Shift, Not a Trend

Efficiency gains alone do not define successful AI transformation. Sustainable digital transformation requires adoption depth across operational teams.

In 2025:

• Total AI interactions increased 13% quarter-over-quarter
• Average AI interactions per user grew 16%

This growth signals more than curiosity — it indicates operational reliance on AI tools.

When frontline safety teams, environmental managers, compliance professionals, and sustainability leaders increase AI usage organically, it demonstrates integration into core workflows, including:

• Incident investigations
• Risk assessments
• Compliance documentation
• Corrective action tracking
• Sustainability and disclosure reporting
• Audit preparation

For executive leadership, adoption velocity serves as a leading indicator of durable enterprise AI value.

Why Embedded AI Outperforms Add-On AI Models in EHS Software

Many AI initiatives in Environmental Health & Safety remain fragmented — pilot programs layered onto legacy systems that require:

• Additional integrations
• Separate change management efforts
• Incremental funding approvals
• Isolated deployment cycles

Genny AI was architected differently.

1. Native Enablement Across All Subscriber Instances

• Enabled globally by default
• No upgrades or custom integrations required
• No separate deployment cycles

This removes a common barrier to enterprise-scale AI adoption: uneven rollout across sites, regions, or business units.

2. Broad Coverage Across EHS & Sustainability Workflows

Today, the platform includes:

• 80+ integrated AI capabilities
• Embedded AI support across:
  • Incident management
  • Risk assessments
  • Compliance documentation
  • ESG reporting
  • Supplier sustainability workflows
  • Quality management processes
• Agentic AI applications supporting multi-step compliance and sustainability workflows
• Advanced AI capabilities including computer vision, safety risk AI, video analytics, and wearables integration

The strategic implication:

AI delivers the greatest enterprise value when it spans the full EHS and Sustainability operating model — not isolated use cases.

Reframing the Role of AI in EHS Leadership Strategy

For many EHS and Sustainability VPs, the challenge is not automation for its own sake. It is balancing:

• Expanding regulatory complexity
• Increased sustainability disclosure requirements
• Heightened operational risk visibility
• Growing stakeholder scrutiny
• Persistent resource constraints

Unlocking nearly 20 FTEs of capacity does not simply reduce cost. It enables strategic redeployment toward higher-value initiatives, including:

• Proactive risk mitigation
• Data-driven safety improvements
• Faster corrective action cycles
• Advanced sustainability analytics
• Strategic program design instead of manual data consolidation

AI in EHS becomes less about task automation and more about strategic bandwidth and enterprise resilience.

Market Validation: AI in EHS Is Becoming Table Stakes

A recent industry survey of 260 EHS leaders found that 92% report using generative AI. The competitive landscape has shifted. AI adoption in EHS and Sustainability software is quickly becoming table stakes.

However, adoption alone does not create differentiation. Integration does.

Verdantix recently recognized Benchmark Gensuite as an Industry Pacesetter for AI Integration in EHS Software, citing its embedded, platform-wide AI strategy.

For EHS leaders evaluating AI vendors, this distinction matters:

• Disconnected AI tools create operational friction.
• Embedded, platform-wide AI creates systemic advantage.

From AI Feature to AI Infrastructure

The 2025 global rollout of Genny AI represents a structural milestone:

Every Benchmark Gensuite subscriber now operates within an AI-enabled EHS and Sustainability environment.

This design ensures:

• Consistent AI access across geographies
• Standardized productivity gains
• Scalable value across EHS, Sustainability, Quality, and Risk
• Reduced IT and implementation complexity

AI is no longer a feature to evaluate.

It is part of the operating backbone of modern EHS and Sustainability management systems.

Key Questions for EHS & Sustainability VPs Scaling AI

As AI maturity accelerates, leadership teams should consider:

1. Where is manual effort still constraining strategic progress within EHS and Sustainability programs?
2. Are AI capabilities embedded directly into daily operational workflows, or operating at the margins?
3. Is AI delivering measurable, enterprise-level productivity gains?
4. How quickly can AI capabilities scale globally without additional IT burden?

Organizations that answer these questions effectively will convert AI from incremental efficiency into durable operational advantage.

The Bottom Line: Enterprise AI Value in 2025

In 2025, Genny AI delivered:

• $1.83M in annual productivity value
• 40,700+ hours returned to customers
• Nearly 20 FTEs of capacity unlocked
• Double-digit engagement growth
• Platform-wide native enablement

For EHS and Sustainability leaders navigating regulatory complexity, ESG disclosure pressure, and operational risk, embedded AI is emerging as a lever not only for efficiency — but for resilience, scalability, and strategic agility.

The next frontier is not adopting AI in EHS.

It is operationalizing AI at enterprise scale.

The post Scaling AI in EHS & Sustainability: From Pilot Programs to Enterprise Value appeared first on Benchmark Gensuite.

Scaling Safety with AI: How Modern EHS Management Software Supports Growing Operations

For John Barlew, Vice President of Safety with Kenco, safety has never been a static program; it’s a moving target shaped by growth, people, and the realities of day-to-day operations. Leading safety for a large, fast-paced logistics organization means navigating constant change: new facilities coming online, new employees joining the workforce, and evolving customer and regulatory expectations. Each shift brings new challenges and operational risks that can’t be managed with yesterday’s tools or approaches.

As the company expanded, John saw firsthand how traditional processes began to strain under the weight of that growth. What his team needed wasn’t just another piece of software, but a partner that could keep pace with their operations, support frontline teams, and turn safety data into clear, practical action. His experience reflects a broader truth across the logistics industry: when the environment moves fast, safety strategies must evolve just as quickly.

Key Takeaways from John Barlew for Modern Safety Programs

• Growth reshapes risk—fast-moving operations require safety strategies that evolve alongside new facilities, new employees, and changing customer expectations.
• AI turns observations into action—tools that analyze tasks and generate clear recommendations help teams move quickly from insight to real operational improvements, generating ROI for operations, employees, and customers.
• Partnership matters as much as technology—the right safety provider supports implementation, aligns with company values, and helps scale programs with confidence.
• Engagement is the foundation of performance—real-time visibility into training, reporting, and participation helps build a culture where every employee contributes to safer outcomes.

What factors matter most when selecting a safety management software for a growing organization?

John: I had worked with Benchmark previously at another employer, and we began the diligence phase of choosing a safety management partner for Kenco in late 2023. We evaluated five or six different software providers and ultimately selected Benchmark.

I look closely at the character of the team representing the solution, in addition to the product itself. From start to finish, and continuing today, Benchmark’s team has aligned well with the principles and character of our organization. Every step of the process, we’ve been supported and treated as true partners, and that played a major role in our decision.

The technology roadmap, artificial intelligence capabilities, and data functionality are all top-notch. Kenco is growing quickly, acquiring businesses, and operating on a fast-paced roadmap. Benchmark is the right partner to help us continue our safety journey and advance toward safety excellence.

Learn how the right safety management partner can support growing operations.

How significant are musculoskeletal injuries in warehousing and what challenges do they create for organizations like Kenco?

John: In warehousing and logistics, the number one cause of injury is soft-tissue musculoskeletal injuries. We’re not immune to that. Beyond serious injury and fatality prevention, minimizing ergonomic risk factors is a major focus area.

The issue is so widespread that in 2022, OSHA announced a National Emphasis Program on warehousing due to high recordable injury rates, primarily related to ergonomics.

Having a solution that we can put into the hands of corporate safety staff and site leaders allows us to address these risks directly. It provides a quantitative tool and clear recommendations for reducing risk factors. That will enable significant injury reduction and knowledge creation across the organization.

I’m excited to see how we use this tool over the next year and how it drives action tracking and continuous improvement across our safety management system.

Can you share an example of how technology—specifically AI—has helped your team address these challenges?

John: Our sales representative provided a trial of Ergo Evaluator with 3motionAI. Around that time, we acquired a nationwide logistics network for a medical provider in our Life Sciences Division. One of the tasks required overhead lifting because of how the product was stacked in the trailers.

By deploying the tool with one of our corporate specialists on site, we were able to quickly analyze the task, run the AI, and generate a report. We shared that report with internal and external stakeholders, and it immediately led to commitment from both the customer and Kenco leadership to improve the task. It also triggered financial investment from both parties to engineer the ergonomic risk factors identified in the report.

A one-minute video led to a long-term investment. It demonstrated Kenco’s ability to provide an ergonomic solution that benefited our bottom line while improving the customer’s safety performance. The solution is driving knowledge sharing and training opportunities at the floor level, while also promoting financial value and ROI for both Kenco and our customer providers.

See how AI-powered ergonomic analysis helps turn observations into measurable improvements.

How are you planning to scale these ergonomic and AI-driven insights across the organization?

John: We’re planning to launch Ergo Evaluator across the corporate team this year. With a thousand AI generations included in the agreement, I can’t even imagine what we’re going to achieve as a result of deploying that module.

What role does the implementation process play in building trust between safety teams and software providers?

John: From the beginning, the sales team was engaged, responsive, and transparent about timelines and the implementation schedule. They also provided guidance on structuring our hierarchy for legal reporting and maximizing the software’s capabilities.

We’re unique in that we don’t have safety managers at every location. Instead, we rely on operations leaders who wear multiple hats. Having a solution they can easily access—where they can submit information, receive reminders, and work from a clean dashboard—makes their lives easier. It also improves efficiency, reliability, and overall system adoption.

From the initial RFP process through implementation, our sales implementation manager, Anthony, has been outstanding—realistic, responsive, and organized. We met our implementation timeline, and the deployment of all modules has gone according to schedule. For our IT team to speak positively about a SaaS provider says a lot.

Discover why a strong implementation approach supports long-term safety success.

In what ways do workforce changes reshape the way you approach safety engagement across Kenco’s operations?

John: The warehousing industry is very fast-paced, and after the pandemic there was a significant surge in demand. Many companies that previously operated their own fulfillment centers moved to third-party providers like Kenco.

The workforce has also changed. We now have many inexperienced, first-time warehouse employees entering the workplace, which creates unique safety risks. Having a tool like Benchmark allows employees to report concerns if they don’t fully understand a process. With Training Tracker, we can see who is meeting compliance requirements and safety standards. We also engage employees through committees, events, and learning teams that we track in the system.

Engagement is a major part of our safety culture and strategy. We’ve set a goal of 100% associate engagement, and with Benchmark’s insights reporting, I can see at any moment how we’re performing against our targets. That ability to provide real-time data to leadership is extremely valuable.

Final Reflections: Rethinking Safety for Evolving Work Environments

John Barlew’s experience highlights how fast-growing operations need safety strategies that evolve just as quickly. By combining AI-driven insights with a trusted implementation partner, organizations can move from reactive processes to proactive, data-informed action. For Kenco, the right technology isn’t just about efficiency—it’s about enabling frontline teams, strengthening engagement, and driving measurable improvements across every facility as the business continues to grow.

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In industries that rely on hazardous materials, maintaining accurate and up-to-date Safety Data Sheets (SDS) is essential. These documents support chemical evaluations, employee training, and regulatory preparedness. When SDS records are missing, outdated, or inconsistent across sites, compliance risks increase—especially during inspections, audits, or incident response.

The challenge is not expertise, but scale. Chemicals enter facilities through multiple channels, suppliers update SDS versions over time, and requirements extend across hazard communication, training, and reporting. Keeping records current, verified, and accessible across every location demands continuous coordination.

As a result, SDS management often becomes reactive. Teams spend hours searching for documents, validating versions, and answering compliance questions—diverting time from proactive safety and risk management efforts.

Making SDS Reviews Faster, Clearer, and More Consistent with Autonomous AI Agents

Traditional SDS management depends on manual collection, storage, and periodic review of documents. Teams compare versions, identify changes, and assess new hazards, often repeating the same work across multiple sites. This approach increases the risk of inconsistencies, missed updates, and limited visibility.

As a result, version discrepancies can go unnoticed, regulated substances may require additional review, and responding to compliance or audit questions often means time-consuming document searches.

Autonomous AI Agents streamline this process by continuously analyzing SDS documents within existing workflows. As files are added or updated, agents identify hazards and regulatory considerations and structure the information into clear, actionable insights—shifting SDS management from reactive review to ongoing operational support.

Learn more about Genny AI Automation Agents and how they streamline complex workflows.

Want to learn more about Genny AI Agents? Read our Permit Agent blog to see how autonomous agents are also transforming permit compliance and explore additional capabilities across the Genny AI Agentic Hub.

How Does Genny AI SDS Agent Work?

The Genny AI SDS Agent begins working as soon as SDS documents are introduced into the system. Built directly into Benchmark Gensuite’s SDS and chemical management workflows, it follows a structured, repeatable process:

1. Upload and analyze SDS documents

   Safety Data Sheets are uploaded into the platform, where the Agent reviews them line by line to extract chemical data, hazards, safety measures, and risk mitigation information embedded in complex documentation.

2. Verify versions and detect changes

   The Agent compares SDS versions to confirm accuracy, identify updates, and detect changes over time—supporting consistent version control and reducing the risk of outdated or incorrect records across sites.

3. Structure chemical information into clear summaries

   Key details are organized into standardized chemical synopses that highlight hazards, precautions, and critical safety considerations, making SDS information easier to review and understand.

4. Identify regulated and high-risk substances

   Chemical constituents are analyzed against relevant regulatory lists to flag substances that require closer review, supporting transparency and consistency in chemical compliance efforts.

5. Integrate insights into SDS workflows

   Structured SDS information connects directly with the Benchmark Gensuite SDS System and related chemical management workflows, keeping records current, accessible, and aligned across the organization.

Changing Day-to-Day for EHS Leaders

By automating SDS review and verification, the Genny AI SDS Agent introduces a new kind of digital co-worker for EHS teams—one that continuously supports chemical safety management by handling document-heavy, repetitive work without removing people from the process.

Instead of spending time searching for SDS files, validating versions, or responding to compliance questions under pressure, teams gain consistent visibility into chemical hazards, safety measures, and documentation status across sites. This leads to fewer last-minute escalations, clearer oversight, and greater confidence during audits, inspections, and incident response.

Built to work alongside EHS professionals, the SDS Agent strengthens day-to-day operations while keeping judgment, accountability, and decision-making with the people responsible for protecting workers and ensuring compliance. With a reliable digital co-worker managing SDS complexity in the background, EHS leaders can focus more time on prevention, oversight, and continuous improvement.

See the Genny AI SDS Agent in action.
Explore how SDS management moves from manual review to structured insight—helping EHS leaders stay proactive, confident, and compliant across every site.

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Managing environmental and operating permits is one of the most time-intensive responsibilities for enterprise EHS teams. Across sites, permits arrive regularly and introduce obligations that must be identified, interpreted, and tracked accurately. When this process breaks down, the impact goes beyond missed deadlines or inconsistent execution; it increases compliance risks and limits visibility across the organization.

For EHS leaders, permit management often becomes reactive, draining time and resources from higher-value work. The challenge is not expertise, but the volume, complexity, and manual effort required to convert permits into actionable compliance tasks—an approach that becomes increasingly difficult to sustain as organizations scale.

From Manual Reviews to Autonomous AI Agents

Manual permit reviews rely heavily on individual interpretation, time availability, and local processes. Teams often spend hours reviewing PDFs line by line, identifying conditions, tracking renewal dates, and updating calendars. When this work is repeated site by site, inconsistencies emerge. What EHS teams need is not another tool that adds steps to the process, but a way to operationalize permit requirements at scale—without increasing administrative burden.

AI Agents address this need by working within established compliance workflows, continuously processing permit information and taking defined actions on behalf of the team. For multi-site EHS programs, this means permit requirements move directly from documents into execution—tracked, assigned, and monitored without manual intervention.

Learn more about Genny AI Automation Agents and how they streamline compliance workflows.

How does Genny AI Permit Agent actually works?

The Genny AI Permit Agent begins working the moment a permit document is uploaded. Built directly into the Benchmark Gensuite platform, it operationalizes permit compliance through a clear, repeatable workflow:

1. Upload and analyze permits
   Permit documents are uploaded directly into the platform, where the Agent reviews them line by line, identifying regulatory requirements, citations, conditions, and due dates embedded in complex language.
2. Structure requirements into action
   Each obligation is translated into clear, trackable compliance tasks. Untracked items are surfaced, accountability can be assigned, and requirements are standardized across sites.
3. Sync and operationalize compliance
   Tasks are automatically synchronized with the Compliance Calendar and Permit Manager solutions, ensuring deadlines, renewals, and conditions remain visible and managed.
4. Prepare for audits and escalation
   The Agent generates site-specific audit protocols and escalation workflows, supporting consistent oversight and audit readiness across the organization.

Changing Day-to-Day Compliance for EHS Leaders

By automating permit compliance, the Genny AI Permit Agent changes how EHS leaders manage risk daily. Instead of spending time reviewing documents, tracking obligations, and validating updates, teams gain consistent visibility into permit requirements and their status, while reducing the manual effort required to keep programs on track.

The result is fewer last-minute surprises, clearer accountability, and greater confidence during audits and inspections. Designed to work alongside EHS professionals, the Permit Agent acts as a digital co-worker that manages document-heavy, repetitive tasks, allowing teams to focus on prevention, oversight, and continuous improvement. Our Agent is designed to help teams operate more efficiently, while decision-making and accountability stay firmly with those responsible for protecting operations and ensuring compliance.

See the Genny AI Permit Agent in action.
Schedule a demo to see how permit compliance moves from upload to action in minutes, helping EHS leaders stay proactive, confident, and audit-ready across every site.

The post From Manual Reviews to Autonomous AI: Simplifying Permit Compliance for Enterprise EHS Teams appeared first on Benchmark Gensuite.