What EHS Leaders Need to Know About the Rise of AI
- Shoyab Ali
- 6 days ago
- 8 min read
Once seen as a futuristic luxury, Artificial Intelligence (AI) is now becoming the standard for workplace safety, especially in high-risk sectors like construction, oil & gas, mining, and heavy manufacturing.
As protecting frontline workers becomes more complex and compliance becomes stricter, EHS (Environmental, Health, and Safety) leaders are turning to AI to stay ahead.
But what exactly does AI mean for EHS?
How does it impact daily site operations, inspections, and emergency response?
This blog dives into the five core insights EHS leaders must understand about the rise of AI and how it's changing safety monitoring, from the ground up.
What is the Role of AI in EHS?
AI plays the role of a silent safety partner—always watching, learning, and acting. It augments human efforts by automating detection, improving decision-making, and anticipating risks before they happen.
In EHS, an AI-powered system ensures that incidents are not only tracked but also predicted and prevented, all while minimizing the burden on human teams.
From PPE compliance and behavior detection to proximity alerts, AI transforms static data into live intelligence. It bridges the gap between awareness and action, making safety more personalized, site-specific, and real-time.
Whether through the hidden benefits of IoT in EHS management or precision of video analytics, AI helps create a connected, responsive safety ecosystem.
Why do EHS Leaders Need AI?
The industrial worksites have evolved, but many safety systems haven’t. Traditional monitoring methods, even today, rely heavily on manual reporting, delayed incident reviews, and static CCTV systems that capture but don’t analyze.
Advanced technology involving AI, such as video-based analytics for workforce safety, computer vision integration and even the upgrade of cameras on site to AI CCTVs, brings a proactive, predictive, and precision-driven approach to safety.
Comparing Safety: Before vs. After AI
EHS Scenario | Before AI | After AI Integration |
Protocol Monitoring | Random spot checks, high chance of oversight | Automated, real-time detection & logging |
Incident Response | Manual reporting, often delayed | Instant alerts with automated escalation |
Safety Audits | Monthly/quarterly, labour-intensive | Live dashboards with trend tracking |
Access Control | Card/manual checks, error-prone | Facial recognition & permit-based AI validation |
AI doesn't just optimize workflows—it revolutionizes how safety is practiced at every level.
5 Things EHS Leaders Must Know About the Rise of AI
As AI takes charge of transforming safety in the EHS management of high-risk industrial sites, the leaders in 2025 must know the following aspects to know what to look for in a video analytics EHS software solution.
1. AI Doesn’t Replace Safety Officers—It Supercharges Them
AI, often mistaken as a replacement for humans, acts only as an ever-present assistant for EHS teams, scanning every zone and every activity around the clock. Instead of replacing human insight, AI strengthens decision-making by providing evidence-based recommendations and detecting violations before they escalate.
For instance, PPE detection modules monitor workers for missing or improperly worn safety gear, while danger zone monitoring modules ensure restricted areas are accessed only by authorized personnel.
In fact, in a Hong Kong-based infrastructure project, the use of an AI video analytics based safety platform led to a 53% drop in their Total Recordable Incident Rate (TRIR) in just 90 days. This wasn’t achieved through more manpower, but by deploying automated alerts and violation trend reports that allowed faster follow-up.
This is where the power of integration lies—AI doesn't eliminate the human element, it enhances it.
2. Behavioral Safety is Now Measurable—and Fixable
One of the most unpredictable areas of safety detection is the estimation of worker behaviour. It is almost impossible to judge where the worker is heading next or if his sleep-deprived body would collapse in the next task.
AI now allows EHS managers to quantify such behavior, a task once seen as purely observational. Using computer vision, AI can identify signs of fatigue, distraction, or unsafe habits in real-time.
Workers using mobile phones while walking in operational zones, repeated bending or lifting with improper posture, and lingering near moving machinery can all be flagged and addressed.
At a large logistics hub in the Middle East, deployment of a behavioral AI module flagged frequent phone usage during crane operations. Post-intervention, behavioral alerts reduced by 45% and crane-related safety events dropped by nearly 38%, proving how AI turns behavioral trends into actionable safety decisions.
By closing the gap between observation and intervention, AI ensures unsafe behavior is addressed long before it becomes an incident.
3. Real-Time Dashboards Lead to Real-Time Action
The use of EHS analytics offer dashboards that provide site-wise and shift-wise insights—available anytime, anywhere. These dashboards aren’t just for display—they help prioritize risk mitigation strategies based on data.
Quick Case Insight:
A major contractor in Southeast Asia implemented viAct’s multi-site centralised dashboard across six projects. Over two quarters, they observed a 41% drop in near-miss reports and a 24% improvement in emergency response time.
Supervisors began using safety heatmaps to reallocate safety marshals to critical zones, dramatically improving worker safety and trust. |
4. AI Doesn’t Just Detect—It Predicts
One of AI’s most transformative powers is its ability to forecast risk. By analyzing historical trends, weather patterns, shift timings, and task types, AI systems offer risk scores and suggest pre-emptive actions.
If certain violations spike during afternoon shifts or rainy days, AI alerts supervisors in advance, who can then modify schedules, brief workers, or pause high-risk work.
For instance, during an airport terminal expansion project in Southeast Asia, AI-powered monitoring was linked to real-time air quality and wind sensors. When particulate matter rose above safe thresholds during concrete cutting, AI triggered machine shutdowns and sent automatic alerts to EHS managers.
This quick action prevented both respiratory risks to workers and potential work stoppages due to safety violations, saving an estimated $520,000 in lost hours and regulatory fines.
AI transforms safety from a reactive process into a forward-looking strategy.
5. Scalable Safety: AI Grows with You
The modern AI-based safety systems are designed to scale. Whether the operation is at one site or extends to ten, AI systems integrate with your existing camera infrastructure (via RTSP) and grow as the operations expand.
With an option for on cloud, On-Prem or hybrid deployment, AI delivers both local and global visibility.
A leading infrastructure company in the UAE connected five worksites through a unified AI dashboard. Each site had its detections and alerts, but all data were centralized for leadership review.
According to the EHS Head, “We get alerts from all five sites instantly—without delays or overload. It’s like having a safety control tower.”
Whether you’re running a pilot or scaling globally, AI provides consistent, connected safety intelligence across your operations.
What EHS Leaders Should Know Before Deploying AI
Before diving into AI deployment, EHS leaders must prepare to integrate it as a continuous improvement tool, not just a surveillance upgrade.
Here are key considerations that can make a difference:
1. Start with a Clear Purpose: Define What You Want AI to Solve
AI is most effective when deployed with a focused, measurable objective. Instead of starting with a general intention like "let’s try AI,” begin by asking questions like:
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For example, if delayed incident responses are major concerns, you might start with AI-powered instant alerting systems consisting of site wide buzzers with notifications via WhatsApp, text and email. A contractor in Singapore used this approach to focus on reducing near misses in crane zones, which led to a 38% drop in zone violations within a quarter.
2. Don’t Automate Without Accountability
AI is a powerful co-pilot, but the final decision must always rest with trained EHS professionals. It’s critical to treat AI as a decision-support tool, not a replacement for human judgment.
In safety-critical environments, ethical deployment matters. Workers should understand how AI supports them, not surveils them. Briefings, Q&A sessions, and transparency on how detections work help improve adoption and reduce resistance.
One logistics company in Dubai made AI part of their daily toolbox talk. Over time, workers started relying on AI alerts as “second eyes,” reporting that it felt like having a personal safety coach, not a watchdog.
3. Know Your Data and Organize It Well
AI is only as powerful as the data it can learn from. If your safety reports, shift logs, or incident records are scattered across spreadsheets, emails, and paper logs, the first step is to consolidate them. Consider:
What data is currently available?
Where is it stored?
Is it structured enough to train AI models or generate insights?
A food & beverage unit in Europe took 6 weeks to streamline historical safety data before deploying predictive analytics. As a result, their AI dashboard now forecasts peak risk hours daily based on historical compliance patterns.
The Future of EHS is Intelligent, Predictive, and Proactive
AI deployment in industrial areas has taken the shape of a powerful tool transforming the DNA of EHS management. From reducing violations to building a stronger safety culture, it equips teams with the tools they need to prevent, protect, and perform.
As the challenges of compliance, cost, and complexity grow, so must our tools. EHS leaders who embrace AI today are setting a foundation for smarter, safer, and more sustainable operations tomorrow.
AI makes safety not just a protocol, but a proactive force.
So, the question isn’t if AI will become essential to EHS—it’s how fast you’re ready to implement it.
Quick FAQs
1. Is the process of EHS video analytics deployment easy?
Yes. Most modern AI video analytics systems—like viAct’s are designed for seamless plug-and-play deployment using existing CCTV infrastructure.
Here’s how the process typically works:
Step 1: Connect your IP/CCTV feeds via RTSP.
Step 2: Choose your detection modules (e.g., PPE, Fall Detection, Danger Zone Intrusion).
Step 3: Go live with on-prem or cloud-based AI monitoring.
In most cases, pilot deployment can begin within 2–5 days, with full rollout possible in under two weeks—no major hardware overhaul required.
2. How accurate are the AI detections for EHS compliance?
AI-powered detections can achieve accuracy levels above 95%, depending on camera quality, lighting, and configuration.
For example, viAct’s AI detected safety violations with 96.3% precision at a high-risk tunnel construction site in Hong Kong, helping reduce non-compliance by over 50% in under 3 months.
The system is also continuously retrained with real-world site footage, so detection accuracy improves over time.
3. Can I customize detections to suit my site’s unique EHS needs?
Yes. Most AI video analytics platforms offer customizable options to match the exact risks and regulations of your site.
You can customize:
The type of violations to monitor (e.g., harness use, reflective vests, zone entry)
Detection zones and priority areas (e.g., crane paths, loading bays)
Alert formats (buzzers, WhatsApp, SMS, email)
Language preferences for multilingual EHS teams
4. Can AI video analytics support multi-site EHS monitoring?
Absolutely. AI-based EHS systems like viAct’s offer centralized dashboards that allow leaders to monitor multiple worksites across cities or even countries in real-time.
Each site has:
Its own detection modules and alerts
A site-specific safety scorecard
Zone-wise heatmaps and trend reports
All data is then rolled up into a central Safety Command Center (SCC) dashboard.
“With all five projects on one screen, we catch issues in minutes—not days. It changed how we manage safety across locations.” —EHS Director, Infrastructure Giant, Southeast Asia
5. How does AI video analytics for EHS protect worker privacy?
AI systems like viAct’s include face blurring to anonymize workers while still detecting safety violations. In a Singapore infrastructure project, viAct’s real-time face blur feature helped meet strict privacy regulations. The site achieved 100% detection accuracy while preventing any storage of identifiable footage—resulting in zero privacy complaints over 18 months.
It also effectively complies with global privacy regulations like GDPR along with local requirements based on its operations across places like Hong Kong, Singapore, Saudi Arabia, United Arab Emirates (UAE), Qatar, Oman, Bahrain, Kuwait, and other GCC and Middle East markets, as well as India, Southeast Asia, Australia, Europe, and North America.
Not sure where to begin the industrial EHS monitoring journey with AI?
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