AI 101: Smarter Tech, Safer Workplaces
Chris Skipper
March 4, 2025AI tech can be sorted into four categories, and each of them comes with game changing applications in workplace safety.
This is the first blog post in a series we’re calling AI for Safety Pros. For the next few months, Voxel will be hosting webinars with other Artificial Intelligence and Workplace Safety experts to help demystify AI and get to the heart of how it can help safety professionals.
Like any 101 level course, our first post and webinar cover the basics. We define artificial intelligence, break down the different kinds of AI, and provide a primer on the tools, techniques, and trends shaping the future of workplace safety.
You can watch the webinar here.
What is Artificial Intelligence?
At its core, artificial intelligence is the science of making machines perform tasks that typically require human intelligence. AI is behind innovations you probably use every day; tools such as facial recognition on smartphones and recommendations on streaming platforms. Now I understand how Netflix knew I wanted to start Grace and Frankie after I finished Bridgerton ;) .
In the context of safety, AI’s ability to process and interpret large volumes of data rapidly makes it a true game changer. It can detect patterns we can’t see, and it can offer fixes and interventions nearly as soon as it identifies dangerous patterns.
Artificial Intelligence is the science of making machines do things that would require intelligence if done by humans.” – Marvin Minsky
Types of AI & Their Role in Workplace Safety
We can sort Artificial Intelligence into four main categories. Each plays a unique role in enhancing safety:
Machine & Deep Learning:
Machine Learning (ML) is powered by digital neural networks: a complicated interconnected series of processors that mimic the complexity of the way neurons fire in our brains. These systems learn from historical data and make predictions based on that data.
When applied in safety, ML can find the highest risk areas in a workplace by identifying patterns of near-miss incidents and predicting where risks might emerge next.
Robotics:
Robots equipped with AI reduce human exposure to hazards by performing dangerous and often repetitive tasks. While it’s true that robotics have been a common feature in the industrial workplace for some time, new advances in artificial intelligence allow them to be an even greater help.
Swarm intelligence allows multiple robots to communicate and adjust their actions in real time, collaboratively managing complex operations. This allows them to avoid colliding, maintain safe paths, and coordinate to safely achieve tasks greater than could be accomplished by any one robot acting on its own.
GenAI & Natural Language Processing (NLP):
When most people think about AI today, this is what they think of. GenAI and NLP include ChatGPT, help bots, image generators, and language translators. These systems understand and generate human language or images, enabling the creation of detailed reports and visual analytics. As a fun example, I asked an AI image generator to create an AI powered superhero called “CaptAIn Safety”...see what I did there…pretty cool right? Also what is with the spider?!?…a reminder to always check the AI output before sharing!
This form of Artificial Intelligence can quickly synthesize raw data into easy-to-read actionable insights, takeaways, and suggestions. While there are widely available online platforms for this technology, we highly recommend using secure internal tools in order to minimize the risk of any private data becoming public.
To show the interpretive power of large language models we loaded thousands of rows of near miss and reported hazard data into Chat GPT. We then asked it to interpret the data and provide us with a chart that showed the top 10 unresolved safety issues, seen below. This is a simple example as tools like Chat GPT are capable of more advanced analytics, such as regression analyses.
Computer Vision:
Perhaps the most transformative for safety, computer vision interprets and processes visual data. It recognizes faces, objects, and behaviors. This recognition allows it to detect hazardous patterns such as improper ergonomics, unsafe pedestrian behaviors, and forklift traffic patterns. Computer Vision shifts safety management from reactive to proactive and even predictive, all while using existing security and CCTV cameras.
Let’s dive deeper into this game-changer for workplace safety…
Spotlight on Computer Vision: Proactive and Predictive Safety
Amongst the different applications of AI, computer vision stands out as a vital tool for safety professionals. Here’s how it’s reshaping workplace safety:
Dynamic Risk Identification
- Continuous Monitoring:
By leveraging existing security cameras, computer vision systems provide 24/7 operational visibility . It identifies unsafe behaviors—such as overreaching, improper bending, and failure to wear appropriate PPE—ensuring that risks are detected in real time.
In this case, computer vision identified a worker at risk of falling from an unsafe height. This worker is in a no pedestrian zone and is not wearing standard PPE. Without computer vision, the odds are that this off-hours risky behavior would have never been discovered.
- Proactive Interventions:
Instead of waiting for an incident to occur, these systems analyze patterns to predict where and when hazards might arise. This predictive capability allows for timely interventions, effectively shifting safety from a reactive to a proactive discipline.
Eliminating Bias and Enhancing Control Verification
Objective Assessment:
Unlike human observers, AI doesn’t bring personal bias into safety observations. For example, whether a forklift is being operated by a new hire, manager, or the CEO’s son, computer vision consistently flags critical risks. This means failures to stop at intersections are identified no matter who is driving, ensuring fair and accurate risk quantification.
Streamlined Verification:
Automated control verification replaces labor-intensive manual inspections and data collection. This not only saves time but also ensures that effective safety controls are consistently implemented across all shifts, including off-hours.
Operational Integration and Analytics
Seamless Deployment:
Designed to integrate with most CCTV systems, many computer vision platforms can be up and running within 48 hours. This scalable architecture allows businesses to expand the system as needed without significant hardware investments.
Actionable Insights:
Aggregated data is transformed into dashboards, heat maps, and dynamic reports, pinpointing high-risk areas and trends. These insights drive informed decision-making, and continuous improvement in safety practices.
Overcoming Barriers to Entry
While there are clear and exciting benefits of implementing AI in workplace safety, companies must overcome barriers to entry before adding artificial intelligence as a tool in their safety arsenal.
Some of the most common concerns surround privacy and data security. Ensuring employee privacy is critical. It is important to choose AI solutions that are built with stringent data security protocols to safeguard sensitive information. Voxel is Soc 2 Type II Compliant, which is the highest industry standard for data security.
Employees may also worry about “Big Brother” watching them, a common concern that must be addressed. It’s important that these technologies are implemented to enhance safety rather than as tools for punitive surveillance. Transparent communication with employees about goals and limitations help mitigate fears of invasive monitoring. The goals are safety and wellbeing, and the limitations are that the cameras will not be used to single out or punish individual employees.
Hardware and cost considerations are a reality as well. Voxel’s site intelligence platform utilizes existing security infrastructure, reducing the need for extensive new hardware. However, costs related to upgrades, maintenance, and ongoing support must be carefully evaluated.
Actionable Steps for AI Implementation in Safety
When considering AI implementation, companies must take actionable steps. We like to break these steps into three phases.
Assess Readiness:
- Define safety challenges and goals
- Evaluate current processes and identify gaps
- Secure stakeholder support
Evaluate & Select Solutions:
- Research and prioritize solutions
- Request demos and proofs of concepts
- Develop a conservative business case and explore potential ROI
- Consider IT requirements
Implement & Monitor:
- Develop a strategic plan that assesses goals and challenges
- Train staff and communicate the benefits of the new system
- Monitor performance, gather feedback, and adjust protocols as necessary
- Evaluate data and feedback
- Scale the solution and expand based on demonstrated improvements
The Future of Safer Workplaces
Embracing AI is not just a technological upgrade—it’s a paradigm shift in safety management, and there is no turning back. Some safety professionals fear AI will take their jobs, but the more immediate risk is losing out to those professionals who embrace AI to work more efficiently and effectively. AI transforms data into actionable insights that protect employees and streamline operations. The journey from reactive to proactive, and ultimately predictive, safety management is already happening at many companies around the world. Our Case Studies are full of excellent examples.
By investing in AI-driven safety tools, your organization can accelerate continuous improvement and make a powerful commitment: prioritizing the well-being of every employee while driving operational excellence.
Get in touch with us today if you’d like to know more about how Voxel can help revolutionize your workplace safety operations. And make sure to look out for our next webinar… AI 201 for Safety Pros.