Are You Ready for AI-Based Safety Video Monitoring?

Introduction

One of the most frequent questions I hear from customers is: “How do we know if we’re ready for AI-based safety video monitoring?” This important question speaks to the heart of a company’s safety culture, and the answer lies not only in technology but also in the maturity of your organization’s safety culture. A technological solution is only as effective as the environment in which it’s deployed. To guide organizations in evaluating their readiness, I use a variant of the Safety Culture Ladder by Dr. Patrick Hudson, that I call the AI Data Safety Ladder. This framework helps determine where a company stands in terms of safety culture and data usage, and whether they’ll benefit from adopting advanced AI technology for safety monitoring. This model illustrates how a company’s safety culture and its relationship with data evolve over time — and how that progression aligns with AI adoption.

A Guide Using the AI Data Safety Ladder

Let’s walk through the stages of this ladder, to see where your company might fit and what that means for your AI-readiness.

1. Pathological Stage: Head in the Sand

At this level, companies operate with a "don't ask, don't tell" mindset when it comes to safety data. In the pathological stage, safety is often seen as a nuisance or a box to check. Companies at this level tend to bury their heads in the sand, much like an ostrich, and prefer not to know too much about safety issues. Why? Because there’s a fear that too much information could be used against them — whether by regulators, stakeholders, or even internally, rather than as a tool for improvement. In this "ostrich with its head in the sand" stage, the company’s leadership avoids delving deeper into safety concerns, fearing potential consequences of exposing flaws or risks. Are you ready for AI-based safety video monitoring?

AI Readiness: Not ready. AI-based monitoring requires a willingness to engage with data honestly and openly. For companies at this stage, AI-based safety monitoring isn’t the solution, because the issue isn’t a lack of technology. The issue is a resistant safety culture. Until the mindset shifts toward embracing safety as a priority rather than something to avoid, introducing AI won’t provide much value. The focus here should be on evolving the culture first. They need to work on fundamental safety principles before even considering AI.

2. Reactive Stage: After-the-Fact Fixes

Organizations in the reactive stage are generally motivated by incidents. They tend to gather and review safety data, but only after an accident or near-miss has occurred. At this stage, cameras and data may already be in use, but only to understand what went wrong after an incident. While these organizations are making efforts to improve, they’re still missing key opportunities for prevention.

AI Readiness: Selectively. While these companies still need to improve their safety culture, there are certain areas where AI could offer immediate benefits. If, for instance, they struggle with specific recurring issues or near misses — like personal protective equipment (PPE) compliance, lockout/tagout issues or housekeeping issues — AI could provide real-time monitoring and alerting for those challenges. However, broader implementation would be premature for these companies to truly leverage AI, and the company will need to continue to work on its safety culture and move beyond reactive behavior.

3. Calculative Stage: Data Overload

Companies at this stage have started using data more systematically to identify trends and predict issues. Companies in the calculative stage are typically more committed to safety and have systems in place for tracking and analyzing safety data. The challenge they face is one of scale: they may be collecting vast amounts of safety data but struggle to make sense of it all. They collect a lot of data, but don’t always know how to interpret or act on it effectively. The sheer volume of information can lead to analysis paralysis, making it difficult to derive actionable insights without being overwhelmed.

AI Readiness: Many opportunities for adoption. AI shines in environments where there's too much data for humans to process efficiently. These companies are primed for AI-driven solutions that can help them streamline data analysis, identify patterns, and generate insights automatically, without requiring an army of analysts

4. Proactive Stage: Real-Time Data Gap

Organizations in the proactive stage are leaders in safety. They’ve adopted Environmental Health and Safety (EHS) software, have established systems to track and report safety metrics, and actively work to improve based on those reports. However, much of their data is still historical — it has been collected after the fact — which means they lack true real-time visibility.

AI Readiness: Widespread opportunities. These companies will see immense value in evolving from data reporting to real-time alerting. AI can help them close the gap between identifying risks and mitigating them on the spot, moving them toward a more immediate, actionable safety approach. AI monitoring can provide in-the-moment visibility and guidance, helping teams address issues before they escalate into incidents.

5. Generative Stage: The Pioneers

At the top of the AI Data Safety Ladder are the generative stage companies. These organizations not only have a deeply ingrained safety culture, but they also fully embrace the role of data and technology in driving continuous improvement. They have a culture that embraces transparency, growth, and learning. They’ve built trust with employees and have worked hard to win their buy-in. They likely already use AI-based tools for safety video monitoring and other applications and have earned the trust of their workforce by fostering transparency and open communication.

AI Readiness: Already there. These companies are pioneers in leveraging AI and other innovative technologies to ensure safety. For these companies, AI is not just a tool but an enabler of their forward-thinking safety strategy. Their efforts are focused on refining the systems they already have in place and pushing the boundaries of what’s possible in safety innovation.

Conclusion: What’s Your Safety Culture Stage?

Knowing where your company stands on the AI Data Safety Ladder is the first step toward determining your readiness for AI-based safety video monitoring. If your organization is still in the preliminary stages, the focus should be on building a solid safety culture before diving into complex technology. On the other hand, companies with a basic safety culture foundation can begin to benefit from the adoption of AI, particularly when it comes to real-time monitoring and preventing incidents before they happen. AI-based safety monitoring isn’t just about the technology, it’s about how well-prepared your organization is to embrace the insights it provides and act on them. Finally, video analytics and AI offer many promising tools to improve safety outcomes, but they rely on the existence of a strong safety culture foundation.

Where do you think your company stands? Are you ready for AI-based safety video monitoring? If so, contact us to take the next step with AI.