Why workplace safety is the next frontier for AI investment

In 2025, global venture capital investment in AI exceeded $500 billion for the first time, according to KPMG's Venture Pulse report. AI-related companies attracted 61% of all venture capital globally, more than doubling their share from just three years earlier, according to the OECD's analysis of VC investment through 2025. The numbers are staggering, and they keep climbing.

But where is that money going? The vast majority flows into large language models, generative AI, and the infrastructure to run them. These are important technologies. But they are not solving one of the largest, most persistent economic problems on the planet: the cost of keeping people safe at work.

The International Labour Organization estimates that workplace accidents and diseases cost approximately 4% of annual global GDP, or roughly $2.8 trillion. Nearly 3 million workers die from work-related causes every year. In the United States alone, businesses spend over $170 billion annually on costs associated with occupational injuries and illnesses. In Australia, Safe Work Australia has estimated that the elimination of workplace injuries and illnesses would grow the economy by $28.6 billion annually.

This is not a problem that has been solved. It is a problem that has been managed, incrementally, with tools and approaches that have not fundamentally changed in decades. And that is exactly why it is ripe for AI.

The gap between AI hype and operational reality

Walk into any technology conference in 2025 and you will hear about AI agents, autonomous systems, and generative workflows. Walk into any warehouse, distribution centre, or manufacturing plant, and you will see a different reality: clipboards, manual incident reports, safety walks conducted once a week, and near misses that go unrecorded because nobody saw them (or nobody reported them).

The Bureau of Labor Statistics recorded 5,070 workplace fatalities in the United States in 2024, with transportation incidents accounting for 38.2% of all deaths. The NSC reports that forklifts alone caused 84 deaths and over 25,000 DART cases in 2023-2024. In Australia, 188 workers died from traumatic injuries in 2024, with vehicle incidents accounting for 42% of all fatalities. In New Zealand, WorkSafe continues to warn that forklifts and moving plant remain a critical risk that too many businesses fail to adequately manage.

These numbers have been stubbornly resistant to improvement. Injury rates have declined over decades, but the decline has plateaued in many industries. The tools we have been using to manage safety have reached the limits of what they can achieve. Compliance-based approaches catch the most obvious failures, but they cannot see the thousands of near misses and deteriorating behaviours that accumulate between incidents.

This is the gap that AI can close. Not generative AI writing incident reports. Not chatbots answering safety questions. Computer vision AI that watches what actually happens on the floor, captures the events that humans miss, and feeds that data into workflows that change behaviour before someone gets hurt.

Why workplace safety is uniquely suited to AI

Several characteristics make workplace safety an ideal application for computer vision AI.

The data already exists. Most industrial facilities already have CCTV cameras installed. They are capturing footage 24 hours a day, but almost nobody is watching it in real time for safety purposes. Computer vision AI turns this dormant infrastructure into an active safety system without requiring new hardware.

The problems are visual and repeatable. Pedestrian-vehicle interactions, exclusion zone breaches, speed violations, PPE non-compliance: these are visible events that occur repeatedly and follow patterns. This is exactly the type of problem that computer vision solves well, and where it outperforms human observation (which is inconsistent, fatigable, and limited to line-of-sight).

The economic case is compelling. A single serious forklift incident can cost hundreds of thousands of dollars in workers' compensation, investigation, downtime, and legal exposure. OSHA's powered industrial truck standard generated over $8 million in penalties from 2,248 citations in 2024 alone. The ROI on preventing even a small number of these incidents is significant.

The regulatory environment is tightening. In New Zealand, the Health and Safety at Work Act 2015 places a duty on PCBUs to manage risks "so far as is reasonably practicable," and what is considered reasonably practicable evolves as better tools become available. When computer vision AI exists and is proven to reduce risk by 67%, the argument that traditional methods are sufficient becomes harder to sustain. In Australia, Safe Work Australia's data showing that 80% of fatalities concentrate in just six industries is driving regulatory focus on proactive risk management.

The human element is the differentiator. Unlike many AI applications where the goal is to remove humans from the loop, workplace safety AI works best when it keeps humans in the loop. The technology detects events. But lasting safety improvement comes from coaching conversations where supervisors and workers discuss what happened, why, and how to prevent it. This combination of AI detection and human coaching is what produces the 67% risk reduction that inviol customers experience.

The market is moving

The broader AI-in-workplace-safety market is attracting serious capital. Protex AI, a Dublin-based platform, raised $36 million in Series B funding in early 2025. Intenseye, based in New York, has built an enterprise-grade platform deployed across multiple countries. Voxel, Visionify, viAct, and others are building solutions for different segments of the market.

This wave of investment reflects a recognition that the market opportunity is enormous. The global electric forklift market alone is valued at over $50 billion and growing rapidly. The broader industrial safety technology market spans warehousing, logistics, manufacturing, construction, mining, agriculture, and ports. The addressable market for AI-powered safety monitoring across these industries is substantial and largely untapped.

What is particularly interesting is the shift from pure detection toward coaching and behaviour change. Early entrants in this space focused on alerting: detecting a hazard and sending a notification. The platforms that are gaining the most traction with customers are those that connect detection to structured improvement workflows. inviol was built around this principle from the start, which is why the coaching-first approach has become our defining characteristic.

What this means for operations leaders

If you are running a warehouse, distribution centre, or manufacturing operation, the implications are practical.

First, the "reasonably practicable" bar is rising. As AI safety monitoring becomes more proven and more accessible, regulators and courts will increasingly expect businesses to adopt it, particularly in high-risk environments. Waiting until computer vision AI is standard across your industry means waiting until you are behind.

Second, the ROI is not theoretical. inviol customers see an average 67% reduction in risk, 42% reduction in incidents over three years, and 61% reduction in machine-on-plant incidents. These are measurable, auditable outcomes that translate directly into fewer injuries, lower insurance costs, less downtime, and less damage to goods and equipment.

Third, the technology works with what you already have. inviol uses your existing CCTV cameras. It does not require every camera on site, just a selection covering your highest-risk areas. It processes 99% of data on-premise, addresses privacy from day one, and integrates with your existing safety processes rather than replacing them.

The next five years

AI investment will continue to accelerate. The OECD reports that AI's share of global venture capital has grown from 30% in 2022 to 61% in 2025. As the application layer matures and investors move beyond foundational models toward industry-specific solutions, workplace safety will attract an increasing share of that capital.

The companies that will lead in this space are those that understand a fundamental truth: detecting hazards is necessary but not sufficient. The real value lies in turning detection into behaviour change. Technology that sees everything but changes nothing is just expensive surveillance. Technology that sees, coaches, and improves is a genuine competitive advantage.

At inviol, this has been our thesis from the beginning. We did not build an alerting system that happens to have a coaching feature. We built a coaching platform that happens to use computer vision AI. The distinction matters, and the results prove it.

If you want to see what coaching-first safety monitoring looks like for your operation, book a demo.

Frequently Asked Questions

How much does workplace injury cost the global economy?

The International Labour Organization estimates that workplace accidents and diseases cost approximately 4% of annual global GDP, or roughly $2.8 trillion. In the United States, businesses spend over $170 billion annually on occupational injury and illness costs. In Australia, Safe Work Australia estimates that eliminating workplace injuries would grow the economy by $28.6 billion per year.

How much venture capital is being invested in AI?

Global venture capital investment in AI exceeded $500 billion in 2025 according to KPMG, with AI-related companies attracting 61% of all VC funding globally according to the OECD. The United States accounts for approximately 75% of global AI VC investment, followed by the EU, China, and the United Kingdom.

Why is workplace safety a good application for AI?

Workplace safety is uniquely suited to AI because the data infrastructure already exists (CCTV cameras), the problems are visual and repeatable (pedestrian-vehicle interactions, exclusion zone breaches), the economic case is compelling (a single serious incident can cost hundreds of thousands of dollars), the regulatory environment is tightening, and the technology works best when combined with human coaching rather than replacing human judgement.

What results does AI safety monitoring deliver?

inviol customers typically see a 67% reduction in risk, a 42% reduction in incidents over three years, and a 61% reduction in machine-on-plant incidents. These outcomes come from combining continuous computer vision AI detection with a coaching-first approach where supervisors use video evidence to have structured improvement conversations with their teams.

Is the "reasonably practicable" standard changing because of AI?

Effectively, yes. In New Zealand, Australia, and other jurisdictions, the duty to manage risk "so far as is reasonably practicable" is informed by what controls are available and proven. As AI safety monitoring becomes more accessible and delivers demonstrated results, the expectation that businesses adopt it will grow, particularly in high-risk industries where the technology has been shown to significantly reduce harm.