Artificial intelligence has quickly become one of the most transformative new tools in the field of ergonomics. AI-powered analysis programs can review videos of workplace tasks to identify potential ergonomic risks, organize injury data, and help generate recommendations at a speed that would be difficult to achieve through manual analysis alone. For companies managing large workforces or multiple facilities, these capabilities can create opportunities to identify risks more efficiently and support more proactive injury prevention.
But AI is not a substitute for expertise, context, or responsible oversight.
As organizations evaluate AI-based ergonomic tools, it is important to consider several common misconceptions that can create unnecessary risk. Understanding what AI can and cannot do is essential for using these technologies effectively to expedite ergonomic risk identification while protecting employees and ensuring a safe workplace.
“Our model was custom built for this task, so it doesn't need oversight.”
“This AI model is going to replace my onsite ergonomics provider.”
“We can’t use AI because our employees' data can't go to these large AI corporations.”
A common false assumption about advanced AI models is that a model designed specifically for ergonomic analysis will automatically produce reliable recommendations. While a purpose-built model may be highly effective at identifying patterns or evaluating specific ergonomic factors, customization does not eliminate the need for human review.
AI evaluates information according to the data, rules, and parameters it has been given. It may identify a potentially awkward posture, repetitive movement, or workstation issue, but it may not understand the full operational context behind that finding. Without understanding the larger context, AI may make recommendations that appear appropriate in isolation but are not practical for a particular job, interfere with production requirements, or fail to address the actual source of the risk.
This is why AI-generated recommendations must be reviewed by a qualified subject matter expert before they are presented to a client or implemented in the workplace.
Human review provides an important quality-control step. An ergonomist or other qualified professional can examine the AI's findings, consider the context of the job, determine whether the recommendation is viable and evaluate whether it is likely to be effective. This ensures recommendations are informed by professional judgment before they influence workplace decisions.
For organizations with onsite ergonomists, athletic trainers, physical therapists, or other health and safety professionals, AI may initially seem like a threat to those positions. In practice, however, AI can provide an opportunity to make onsite providers more effective.
Much of a provider's time can be consumed by administrative work: documenting assessments, organizing information, preparing reports, reviewing video, or completing repetitive analysis tasks. These responsibilities are necessary, but they do not necessarily represent the highest-value use of a trained professional's time.
AI can help automate or accelerate some of this work.
When technology handles portions of the data collection and analysis process, providers can spend more time doing what technology cannot easily replicate:
Interacting directly with employees
Observing work in context
Coaching workers on body mechanics to reduce fatigue and strain
Discussing concerns with supervisors
Developing practical ergonomic solutions
This shift can make an onsite programs more personal rather than less.
Instead of spending hours documenting every detail of an assessment, a provider may be able to spend more time walking the floor, talking with employees, and identifying issues that may not be apparent from a video or dataset. AI becomes a tool that extends the provider's capabilities rather than a replacement for the provider.
The most effective model is not AI versus people. It is AI plus people.
The concern over data sharing is legitimate, particularly when ergonomic programs involve employee information, workplace videos, or other potentially sensitive data. Protecting employee privacy should be a fundamental responsibility of any organization using AI in workplace health and safety.
Companies should understand exactly what information is being collected, where it is processed, how it is stored, who can access it, and whether it is used for purposes beyond the service being provided.
However, protecting privacy does not necessarily mean organizations cannot use AI.
One approach is to design systems around anonymized information. An appropriately designed in-house or private AI model can process ergonomic data without retaining markers that identify an individual employee. The system may be able to evaluate movement patterns, job demands or ergonomic risk factors without needing an employee's name or other identifying information. This minimizes unnecessary exposure of personal information while still allowing organizations to use technology to address workplace risks.
Companies should also avoid assuming that every AI platform handles data in the same way. Privacy and security practices can vary significantly between tools. Before adopting an AI solution, organizations should understand its data policies and ensure they align with their legal, contractual, and internal privacy requirements.
AI can provide significant value to office and industrial ergonomics programs, but organizations should approach implementation deliberately. Three strategies can help reduce common risks.
Technology should be supported by experience. Working with an established provider that understands ergonomics, occupational health, and workplace safety can provide an important layer of professional oversight.
A qualified provider can help determine where AI is appropriate, validate its outputs, and integrate technology into a broader injury prevention strategy. This also helps ensure that AI is being used to solve a real business or safety problem rather than simply being adopted because it is new.
Organizations should know what happens to information once it enters an AI system. Any tool or system should be open and transparent about their processes.
Before implementing a tool, ask practical questions: What information does the system collect? Where is it processed? Is the information stored? Is it used to train another AI model? Who can access it? How are recommendations generated? What limitations does the system have?
This transparency gives companies the chance to make informed decisions about whether a particular technology is appropriate for their workplace and their needs.
Technology is only effective when people understand how to use it appropriately. Employees, managers and safety professionals should receive education about what an AI tool is designed to do, what it cannot do, and when human judgment is required.
Regular check-ins and audits are equally important. Organizations should periodically evaluate whether the technology is producing useful results, whether recommendations are being implemented appropriately and whether privacy and data-handling practices remain consistent with company expectations.
AI has the potential to make ergonomic programs faster, more scalable, and more data driven. But its greatest value may come from how it complements human expertise rather than replaces it.
The organizations most likely to benefit will be those that treat AI as another tool within a larger injury prevention strategy. Technology can identify patterns, organize information and reduce administrative burdens. Experienced professionals can provide necessary context, communicate with employees, evaluate recommendations, and make decisions based on the realities of the workplace.