AI in Occupational Health: Emerging Risks, Rapid Change, and What Employers Can Do Next 

What Research Tells Us   

The genie is out of the bottle. We are in a new era in which long-term benefits associated with the use of advanced technology for OH&S management are not yet clear:   

• A literature review found that AI applications “significantly contributed to safer and more efficient workplaces,” but challenges such as data privacy concerns, algorithmic biases, and reduced worker autonomy created barriers to broader AI adoption in OH&S. The study’s authors recommend taking a “human-centered approach, where AI complements rather than replaces human oversight.”   
• Authors of another systematic review stated that “we are at the early stages of understanding the role AI can play in OH&S.” They identified “a critical need for future research to unpack how considerations taken in the development and adoption of workplace AI tools for OH&S can determine their effectiveness in addressing worker injury or illness.”  
• A study on the advancement of AI in OH&S across high-risk industries highlights AI’s “pivotal role in mitigating the global incidence of occupational incidents and diseases, which result in approximately 2.3 million fatalities annually.” This study found that AI technologies have been instrumental in automating hazardous tasks, enhancing real-time monitoring, and improving decision-making through comprehensive data analysis. Technology referenced in the study includes drones and robots, computer vision for environmental monitoring, predictive analytics, and AI-driven simulations to enhance training protocols. With a transition from reactive to proactive safety measures, “the implementation of AI represents a transformative approach, aiming to substantially reduce the global burden of occupational injuries and fatalities in high-risk sectors,” the authors said. 

What Are the Emerging Risks of Using AI in Occupational Health? 

As AI becomes more embedded in occupational health programs, employers are discovering its benefits and encountering a new set of risks that require thoughtful oversight, clear governance, and a continued focus on people — not just technology. The following six challenges highlight where employers should proceed with adapting to how AI is reshaping occupational health management. 

1. Over-Reliance on Automation at the Expense of Human Judgment 

AI-driven systems can identify injury trends, flag risk patterns, and recommend interventions at a scale no human team could manage alone. However, in occupational health, clinical judgment and situational context remain essential. 

When automated recommendations are followed without appropriate human oversight, employers risk missing nuances such as job-specific demands, psychosocial stressors, or early warning signs that fall outside algorithmic models. 

Why This is Important: Occupational health decisions influence OSHA recordability, return-to-work outcomes, workers’ compensation exposure, and employee trust. AI is most effective when it supports — not replaces — professional decision-making. 

What Employers Can Do: 

• Establish governance models that require human review of AI-assisted health and safety decisions. 
• Develop a framework for the implementation of AI-driven solutions that are designed to augment OH&S management. 
• Use AI as a decision support tool rather than a decision-making authority. 
• Document how automated insights are evaluated and applied in practice. 

2. Data Privacy Concerns and Perceived Employee Surveillance 

Wearables, biometric sensors, and medical monitoring tools can provide valuable insights into exposure risks and early symptoms. However, without safeguards, these technologies can blur boundaries between health protection and perceived surveillance, particularly in remote or hybrid work environments. 

Why This is Important: If employees lose trust in how health data is collected or used, they may delay reporting symptoms, disengage from wellness programs, or avoid participation altogether — undermining the very outcomes AI is meant to improve. 

What Employers Can Do: 

• Use employee health management information management systems that support employee health and safety programs and other business practices. This includes collaboration with occupational health providers who use AI-driven systems to access care recommendations based on best medical practices and findings from millions of similar cases.  
• Clearly define what data is collected, why it is collected, and how it will be used. 
• Communicate transparently with employees before deploying monitoring tools. 
• Align occupational health technology applications with privacy, confidentiality, and consent requirements. 

3. Regulatory and Legal Exposure Outpacing Policy 

The adoption of artificial intelligence in occupational health is accelerating faster than many regulatory frameworks. Employers face uncertainty around how AI-driven insights intersect with OSHA obligations, medical confidentiality, disability accommodations, and emerging state and federal AI governance rules. 

Why This is Important: Across all industries, how health guidance and treatment decisions are made matters as much as the outcomes. Lack of clarity or documentation around AI-assisted decisions can increase legal and compliance risk. 

What Employers Can Do: 

• Develop written policies governing AI use in occupational health programs. 
• Ensure AI-supported workflows align with existing health, safety, and employment regulations. 
• Partner with occupational health providers who understand both clinical care and compliance requirements. 
• Comply with federal and state regulations that apply to the use of AI in the workplace to prevent violations of employees’ legal rights. Employment law attorneys recommend adopting comprehensive AI use policies to help minimize legal liability.  

4. Algorithmic Bias Affecting Health and Safety Outcomes 

AI systems rely on historical data to identify patterns and predict risk. If training data is incomplete or skewed, AI-driven recommendations may unintentionally reinforce inequities across job roles, worker populations, or injury classifications. 

Why This is Important: Bias can affect injury outcomes, return-to-work timelines, employee relations, and organizational credibility, especially in regulated or unionized environments. 

What Employers Can Do: 

• Ask technology vendors how models are trained, validated, and monitored. 
• Review outcomes for unintended disparities. 
• Maintain explainability and reviewability in AI-assisted decisions. 

5. Fragmentation from Rapid Technology Adoption 

As employers adopt multiple AI-enabled tools — from dashboards to wearables to monitoring platforms — data can become fragmented across systems, teams, and vendors. 

Why This is Important: Occupational health effectiveness depends on connected, coordinated insights, not isolated data points. Fragmentation can delay interventions or lead to inconsistent responses. 

What Employers Can Do: 

• Prioritize integrated platforms over disconnected point solutions. 
• Ensure occupational health data flows across safety, HR, and operations teams. 
• Use analytics to inform prevention strategies, not just reporting. 

6. Workforce Readiness and Change Fatigue 

Occupational health professionals, supervisors, and frontline managers are being asked to adapt to new tools and workflows at an unprecedented pace. Without adequate training and support, AI-enabled systems may be underused or misapplied. 

Why This is Important: Technology adoption that outpaces workforce readiness can weaken safety culture and reduce program effectiveness. 

What Employers Can Do: 

• Focus on applications with positive benefits for worker well-being. Examples include automating repetitive tasks linked to musculoskeletal complaints, using analytics to identify and reduce exposure risks, and retraining employees for the new work environment. (WorkCare consults on these and other types of preventive interventions.)  
• Phase implementations rather than deploy multiple tools at once. 
• Invest in training for occupational health and safety leaders. 
• Frame AI as a support tool that reduces administrative burden and enhances care. 

How WorkCare Can Help 

WorkCare clients have access to Navigator, our technologically advanced information management system that integrates AI-driven analytics with automated workflows. Navigator makes it easier for employers to: 

• Track incidents and injuries and mitigate hazards in real time 
• Comply with medical surveillance requirements and ensure safe workplaces 
• Automate administrative tasks so teams can focus on higher-value functions 
• Use data to improve operational efficiencies, boost productivity, and reduce waste 

WorkCare offers: 

• Wellness Solutions to support employees’ physical and mental health 
• Injury Care guidance at onset for better health and business outcomes 
• Occupational Health Screening to ensure regulatory compliance and safe work 
• On-site Clinical Services to monitor and manage work-related medical conditions 
• Incident Prevention coaching and first aid for sprains and strains 

“AI-driven technology encourages employee adherence with care guidance and helps streamline administrative functions for more efficient and cost-effective healthcare management.” 
– Peter P. Greaney, M.D., Executive Chairman and Chief Medical Officer, WorkCare 

Navigating AI in Occupational Health with Confidence 

AI is changing occupational health faster than any single technology shift in recent history. When implemented thoughtfully, AI in occupational health can enhance prevention, improve outcomes, and support a healthier, more resilient workforce. When adopted without clear governance or human oversight, it can introduce new risks. 

Employers who succeed will be those who balance innovation with responsibility, pairing advanced technology with clinical expertise, transparency, and trust. 

Contact WorkCare to learn more about how we responsibly leverage AI in occupational health to help employers manage risk, protect their workforce, and adapt confidently to rapid change. 

FAQs 

Q: What is the expected return on investment in AI-driven technology for occupational health program management? 
A: A National Bureau of Economic Research working paper, which is considered to be reliable source on the potential impact of AI on healthcare spending in general, estimates 5-10% savings with widespread adoption. Cost-savings benefits in industry-specific case studies vary depending on how and why AI is being applied to occupational health program management. 

Q: How should employers address employee hesitancy about AI adoption? 
A: Transparency, early communication, and training are critical. Emphasizing how AI supports employees by reducing repetitive tasks and improving work-life balance can help alleviate concerns and improve adoption.