AI is here to stay in Personal Injury and Disability Management

Artificial intelligence (AI) tools are everywhere, and they are not going away.

If you are a personal injury and disability management (PIDM) professional, leader, learner or educator, AI tools are part of your reality. That does not mean we are acting on (or reacting to) this reality in the most appropriate way.

Over the last two years, I have spoken about AI with boards of directors, disability management professionals, rehabilitation practitioners, and educators across workers’ compensation and disability insurance systems. Audiences recognized the potential benefits of AI in this domain:

• Faster identification of cases requiring intervention
• Earlier referral to supports and services
• More individualized treatment and recovery pathways
• Improved RTW planning and coordination
• Reduced administrative burden on practitioners
• More time available for direct client engagement

Central to PIDM professionalism is the health and wellbeing of the client while maintaining ethical standards. AI tools can help achieve that objective.

It is incumbent on professionals to be current keep current with the body of knowledge underpinning PIDM. Here, again, AI tools can help identify and apply the ever-evolving knowledge base to the benefit of client outcomes.

Professionals in all fields are accountable for the tools they select and use. PIDM professionals confirm the benefits of AI tools but repeatedly raise three issues:   

1.     Organizations not articulating a clear vision for AI.

2.     Inadequate or inconsistent professionally-specific training on AI tools.

3.     Intensifying cognitive load, leading to AI “Brain Fry.”

Organizational Direction

The concern most reported by PIDM professionals is not rooted in the AI tools themselves. It stems from the organization: leadership uncertainty, vague expectations, and unclear boundaries around how AI should be integrated into daily practice.

Many professionals report receiving communications focused primarily on the risks of AI. Some describe policies that prohibit AI use outright. Others report blocked access to AI platforms or disabled AI functions within workplace software.

At the same time, many PIDM practitioners quietly acknowledge using personal AI accounts to assist with tasks central to their professional responsibilities and work demands.

This creates an uncomfortable situation for both organizations and employees.

From an organizational perspective, unauthorized use can create confidentiality, privacy, and security risks. From the practitioner's perspective, however, the technology may represent a legitimate opportunity to improve service quality and efficiency.

As one PIDM professional asked:

"How can I provide the best service to injured and disabled clients with one hand tied behind my back?"

Others report observing peers who are achieving better results through effective, although unauthorized and undisclosed, AI use.

One vocational rehabilitation specialist summarized the concern this way:

"I'm worried I'm falling behind. If I want to advance in this profession, I need to keep up with AI technologies."

Organizations that focus exclusively on restriction may inadvertently encourage shadow AI practices while missing opportunities to establish safe, effective, and transparent approaches to adoption.

Inadequate Training

Professional responsibility requires practitioners understand the tools they use—including AI technologies.

Where organizations have authorized the use of AI tools (such as ChatGPT, Microsoft Copilot, Gemini, or Claude), PIDM-specific training frequently lags deployment.

Following a recent conference keynote presentation, a cluster of PIDM professionals highlighted their reality. Their organizations had provided AI technologies but with limited and generic instruction. The training focused on common administrative tasks with little guidance or “use case” examples related to disability management, claims administration, rehabilitation, or return-to-work coordination.

As one case manager explained:

"We were given the AI tools, but we were expected to figure out the specifics of using them ourselves."

In one large agency, PIDM professionals reported creating informal learning networks, sharing successful prompts, use cases, and lessons learned with or from other colleagues.

While this initiative is encouraging, organizations should not rely on informal improvisation alone. Effective AI implementation requires role-specific training, governance, and ongoing professional development.

Just as organizations invest in training for case management systems, clinical protocols, and legislative requirements, they must also invest in both AI literacy and specific AI applications they authorize and provide.

AI "Brain Fry"

One of AI's greatest advantages is its ability to automate routine tasks.

Whether through generative AI tools such as ChatGPT, Copilot, Gemini, and Claude, or emerging agentic AI systems capable of carrying out more complex workflows, organizations are increasingly using AI to reduce administrative effort and accelerate decision-making.

Many practitioners appreciate these efficiencies. As one therapist noted:

"It speeds up documentation and correspondence, allowing more time with my clients."

Yet the same therapist added:

"I'm glad to have access to AI tools, but I'm feeling more exhausted than ever."

This observation points to an emerging challenge a client service representative described succinctly:

"It's not that I am dealing with more cases. The cases I am dealing with are just much more complex."

A board member from a workers' compensation authority captured what may be occurring:

"AI removes the simple work… it changes the mix… accelerates the complex work, and leaves [PIDM] professionals with a higher volume of cognitively demanding decisions."

She succinctly christened this phenomenon as the AI intensity effect and related it to a similar observation in nursing where the number of beds in a ward are not increasing but the healthcare needs and nursing demands are.

As AI assumes routine administrative activities, practitioners may find themselves spending a greater proportion of their workday addressing complex exceptions, nuanced judgment calls, difficult client interactions, and high-consequence decisions. The total caseload may not increase, but the cognitive demands of that caseload does.

Recent research reported in the Harvard Business Review refers to this experience as "Brain Fry"—a state of mental exhaustion and cognitive strain associated with intensive AI use. While the article highlights the substantial benefits of AI, it also notes that productivity gains may diminish and cognitive burden increase when employees are required to manage multiple AI systems simultaneously. [See Julie Bedard, Matthew Kropp, Megan Hsu, Olivia T. Karaman, Jason Hawes and Gabriella Rosen Kellerman, When Using AI Leads to “Brain Fry,” Harvard Business Review, March 5, 2026, available at https://hbr.org/2026/03/when-using-ai-leads-to-brain-fry].

For PIDM professionals, whose work already involves complex decision-making, empathy, ethical judgment, and interpersonal communication, this risk deserves serious attention.

Technology Alone Is Not an AI Strategy

AI implementation is not simply a technology project. It is a workforce transformation initiative.

Boards of directors, executives, and professional leaders should be asking:

• Do we have a clear AI strategy?
• Are we providing role-specific AI training?
• Do employees understand appropriate and inappropriate uses of AI?
• Are we monitoring how workload intensity changes as AI tools are introduced?
• Are we preparing managers and staff to recognize signs of AI-related cognitive strain and fatigue?

Employers have increasingly recognized what PIDM professionals already know: “psychological health and safety” is an essential component of workplace risk management. As AI becomes more deeply integrated into professional work, leaders must consider the risk of AI-related workload intensity and cognitive strain; the must recognize this emerging psychosocial hazard and take steps to manage that risk.

The irony is difficult to ignore. Many organizations are implementing AI to improve productivity, enhance service delivery, and reduce administrative burden. Yet if AI deployment results in sustained mental fatigue, cognitive overload, or increased psychological stress among employees, those gains may be offset by reduced engagement, burnout, turnover, or even psychological injury.

For organizations whose mission includes preventing injury and supporting recovery, this issue deserves particular attention. Workers' compensation authorities, disability insurers, and rehabilitation providers have long understood that workplace systems and job design can significantly influence health outcomes. The same principle should apply to AI implementation.

The business case for AI extends beyond productivity gains and cost savings.

In workers' compensation, disability insurance, and rehabilitation systems, the ultimate objective is better outcomes for the people we serve. If AI can help identify needs earlier, support better decisions, improve treatment pathways, and facilitate safer and more durable return-to-work outcomes, then its value is significant.

However, achieving those outcomes requires investing in people as deliberately as we invest in technology.

The future of AI in PIDM will not be determined solely by the sophistication of the tools. It will be determined by how effectively organizations help professionals use those tools while preserving the human judgment, expertise, and wellbeing that remain at the heart of the profession.

Organizations that successfully navigate the AI transition will be those that view AI not merely as a technology initiative, but as a strategic change effort that balances innovation, professional competence, psychological health and safety, and client outcomes. In that respect, preventing AI "Brain Fry" may prove to be just as important as implementing AI itself

Where does AI fit in PIDM professional training?

How do we prepare the next generation of PIDM professionals for this reality? I argue against a passive, permissive approach. Our students need to be prepared to use AI tools in the workplace. Intentional instruction on AI must be part of the curriculum. Those entering professional roles need to know how AI tools work. They also need to recognize improper use of AI in the workplace.

For the last few years, I provides guidance on permitted and unacceptable uses of AI in the courses I teach. I required students disclose the AI tool use in an “AI Attestation” statement submitted as part of formal assignments. This allows students to confirm their knowledge of AI tools and their intentional use of AI in assignments. It also provides an opportunity for dialogue on proper uses.

Incorporating AI literacy into the curriculum is just one element of what educators must consider. Educational assessment needs to be AI sensitive. Assessing mastery of PIDM skills needs to be AI-aware. Failing to prepare future professionals for the reality of AI in their roles may limit their career entry and progression. I certainly want the student I teach to be AI literate and sensitive to both proper and improper use in the profession.

Failing to provide AI literacy and appropriate training may leave the next generation of PIDM professionals and those they serve open to harm.