AI in Care: Opportunities and Challenges for Personal Injury Claims

In recent months, I’ve noticed more conversations around AI creeping into care discussions — particularly within rehabilitation case management and cost forecasting. Yet despite the noise, genuine adoption in care packages remains rare.

That’s not because AI lacks potential, but because the systems that shape care delivery still depend almost entirely on human-led service models. There’s little commercial incentive for providers to invest in technologies that might reduce billable hours.

Until that changes, the use of AI in personal injury care will remain limited — and its impact on costs, minimal.

Where AI shows real potential in care

Right now, the most promising role for AI lies in the background of care delivery:

• ›Streamlining administrative processes such as record keeping and appointment management
• ›Improving the accuracy and speed of rehabilitation data analysis
• ›Helping case managers measure outcomes and refine intervention goals

Used properly, these systems could free up clinical time, reduce duplication, and help build more person-centred, outcome-focused care plans. They might also improve consistency and transparency in how progress is recorded — both of which are valuable in litigation settings.

The challenges — and why they matter in claims

For all the promise and potential, AI remains difficult to evaluate in the context of litigation. Issues around bias, data quality, security, and ownership continue to dominate the debate.

As Kim Morris explored in 'Not All Expert Witnesses Are Equal', the quality and balance of evidence are critical. That applies equally to how we approach new technologies.

Even further, there’s a question of fit: a lot of AI tools are designed for broad healthcare use, not the individualised, high-stakes world of personal injury rehabilitation.

There’s also the human dimension. AI systems aren’t sentient; they can’t show empathy or emotional awareness. Effective care depends on compassion and connection — the “soft skills” that drive trust and recovery. No machine or algorithm can replicate that.

What AI means for claims

When AI appears within a care package, its purpose and perceived value often depend on who’s instructing.

For claimant solicitors, the focus is likely to be on continuity and standards of care. With ongoing shortages in skilled care staff, they’ll want reassurance that AI-driven monitoring or assistance can maintain — or even improve — the quality of input their client receives.

For defendant solicitors, the appeal lies in potential cost control and consistency. With agency fees rising steeply, AI alternatives may seem an opportunity to contain inflation while still meeting care needs.

Balancing these expectations requires careful, evidence-based analysis. It’s not enough to assume that technology equals progress or efficiency.

Five questions solicitors should ask when AI appears in a care package

1. What measurable outcomes or quality indicators support the inclusion of AI in this package?
2. Does the system improve continuity and safety of care, or does it simply replace human input?
3. How reliable and transparent is the data underpinning its use?
4. Are the expected cost savings realistic once training, maintenance, and oversight are considered?
5. Who is accountable if the AI system fails, gives false feedback, or compromises care?

Ask these questions and the discussion will move beyond “new versus old” and toward what truly matters in patient care — quality, safety, and whether the solution truly fits the individual’s needs.

The cost illusion of AI

While AI might promise long-term savings, with what we’re seeing from the technology at the moment, those reductions are often marginal at best.

Individualised care — especially for people with catastrophic injuries — rarely goes hand in hand with standardised, technology-driven models. And when you factor in research, development, training, and potential failures, the total cost can easily match or exceed traditional methods.

Cheaper care isn’t automatically better care. In some cases, the real value is in improving quality and outcomes for the same cost.

A balanced view on AI in care

As an expert witness, I see AI’s potential as both practical and procedural.

It can improve record accuracy, streamline administration, and help measure outcomes more consistently. But it can’t replicate the empathy, intuition, and experience that define high quality care.

The focus should remain on how technology complements human expertise — not how it replaces it. In that sense, AI can be a useful teammate in the pursuit of better rehabilitation outcomes, but it must never become the one writing the care plan.