What defendant insurers need to know
Artificial intelligence (AI) is constantly improving the diagnosis and treatment of traumatic brain injury (TBI). In this article, Weightmans’s Brain Injury Technical Unit reviews developments in this fast-moving area of medical science and also considers how AI is impacting on high value claims relating to TBI.
AI in treatment of TBI
A recent study by Ahmed et al called Artificial Intelligence in Traumatic Brain Injury: A Systematic Review of Prognostic, Diagnostic, and Monitoring Applications, published in December 2025 and including 12 studies conducted across North America, Europe, Asia, and the Middle East, concluded that:
“AI applications in TBI demonstrate strong potential for improving prognostication, imaging analysis, and patient stratification, yet their clinical translation remains constrained by methodological shortcomings.
“Future research should prioritise multicenter prospective datasets, external validation, calibration assessment, and evaluation of clinical impact to enable reliable integration of AI into TBI care.”
The study by Ahmed et al states that recent research demonstrates that the use of AI can result in “strong predictive performance across clinical settings and yield accurate mortality estimates. Imaging-based deep learning models, particularly those for CT segmentation, also show promise in supporting early treatment planning.” Imaging-based approaches employing AI have also yielded improved prediction of the intensity of therapy required by patients, assisting with treatment planning.
We are therefore likely to see AI employed increasingly to enhance accurate diagnosis of TBI, including review of brain imaging, to reduce human error in interpretation of scans.
However, AI in relation to TBI can also be used to enhance rehabilitation and prognosis by allowing patients to undergo, for example, AI-guided targeted electrical brain stimulation to improve memory. AI-guided physiotherapy that tracks progress in real time and adjusts the difficulty level to match patients’ individual needs can also support clinical decision-making and optimise patient recovery.
Given the significant positive impact that AI can have on the treatment of TBI, it will be important to ensure that developments can be accessed equitably by patients and that the data on which AI relies remains accurate and up to date, particularly in relation to interpretation of brain imaging.
Impact of AI on TBI claims
Improvements in predicting patient prognosis using AI, including treatment needs, length of inpatient stay and, ultimately, functional recovery, are likely to enable the parties to identify potentially complex claims sooner, benchmark likely outcomes and value quantum and costs more accurately at an earlier stage.
However, it is important to remember that clinical results generated though AI may not always be correct and may rely on small datasets that are not widely representative. Clinical oversight will therefore remain essential. In addition, some AI tools are “black box” and it is difficult to interrogate the reasons for decisions they make.
Furthermore, AI is also likely to be used increasingly to support experts’ reasoning when reporting in brain injury claims and when scrutinising expert reports, for example, in relation to AI-generated material that may contain substantive error. Defendant insurers need to be on the lookout for the use of AI in expert reports, especially in respect of interpreting imaging and predicting prognosis.
For defendants, expert input is key to challenging the use of AI effectively in the context of TBI claims, including asking how the AI was used, checking data quality and applicability and ensuring any limitations are disclosed.
