AI continues to develop across the legal sector, but the strongest uptake in 2025–2026 has been among teams handling large volumes of unstructured documents.
Personal Injury (PI) teams, insurance claim professionals, and their clients are seeing tangible benefits as AI tools help automate time-consuming tasks, quickly highlight essential details, and boost efficiency, all while fitting in seamlessly with existing ways of working.
This article summarises five areas where our PI clients are starting to apply AI in practical, low disruption ways.
1. Using AI to develop initial medical chronologies
One of the most impactful early uses of AI in personal injury matters is automatically generating a preliminary medical chronology from voluminous medical records. Instead of a paralegal manually sifting through hundreds of pages of hospital records and doctor’s reports, Cicero AI can rapidly scan these unstructured texts and identify key dates, treatments, symptom changes, and medication events in the patient’s history. The result is an initial timeline of medical events – a chronological narrative of the injury and treatment.
Practitioners still review and refine these AI-generated chronologies for accuracy and nuance, but having this structured sequence of events right at the start of the case yields major advantages. Teams can progress faster, focusing on analysis rather than data extraction.
Example: If Cicero AI flags a surgery on March 3 and a rehabilitation session on April 10, the lawyer can immediately see the gap and inquire if anything noteworthy occurred in between, rather than hunting for those dates in the files.
This jump-starts case strategy and ensures important details aren’t overlooked early on.
By leveraging AI for timeline creation, personal injury lawyers and insurance professionals save substantial time on early case prep. They begin with a solid foundation – a chronology of care – which leads to more informed initial assessments.
Clients, in turn, benefit from quicker case kick-off and potentially faster resolution, since critical facts (e.g. when a condition worsened, or when a treatment occurred) are illuminated sooner.
Front-loading the case with an AI-drafted chronology means that human effort can be redirected to higher-level analysis and client advising, rather than spent flipping through files.
2. Organising and stabilising large sets of medical records
PI matters often involve records sourced from multiple providers, each with different formats, naming conventions and levels of completeness. AI is assisting with the initial organisation of these bundles by grouping similar documents, identifying duplicates and flagging missing dates or unexpected gaps.
Some teams use review-oriented platforms with integrated AI, including Relativity aiR, to classify and segment large record sets before clinical assessment begins. Others pair this with a second pass using tools like Cicero AI to surface relevant medical information once the dataset is structured.
Automating the organisation of medical records means less time spent manually sorting files and renaming documents, and more time understanding the case.
Legal teams benefit from a clean, navigable set of evidence – they can find what they need without hunting through chaotic folders. This consistency also reduces the risk of human filing errors. For clients and insurance stakeholders, the initial review process moves faster and with greater accuracy. Early medical review that might have taken weeks can be shortened significantly, which can lead to faster case moves (for instance, getting to an early mediation or settlement discussion sooner because the facts were organised and clear).
AI-driven record structuring lays a solid foundation for the case, on which lawyers can build their analyses without getting lost in the paperwork.
3. Supporting early case analysis through pattern recognition
Practitioners preparing an early briefing or forming a preliminary view on a matter often need to understand how the injury evolved and whether the medical records present any inconsistencies.
AI tools excel at spotting patterns and anomalies across a large dataset of medical evidence. Cicero AI and Relativity aiR can comb through all documents to highlight things like shifts in symptoms, unexplained treatment gaps, or inconsistencies between a patient’s statements and the medical reports.
These insights do not replace detailed legal review, but they assist practitioners in identifying lines of inquiry earlier and preparing more targeted instructions for experts or counsel.
4. Assisting with the preparation of briefing material
AI is also being used to streamline the preparation of briefs, mediation packs and instructions. Preliminary chronologies generated by tools like Cicero AI can be incorporated into matter materials after legal revision, while AI enabled review platforms help practitioners quickly retrieve the key supporting documents associated with specific events in the chronology.
As cases progress, Practitioners must prepare briefs, settlement packs, and evidence bundles that thoroughly document the injury timeline and support each argument with records. AI significantly streamlines this preparation. This leads to faster assembly of evidence-backed briefs.
Lawyers spend far less time on tedious tasks like collating exhibits or double-checking dates, and more time refining arguments. The final work product is both comprehensive and consistent; every important fact is backed by an attached record, and nothing gets left out due to oversight.
5. Scaling During Peak Workloads
PI practices commonly experience peaks in workload; when large bundles of medical records arrive, when multiple matters reach a critical stage simultaneously, or when deadlines converge. AI provides scalable assistance by helping teams process records more quickly and generate starting chronologies on demand.
When used alongside existing paralegal and administrative resources, tools such as Cicero AI and Relativity aiR act as a flexible extension of capacity, allowing teams to maintain momentum without interrupting established workflows.
The role of AI in Personal Injury Law
Across the sector, the role of AI in Personal Injury matters remains focused on administrative support rather than substantive legal analysis. The trend is toward:
- faster organisation of incoming materials;
- more consistent extraction of medical details;
- earlier visibility of potential issues; and
- smoother preparation of downstream documentation.
Practitioners continue to make all final assessments and decisions, but the groundwork required to reach that point is becoming more efficient.
How Law In Order can assist
As AI becomes more integrated into PI workflows, many teams are looking for practical ways to incorporate these tools without adding complexity or disrupting established processes.
Law In Order supports this by providing:
- Access to AI tools like Cicero AI and Relativity aiR on an on-demand basis
- Secure handling of medical records and sensitive material, aligned with legal confidentiality requirements
- Support across high volume matters, particularly when record sets arrive suddenly or deadlines compress
- Assistance with downstream document preparation, including briefs, bundles and mediation materials
Our role is to provide the operational support and technology access practitioners need, while enabling teams to retain full control over their legal analysis and decision making.
If you’d like to see how these AI-enabled solutions work in practice, please get in touch for more information.
For further information, please contact:
Murali Baddula, Chief Digital Officer, Law In Order
sydney@lawinorder.com
