Expert Evidence AI Attribution Agent for Sydney Litigation Lawyers: Make Every AI-Assisted Expert Output Defensible

Your expert witness emailed their report yesterday. It’s strong — modelling, charts, a clean methodology section. Then in conference she mentions she used a generative model to help summarise one section and to render a chart caption. The ART Expert Evidence Practice Direction is sitting on your desk and the cross-examination is in three weeks. You don’t have a clean record of which paragraphs are model-derived, which prompts produced them, or which underlying data the expert was working from when she ran them. The Expert Evidence AI Attribution Agent is built to attach that record to the report before it leaves the expert’s hands.

The problem

Tribunals and courts now expect practitioners and their experts to be candid about generative AI use in evidence. The Administrative Review Tribunal’s Practice Directions and Other Guidance set expectations for the conduct of proceedings, including the form and integrity of evidence put before the Tribunal. The Federal Court’s General Practice Note on AI (GPN-AI) makes practitioners responsible for the accuracy of AI-assisted content in documents filed with the court. The Australian Solicitors’ Conduct Rules (Rule 19) require candour to the court — which extends to disclosing, where relevant, that an AI tool was used in producing material on which the court is being asked to rely.

The operational problem is narrower than the policy one. Experts use models. They use them to summarise transcripts, to format chronologies, to draft methodology paragraphs, to render visualisations. By the time the report reaches you, the trail of which parts touched a model — and what data the model saw — is usually gone. If the question gets asked in cross-examination, “I don’t recall” is not a defensible answer.

What the Expert Evidence AI Attribution Agent does

The agent attaches verifiable attribution metadata to expert evidence outputs. It runs alongside the expert’s drafting workflow and records, for each output artefact in the report:

• whether a generative model was involved in producing that artefact
• the model identifier and version, where known
• the prompt or instruction that produced the output
• the input documents or data the expert had open or referenced
• a hash of the resulting artefact so it can later be matched to the version filed

The output is a structured attribution log that travels with the report. If the expert is asked in cross-examination which paragraphs were AI-assisted and what the model saw, the log answers the question deterministically.

How it works

1. The expert installs the agent locally and links it to the matter folder containing their working files.
2. As the expert drafts — in Word, in their analysis environment, or in a model-assisted tool — the agent records attribution events: model used, prompt, input context, output artefact hash.
3. When the report is finalised, the agent produces a structured attribution log mapped to the final document, with each AI-assisted section tagged.
4. The instructing solicitor receives the attribution log alongside the report and stores it on the matter file as part of the evidence chain.
5. If the AI use is challenged, the log produces a paragraph-by-paragraph answer with model, prompt, and inputs.

Why this matters in Sydney

Sydney litigation runs across the Federal Court, the NSW Supreme Court, the ART, and a heavy commercial arbitration practice — and expert evidence is central to most of the matters that justify the cost of bringing them. The ART’s published Practice Directions set the conduct standard for matters reviewed in that forum, and the Federal Court’s GPN-AI applies across federal proceedings commenced or run in the Sydney registry. A Sydney litigation lawyer briefing a forensic accountant, a valuer, a medical expert or a technical expert has no way today of compelling a clean attribution record from the expert’s workflow. Asking after the fact rarely produces one. The Expert Evidence AI Attribution Agent is intended to close that gap before the report is signed and served.

The narrower point: where the expert’s credibility is the case, the credibility of the attribution record is part of the case.

Sources

• Administrative Review Tribunal — Practice Directions and Other Guidance: https://www.art.gov.au/help-and-resources/professionals-and-practitioners/practice-directions-and-other-guidance
• Federal Court of Australia — Use of Generative Artificial Intelligence Practice Note (GPN-AI): https://www.fedcourt.gov.au/law-and-practice/practice-documents/practice-notes/gpn-ai
• Law Council of Australia — Australian Solicitors’ Conduct Rules: https://lawcouncil.au/policy-agenda/regulation-of-the-profession-and-ethics/australian-solicitors-conduct-rules
• Federal Court of Australia — Rules, Acts & Regulations: https://www.fedcourt.gov.au/law-and-practice/rules-acts-and-regulations

Exegesis capability references:

• RuleCheck by Exegesis — live beta
• Expert Evidence AI Attribution Agent spec

Join the waitlist

Join the waitlist — be the first to know when access opens for Sydney litigation teams briefing AI-assisted expert evidence

The Expert Evidence AI Attribution Agent is in build. We’re scoping how it sits inside the expert’s workflow without slowing the report timeline, and we’re shaping pricing (per-report, per-matter, or firm-licence) based on what we hear from instructing solicitors. Join the waitlist and what you tell us will shape the tier you sit in.