AI in arbitration: rules, tools, and risks
Artificial intelligence is shifting from talking point to implementation in arbitration, with institutions publishing AI guidelines, providers piloting AI‑assisted awards, and courts confronting the limits of delegating adjudication to machines. Clients want speed and savings, but tribunals and counsel must adapt within clear governance, disclosure, and data‑security guardrails to protect enforceability and fairness.
What’s new
Soft‑law guidance now frames responsible use. The Silicon Valley Arbitration & Mediation Center (SVAMC) issued first‑of‑its‑kind Guidelines in April 2024 emphasising competence, confidentiality, and a bright‑line rule that arbitrators must not delegate any part of their personal mandate – especially decision‑making – to AI, coupled with appropriate disclosure where AI materially affects process or reasoning. The Chartered Institute of Arbitrators (CIArb) followed with a 2025 Guideline that encourages early procedural discussion of AI, provides template language, and underscores arbitrators’ responsibility for the award and for verifying AI outputs. The Stockholm Chamber of Commerce Arbitration Institute (SCC) has likewise published guidance urging confidentiality safeguards, verification to avoid bias and false information, and non‑delegation of decision‑making.
Institutions are also testing narrow, supervised workflows. The American Arbitration Association – International Centre for Dispute Resolution (AAA‑ICDR) launched an opt‑in “AI arbitrator” for two‑party, documents‑only construction cases: the system drafts an award from structured prompts trained on past awards, but a human arbitrator reviews, edits, signs, and remains responsible; AAA reports projected cycle‑time and cost reductions while publishing oversight, ethics, and privacy materials to enhance explainability.
Legal risk landscape
Courts are beginning to confront alleged over‑reliance on AI. In the pending U.S. case LaPaglia v. Valve, a party seeks vacatur alleging the arbitrator “outsourced” award drafting to AI – raising questions about exceeding mandate and undermining a reasoned human decision; whatever the outcome, it illustrates challenge vectors if tribunals fail to disclose or to exercise independent judgment. Similar concerns about fabricated citations and hallucinations have prompted sanctions and judicial warnings in litigation, reinforcing the need for human verification of any AI‑assisted content.
Regulatory frameworks are taking shape, led by the EU AI Act. The Act generally classifies AI used by courts and analogous ADR bodies to research or apply law – when outcomes produce legal effects – as “high‑risk,” triggering duties around oversight, data quality, robustness, and logging as provisions phase in through 2026.
Where AI adds value today
Users and institutions converge on a practical split: AI is well‑suited to procedural and data‑heavy tasks, but not to reasoning or adjudication. Survey data indicates arbitration users expect significant uptake for research, document review, analytics, summarisation, and chronology building, while resisting AI for drafting reasons or merits assessments without human control.
Security and confidentiality are paramount. Open models can retain or leak inputs, and real‑world incidents (e.g., inadvertent disclosures) illustrate the stakes; closed systems reduce risk but do not eliminate obligations under professional rules, protocols, and data‑protection laws. Tribunals and parties should align on cybersecurity protocols, avoid introducing extra‑record material via AI, and ensure any AI‑generated summaries or translations are verified against the record to preserve due process and enforceability.
Practical playbook
- Build AI into Procedural Order No. 1. Define permitted uses (e.g., transcription, summaries, chronology), prohibited uses (decision‑making), disclosure triggers, and data‑security baselines.
- Keep a human firmly “in the loop.” Document that arbitrators and counsel independently review, verify, and take responsibility for any AI‑assisted work product, especially award drafting.
- Choose the right tools the right way. Prefer vetted, closed systems for sensitive material.
- Anticipate challenge risk. Maintain a disclosure record proportionate to materiality of AI use; avoid black‑box reasoning and ensure awards reflect the tribunal’s independent analysis of the record.
How we can help
We provide comprehensive arbitration support across the full lifecycle – from clause drafting and seat/rules selection to case management, evidence strategy, hearings, settlement, and award enforcement or set-aside. Where it serves your objectives, we integrate AI-aware workflows on an opt-in basis to enhance efficiency and insight – always with humans in the loop – and calibrate disclosure, governance, and security to institutional guidance and emerging regulation. Our priority is durable outcomes grounded in fairness, confidentiality, and enforceability.
