AI & Law
An analysis published on 2 November 2026 by Artificial Lawyer, authored by Jean-Remi de Maistre, CEO of Jus Mundi, sets out how specialist AI agents are being developed to support arbitrator selection in international arbitration. The piece identifies arbitrator selection as one of the most consequential and legally sensitive decisions in any arbitration proceeding, where billions of dollars may be at stake, and argues that current processes remain heavily reliant on manual research, internal networks, and word-of-mouth. Jus Mundi's analysis of major arbitral institutions' 2024 to 2025 statistics found that female arbitrator appointments accounted for 35% to 46% of direct institutional appointments but only 17% to 24% of party nominations, illustrating how reliance on familiar networks can entrench imbalances. AI tools aim to assemble a multidimensional evidence base covering candidates' professional background, case experience, publications, and potential conflicts of interest, and to surface candidates outside usual networks. The analysis identifies three core challenges for legal AI in this context: assembling a reliable evidence base, assessing evidence without overstating it, and managing ethical risks including algorithmic bias and inaccurate representation of practitioners' records.
Why this matters
AI-assisted arbitrator selection sits at the intersection of legal technology, professional ethics, and international arbitration governance. If widely adopted, tools of this type could materially affect how arbitral appointments are made, with implications for arbitrator diversity, challenge procedures, and institution accountability. The ethical risks flagged in the analysis, including algorithmic bias that could reproduce historical appointment patterns, are commercially and legally significant because a flawed appointment can expose an award to challenge and derail proceedings.
On the Ground
The development of AI arbitrator-selection tools creates legal work across technology licensing, data processing, and professional responsibility practices: reviewing AI vendor contracts for arbitration institutions, advising on data protection compliance where candidate personal data is processed, and assessing potential liability if a biased or inaccurate AI recommendation contributes to a defective appointment. International arbitration practices will need to develop internal policies on when and how such tools can be used by counsel. A trainee might prepare a vendor due diligence questionnaire for an AI tool procurement, or draft a data processing agreement markup for an arbitral institution considering adopting the technology.
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