{"id":905793,"date":"2026-06-17T15:34:21","date_gmt":"2026-06-17T21:34:21","guid":{"rendered":"https:\/\/www.myconstructionexpert.com\/blog\/?p=905793"},"modified":"2026-06-17T15:47:35","modified_gmt":"2026-06-17T21:47:35","slug":"arbitration-use-of-artificial-intelligence-guiding-principles-part-ii","status":"publish","type":"post","link":"https:\/\/www.myconstructionexpert.com\/blog\/arbitration-use-of-artificial-intelligence-guiding-principles-part-ii\/","title":{"rendered":"Principles Guiding the Use of AI in Arbitral Proceedings (Part II)"},"content":{"rendered":"\n

Rohit Bhat, Natalia Marina Zibibbo, Sue Ng, Olivier Andr\u00e9 | Freshfields<\/a><\/p>\n\n\n\n

As outlined in\u00a0Part I<\/a>, a framework governing the use of AI in arbitration is rapidly taking shape. In this Part II, we explore how emerging principles\u2014responsible use, human oversight, data protection, transparency, and fairness\u2014interact with real-world arbitral practice. Where we set out relevant jurisprudence and rules, this is not intended to be an exhaustive survey, but instead to highlight recent practices that have emerged. As the use of AI and regulations continue to develop, there may be greater room for divergence across jurisdictions.<\/p>\n\n\n\n

Balancing AI Efficiency with Human Oversight        <\/strong><\/h4>\n\n\n\n

As the uses of AI in international arbitration expand, maintaining human oversight is key to ensuring that the use of AI remains efficient<\/a> while complying with broader professional and ethical obligations.<\/p>\n\n\n\n

For parties: <\/strong>Whether parties\u2019 use of AI is protected by attorney-client privilege remains unsettled, and the law on this continues to develop. While we are not aware of any arbitral tribunal decision on the interaction between the use of AI and legal privilege, courts in the United States have started to grapple with this question, but clear principles are yet to emerge. In United States v Heppner<\/em> (S.D.N.Y. 2026)<\/a> the court held that communications with a publicly accessible AI tool were neither privileged nor protected as work product because they were not confidential and were not communications with, or documents prepared by, an attorney (see<\/em> Blog post here<\/a>). Conversely, in Warner v Gilbarco<\/em> (E.D. Mich. 2026)<\/a> the court held that a pro se <\/em>plaintiff\u2019s AI chats reflected her internal analysis and mental impressions generated using a tool, and were thus protected by the work product doctrine.<\/p>\n\n\n\n

For counsel:<\/strong> A core risk associated with generative AI use is \u201challucination\u201d\u2014where the tool produces plausible but incorrect citations, quotations, or summaries. In several instances, courts have criticized (and in some cases sanctioned) lawyers for filing submissions containing non-existent or inaccurate authorities (see<\/em> e.g.<\/em>, the English High Court in Ayinde v London Borough of Haringey and Al-Haroun v Qatar National Bank<\/em><\/a> and the Singapore High Court in Tajudin bin Gulam Rasul and Mohamed Ghouse s\/o Rajudin v Siriaya bte Haja Mohidden<\/em><\/a>).<\/p>\n\n\n\n

To mitigate this risk, guidelines increasingly recommend that counsel implement robust internal verification processes (including appropriate supervision), rather than relying blindly on AI outputs. The Singapore Ministry of Law\u2019s Guide for Using Generative AI in the Legal Sector<\/em><\/a>, for instance, recommends a risk-based approach: a \u201chuman-in-the loop\u201d model for high-risk work products (where legal professionals review outputs and verify facts, citations, and legal reasoning), and a \u201chuman-on-the-loop\u201d model for lower-risk tasks (where oversight is provided through supervised checks or structured sampling) (see<\/em> Diagram 2). <\/p>\n\n\n\n

For arbitrators:<\/strong> AI-assisted summaries may influence how facts are selected, framed or prioritized. An increasing number of arbitral institutions, in their AI-specific guidelines to arbitrators, consistently emphasize the non-delegation of legal reasoning and decision-making to AI (see e.g.<\/em>, SVAMC Guidelines 2024<\/a>, SCC Guide 2024<\/a>, AAA-ICDR Guidance 2025<\/a>, VIAC Note on AI 2025<\/a>, and CIArb Guideline 2025<\/a>).<\/p>\n\n\n\n

The challenge is therefore not whether AI may be used, but how it can be integrated in a way that preserves efficiency gains while ensuring an adequate level of human oversight.<\/p>\n\n\n\n

Divergent Approaches to Transparency          <\/strong><\/h4>\n\n\n\n

The Illinois Supreme Court\u2019s Policy<\/a> does not require parties to disclose the use of AI in pleadings. That contrasts with the approach of one of the magistrate judges in the Northern District of California<\/a>, which requires parties to disclose any part of their pleadings produced with the help of AI, as well as any AI-generated material used as evidence, failing which such material may be treated as inadmissible (see<\/em> p 10). The underlying rationale is that the tribunal should be able to evaluate the tools and methods used to generate submissions and evidence.<\/p>\n\n\n\n

Arbitral institutions have taken different approaches to disclosures by parties and arbitrators. <\/p>\n\n\n\n