AI in Arbitration: Frameworks, Applications, and Challenges

Artificial Intelligence (AI) is being integrated into arbitration as a tool to enhance efficiency and decision-making. In broad terms, AI refers to computer systems capable of tasks that typically require human intelligence, such as learning, pattern recognition, and natural language processing. In arbitration, AI’s role so far has been largely assistive – helping arbitrators and parties manage complex information and streamline procedures.

For example, AI-driven software can rapidly review and analyze documents, searching exhibits or transcripts for relevant facts far faster than manual methods. Machine learning algorithms can detect inconsistencies across witness testimonies or summarize lengthy briefs into key points. Generative AI tools (like large language models) are also being used to draft texts – from procedural orders to initial award templates – based on user-provided inputs.

The potential applications of AI in arbitration extend to nearly every stage of the process. AI systems can assist in legal research, sifting through case law and past awards to identify relevant precedents or even predict probable outcomes based on historical patterns. They can facilitate case management by automating routine administrative tasks, scheduling, and communications.

We are proud to present an analysis of AI in arbitration available today. If you are exploring AI’s role in arbitration, Prokopiev Law Group can help. We pair seasoned litigators with leading-edge AI resources to streamline complex cases and help you navigate this evolving landscape. If your situation calls for additional expertise, we are equally prepared to connect you with the right partners.

Legal and Regulatory Frameworks

The incorporation of AI into arbitration raises questions about how existing laws and regulations apply to its use. Globally, no uniform or comprehensive legal regime yet governs AI in arbitration, but several jurisdictions have started to address the intersection of AI and dispute resolution through legislation, regulations, or policy guidelines.

Convention on the Recognition and Enforcement of Foreign Arbitral Awards (New York Convention)

A. Overview of the Convention’s Scope

Article I(1) states that the Convention applies to the “recognition and enforcement of arbitral awards made in the territory of a State other than the State where the recognition and enforcement are sought,” arising out of disputes between “persons, whether physical or legal.”

The Convention does not define “arbitrator” explicitly; rather, it references “arbitral awards … made by arbitrators appointed for each case or … permanent arbitral bodies.” There is no mention of any possibility that the arbitrator could be non-human or an AI entity.

B. Key Provisions Envision Human Arbitrators

Article II: Speaks of “an agreement in writing under which the parties undertake to submit to arbitration all or any differences….” The Convention assumes an “arbitration agreement” with standard rights to appoint or challenge “the arbitrator.”

Article III–V: Concern the recognition/enforcement of awards and set out grounds upon which enforcement may be refused. For instance, Article V(1)(b) refers to a party “not [being] given proper notice of the appointment of the arbitrator,” or “otherwise unable to present his case.”

Article V(1)(d): Allows refusal of enforcement if “the composition of the arbitral authority … was not in accordance with the agreement of the parties….” The reference to an “arbitral authority,” “arbitrator,” or “composition” suggests a set of identifiable, human arbitrators who can be “composed” incorrectly or fail to abide by required qualifications.

Article I(2): The “term ‘arbitral awards’ shall include not only awards made by arbitrators appointed for each case but also those made by permanent arbitral bodies….” Even in the latter scenario, the Convention contemplates a recognized body of human arbitrators (e.g. an institution with a roster of living arbitrators), not an automated algorithm.

C. The Convention’s Enforcement Regime Presupposes Human Judgment

The entire enforcement structure is that an award is recognized only if it meets due-process requirements such as giving a party notice, enabling them to present their case, ensuring the arbitrator or arbitral body was validly composed. For instance, Article V(1)(a) contemplates that each party to the arbitration agreement must have “capacity,” and Article V(1)(b) contemplates that the party was able to present its case to an impartial decision-maker. An AI system cannot easily satisfy these due-process standards in the sense of being challenged, replaced, or tested for partiality or conflict of interest.

D. “Permanent Arbitral Bodies” Do Not Imply Autonomous AI

While Article I(2) references that an arbitral award can be made by “permanent arbitral bodies,” this does not open the door to a fully autonomous AI deciding the merits. A “permanent arbitral body” is typically an arbitral institution (like the ICC Court or an arbitral chamber) with rosters of living arbitrators. Nowhere does the Convention recognize a non-human decision-maker substituting for arbitrators themselves.

UNCITRAL Model Law on International Commercial Arbitration

A. Terminology and Structure

Article 2(b) of the Model Law defines “arbitral tribunal” as “a sole arbitrator or a panel of arbitrators.” Article 10 refers to determining “the number of arbitrators,” “one” or “three,” etc., which in ordinary usage and practice means one or more individual persons. Article 11 lays out a procedure for appointing arbitrators, handling their challenge (articles 13, 14), and so on, plainly assuming a person.

B. Core Provisions That Imply a Human Arbitrator

Article 11 (and subsequent articles on challenge, removal, or replacement of arbitrators) revolve around verifying personal traits, such as independence, impartiality, and conflicts of interest. For example, Article 12(1) requires an arbitrator, upon appointment, to “disclose any circumstances likely to give rise to justifiable doubts as to his impartiality or independence.” This is obviously oriented to a natural person. An AI system cannot meaningfully “disclose” personal conflicts.

Article 31(1) demands that “The award shall be made in writing and shall be signed by the arbitrator or arbitrators.” While in practice a tribunal can sign electronically, the point is that an identifiable, accountable person signs the award. A machine cannot undertake the personal act of signing or be held responsible.

Article 19 affirms the freedom of the parties to determine procedure, but absent party agreement, the tribunal “may conduct the arbitration in such manner as it considers appropriate.” This includes evaluating evidence, hearing witnesses, and ensuring fundamental fairness (Articles 18, 24). That discretionary, human-like judgment is not accounted for if the “tribunal” were simply an AI tool with no human oversight.

C. Arbitrator’s Duties Presuppose Personal Judgment

Many of the Model Law’s articles require the arbitrator to exercise personal discretion and to do so impartially:

Article 18: “The parties shall be treated with equality and each party shall be given a full opportunity of presenting his case.” Human arbitrators are responsible for ensuring this fundamental right.
Article 24: The tribunal hears the parties, manages documents, questions witnesses, etc.
Article 26: The tribunal may appoint experts and question them.
Article 17 (and especially the 2006 amendments in Chapter IV A) require the arbitrator to assess whether an “interim measure” is warranted, including the “harm likely to result if the measure is not granted.”

These duties reflect a legal expectation of personal capacity for judgment, integral to the role of “arbitrator” as recognized by the Model Law.

United States

The United States has no specific federal statute or set of arbitration rules explicitly regulating the use of AI in arbitral proceedings. The Federal Arbitration Act (“FAA”), first enacted in 1925 (now codified at 9 U.S.C. §§ 1–16 and supplemented by Chapters 2–4), was drafted with human decision-makers in mind. Indeed, its provisions refer to “the arbitrators” or “either of them” in personal terms. Fully autonomous AI “arbitrators” were obviously not contemplated in 1925.

Nonetheless, the FAA imposes no direct ban on an arbitrator’s use of technology. Indeed, under U.S. law, arbitration is fundamentally a matter of contract. If both parties consent, the arbitrator’s latitude to employ (or even to be) some form of technology is generally broad. So long as the parties’ agreement to arbitrate does not violate any other controlling principle (e.g., unconscionability, public policy), it will likely be enforceable.

AI and the “Essence” of Arbitration Under the FAA

The threshold issue is not whether an arbitrator may use AI, but whether AI use undermines the essence of arbitration under the Federal Arbitration Act (FAA). The parties’ arbitration agreement—and the requirement that the arbitrator “ultimately decide” the matter—are central. Under 9 U.S.C. § 10(a), a party may move to vacate an award if “the arbitrators exceeded their powers,” or if there was “evident partiality” or “corruption.” In theory, if AI fully supplants the human arbitrator and creates doubt about the award’s impartiality or the arbitrator’s independent judgment, a court could be asked to vacate on those grounds.

A. Replacing the Arbitrator Entirely

If AI replaces the arbitrator (with minimal or no human oversight), courts might question whether a non-human “arbitrator” is legally competent to issue an “award.” Under the FAA, the arbitrator’s written award is crucial (9 U.S.C. §§ 9–13).

If the AI cannot satisfy minimal procedural requirements—like issuing a valid award or being sworn to hear testimony—or raises questions about “evident partiality,” a reviewing court could find a basis to vacate (9 U.S.C. § 10(a)).

If an AI system controls the proceeding such that the human arbitrator exercises no true discretion, that might mean the award was not genuinely issued by the arbitrator—risking vacatur under 9 U.S.C. § 10(a)(4) for “imperfectly executed” powers.

B. Public Policy Concerns

An all-AI “award” that lacks a human hallmark of neutrality could, in a hypothetical scenario, be challenged under public policy.

II. Potential Legal Challenges When AI Is Used in Arbitration

A. Due Process and Fair Hearing

Right to Present One’s Case (9 U.S.C. § 10(a)(3)): Both parties must have the chance to be heard and present evidence. If AI inadvertently discards or downplays material evidence, and the arbitrator then fails to consider it, a party could allege denial of a fair hearing.

Transparency: While arbitrators are not generally obliged to disclose their internal deliberations, an arbitrator’s undisclosed use of AI could raise due process issues if it introduces an unvetted analysis. If a losing party discovers the award rested on an AI-driven legal theory not argued by either side, the party could claim it had no opportunity to rebut it.

“Undue Means” (9 U.S.C. § 10(a)(1)): Traditionally, this refers to fraudulent or improper party conduct. Still, a creative argument might be that reliance on AI—trained on unknown data—without informing both parties is “undue means.” If the arbitrator’s decision relies on undisclosed AI, a party could argue it was effectively ambushed.

B. Algorithmic Bias and Fairness of Outcomes

Bias in AI Decision-Making: AI tools can inadvertently incorporate biases if trained on skewed data. This can undercut the neutrality required of an arbitrator. If an AI influences an award—for example, a damages calculator that systematically undervalues certain claims—a party might allege it introduced a biased element into the arbitration process.

Challenge via “Evident Partiality” (9 U.S.C. § 10(a)(2)): If an arbitrator relies on an AI known (or discoverable) to be biased, a losing party might argue constructive partiality. A court’s review is narrow, but extreme or obvious bias could support vacatur.

III. FAA Vacatur or Modification of AI-Assisted Awards

A. Exceeding Powers or Improper Delegation (9 U.S.C. § 10(a)(4))

An award is vulnerable if the arbitrator effectively delegates the decision to AI and merely rubber-stamps its output. Parties choose a human neutral—not a machine—and can argue the arbitrator “exceeded [their] powers” by failing to personally render judgment.

B. Procedural Misconduct and Prejudice (9 U.S.C. § 10(a)(3))

Using AI might lead to misconduct if it pulls in information outside the record or curtails a party’s presentation of evidence. Any ex parte data-gathering (even by AI) can be challenged. Courts might find “misbehavior” if parties had no chance to confront AI-derived theories.

C. Narrow Scope of Review

Judicial review under the FAA is strictly limited (9 U.S.C. §§ 10, 11). Simple factual or legal errors—even if AI-related—rarely suffice for vacatur. A challenger must show the AI involvement triggered a recognized statutory ground (e.g., refusing to hear pertinent evidence or actual bias). Courts typically confirm awards unless there is a clear denial of fundamental fairness.

D. Modification of Awards (9 U.S.C. § 11)

If AI introduced a clear numerical error or a clerical-type mistake in the award, courts may modify or correct rather than vacate. Such errors include “evident material miscalculation” (§ 11(a)) or defects in form not affecting the merits (§ 11(c)). These are minor and straightforward fixes.

AI Bill of Rights

The White House’s Blueprint for an AI Bill of Rights (October 2022) sets forth high-level principles for the responsible design and use of automated systems. Two of its core tenets are particularly relevant: “Notice and Explanation” (transparency) and “Human Alternatives, Consideration, and Fallback” (human oversight). The Notice and Explanation principle provides that people “should know that an automated system is being used and understand how and why it contributes to outcomes that impact [them]”, with plain-language explanations of an AI system’s role. The Human Alternatives principle urges that people “should be able to opt out, where appropriate, and have access to a person who can quickly consider and remedy problems” caused by an automated decision.

While the AI Bill of Rights is a policy guidance document (not a binding law), it reflects a federal push for algorithmic transparency, accountability, and human oversight in AI deployments. These values can certainly inform arbitration practice. For instance, if an arbitrator or arbitration institution chooses to utilize AI in case management or decision-making, adhering to these principles – by being transparent about the AI’s use and ensuring a human arbitrator remains in ultimate control – would be consistent with emerging best practices. We already see movement in this direction: industry guidelines under development (e.g. the Silicon Valley Arbitration & Mediation Center’s draft “Guidelines on the Use of AI in Arbitration”) emphasize disclosure of AI use and that arbitrators must not delegate their decision-making responsibility to an AI.

European Union AI Regulation

The AI Act (Regulation (EU) 2024/1689) lays down harmonized rules for the development, placing on the market, putting into service, and use of AI systems within the Union. It follows a risk-based approach, whereby AI systems that pose particularly high risks to safety or to fundamental rights are subject to enhanced obligations.

The AI Act designates several domains in which AI systems are considered “high-risk.” Of particular relevance is Recital (61), which classifies AI systems “intended to be used by a judicial authority or on its behalf to assist a judicial authority in researching and interpreting facts and the law and in applying the law to a concrete set of facts” as high-risk. That same recital extends the classification to AI systems “intended to be used by alternative dispute resolution bodies for those purposes,” when the decisions they produce create legal effects for the parties.

Consequently, if an AI system is intended to assist arbitrators in a manner akin to that for judicial authorities, and if its decisions or outputs can materially shape the arbitrators’ final binding outcome, then such an AI system comes within the “high-risk” classification.

I. Conditions Triggering High-Risk Classification for AI Arbitration

Does the AI “assist” in interpreting facts or law?

According to Recital (61), the high-risk label applies when the AI system is used “to assist […] in researching and interpreting facts and the law and in applying the law to a concrete set of facts.”

If an AI tool offers predictive analytics on likely case outcomes, interprets contract terms in light of relevant legal doctrine, or provides reasoned suggestions on liability, quantum of damages, or relevant procedural steps, it falls within the scope of “assisting” the arbiter in a legally determinative task.

Does the AI system produce legal effects?

The Regulation explicitly points to “the outcomes of the alternative dispute resolution proceedings [that] produce legal effects for the parties.” (Recital (61))

Arbitral awards are typically binding on the parties—thus having legal effect—and often enforceable in national courts. Therefore, an AI system that guides or shapes the arbitrator’s (or arbitration panel’s) legally binding decision is presumably captured.

Exclusion of “purely ancillary” uses

Recital (61) clarifies that “purely ancillary administrative activities that do not affect the actual administration of justice in individual cases” do not trigger high-risk status. This means if the AI is limited to scheduling hearings, anonymizing documents, transcribing proceedings, or managing routine tasks that do not influence the legal or factual determinations, it would not be considered high-risk under this Regulation.

The dividing line is whether the AI’s output can materially influence the final resolution of the dispute (e.g., analyzing core evidence, recommending liability determinations, or drafting essential portions of the award).

II. Legal and Practical Implications for AI in Arbitration in EU

When an AI tool used in arbitration is classified as high-risk, a suite of obligations from the Regulation applies. The Regulation’s relevant provisions on high-risk systems span risk management, data governance, technical documentation, transparency, human oversight, and post-market monitoring (Articles and recitals throughout the Act). Below is an overview of these obligations as they would apply to AI arbitration:

A. Risk Management System (Article 9)

Providers of high-risk AI systems are required to implement a documented, continuous risk management process covering the system’s entire lifecycle. For AI arbitration, the provider of the software (i.e. the entity placing it on the market or putting it into service) must:

Identify potential risks (including the risk of incorrect, biased, or otherwise harmful award recommendations).
Mitigate or prevent those risks through corresponding technical or organisational measures.
Account for reasonably foreseeable misuse (for instance, using the tool for types of disputes or jurisdictions it is not designed to handle).

B. Data Governance and Quality (Article 10)

Data sets used to train, validate, or test a high-risk AI system must:

Be relevant, representative, and correct to the greatest extent possible.
Undergo appropriate governance and management to reduce errors or potential biases that could lead to discriminatory decisions or outcomes in arbitration.

C. Technical Documentation, Record-Keeping, and Logging (Articles 11 and 12)

High-risk AI systems must include:

Clear, up-to-date technical documentation, covering the model design, data sets, performance metrics, known limitations, and other key technical aspects.
Proper record-keeping (“logging”) of the system’s operations and outcomes, enabling traceability and ex post review (e.g. in the event of challenges to an arbitral decision relying on the AI’s outputs).

D. Transparency and Instructions for Use (Article 13)

Providers of high-risk AI systems must ensure sufficient transparency by:

Supplying deployers (e.g. arbitral institutions) with instructions about how the system arrives at its recommendations, the system’s capabilities, known constraints, and safe operating conditions.
Disclosing confidence metrics, disclaimers of reliance, warnings about potential error or bias, and any other usage guidelines that allow arbitrators to understand and properly interpret the system’s output.

E. Human Oversight (Article 14)

High-risk AI systems must be designed and developed to allow for human oversight:

Arbitrators (or arbitral panels) must remain the ultimate decision-makers and be able to detect, override, or disregard any AI output that appears flawed or biased.
The AI tool cannot replace the arbitrator’s judgment; rather, it should support the decision-making process in arbitration while preserving genuine human control.

F. Accuracy, Robustness, and Cybersecurity (Article 15)

Providers must ensure that high-risk AI systems:

Achieve and maintain a level of accuracy that is appropriate in relation to the system’s intended purpose (e.g. suggesting case outcomes in arbitration).
Are sufficiently robust and resilient against errors, manipulation, or cybersecurity threats—particularly critical for AI tools that could otherwise be hacked to produce fraudulent or manipulated arbitral results.

G. Post-Market Monitoring (Article 17)

Providers of high-risk AI systems must also:

Monitor real-world performance once the system is deployed (i.e. used in actual arbitration proceedings).
Take timely corrective actions if unacceptable deviations (e.g. high error rates, systemic biases) emerge in practice.

III. The Role of the Provider vs. the Arbitration Institution (Deployer)

Pursuant to Article 3(10) of Regulation (EU) 2024/1689 (“AI Act”), a provider is defined as:

“...any natural or legal person, public authority, agency or other body that develops an AI system or that has an AI system developed and places that system on the market or puts it into service under its own name or trademark.”

Accordingly, where a law firm, software vendor, or specialized AI start-up develops a high-risk AI system and makes it available to arbitral institutions for the purpose of dispute resolution, that entity qualifies as the provider. Providers of high-risk AI systems must comply with the obligations set out in Articles 16–25 of the AI Act, including ensuring that the high-risk AI system meets the requirements laid down in Articles 9–15, performing or arranging the relevant conformity assessments (Article 43), and establishing post-market monitoring (Article 17).

Under Article 3(12) of the AI Act, a deployer is defined as:

“...any natural or legal person, public authority, agency or other body using an AI system under its authority, except where the AI system is used in the course of a personal non-professional activity.”

In the arbitration context, the arbitral institution or the arbitration panel implementing the high-risk AI system is considered the deployer. Deployers have obligations outlined in Articles 29–31, which include using the system in compliance with the provider’s instructions, monitoring its performance, retaining relevant records (Article 29), and ensuring that human oversight is effectively exercised throughout the system’s operation (Article 14).

IV. Distinguishing “High-Risk” vs. “Ancillary” AI in Arbitration

The AI Act’s operative text (specifically Article 6(2) and Annex III Section A, point 8) classifies as high-risk those AI systems “intended to be used by a judicial authority or on their behalf to assist a judicial authority in researching and interpreting facts and the law and in applying the law to a concrete set of facts, or to be used in a similar way in alternative dispute resolution,” when the outcomes of the proceedings produce legal effects. However, the Regulation does not designate as high-risk any AI system that merely executes ancillary or administrative tasks (the Act itself uses the term “purely ancillary administrative activities that do not affect the actual administration of justice in individual cases” in Recital (61)).

Therefore:

High-risk arbitration AI:
- Covered by Article 6(2) and Annex III Section A, point 8, if the AI system materially or substantively influences the resolution of the dispute by “assisting in researching and interpreting facts and the law and in applying the law to a concrete set of facts.”
- This includes systems that suggest legal conclusions, draft core elements of the arbitral decision, or advise on factual or legal findings central to the final outcome.
Not high-risk:
- If the AI tool is purely “ancillary” in nature — for instance, scheduling, document formatting, automated transcription, or anonymization — and does not shape the actual analysis or findings that produce legally binding effects.
- Such use cases are not captured by Annex III, nor do they meet the condition in Article 6(2).
Boundary scenarios:
- If the AI tool nominally performs only “supporting” tasks (such as ranking evidence or recommending procedural steps) but in practice significantly guides or steers the arbitrator’s essential decisions, that usage may bring it under the scope of high-risk classification. The decisive factor is whether the system’s functioning meaningfully affects how the law and facts are ultimately applied.

Hence the quoted distinction between “High-risk” AI and “Not high-risk” (or ancillary) AI in arbitration aligns with the AI Act, subject to the caveat that borderline applications must be assessed in light of whether the AI’s outputs meaningfully influence or determine legally binding outcomes.

National Arbitration Laws in Key EU Member States

Arbitration in the EU is primarily governed by the national laws of each Member State. Over the past decades, many European countries have modernized their arbitration statutes, often drawing inspiration from the UNCITRAL Model Law on International Commercial Arbitration. However, the extent of Model Law adoption and procedural frameworks varies by country.

Country	Primary Legislation	Based on UNCITRAL Model Law?	Enforcement
Germany	10th Book of Civil Procedure (ZPO), Sections 1025–1066	Yes – Adopted Model Law (1985) with modifications. Applies to both domestic and international arbitrations.	Arbitration-friendly courts; awards enforceable by court order, with grounds for setting aside or refusal mirroring New York Convention (NYC) defenses.
France	Code of Civil Procedure (CPC), Articles 1442–1527.	No – French law is an independent regime not based on the Model Law.	Domestic arbitration is subject to more stringent rules, while international arbitration is more liberal. International arbitration is defined broadly (dispute implicates international trade interests). Few mandatory rules in international arbitration; parties and arbitrators have wide autonomy. No strict writing requirement for international arbitration agreements. Uses an exequatur process.
Netherlands	Dutch Arbitration Act (Book 4, Code of Civil Procedure).	Partial – Not a verbatim Model Law adoption, but significantly inspired by it. No distinction between domestic and international cases.	Domestic awards are enforced like judgments after deposit with the court. Foreign awards are recognized under the NYC, as the Act’s enforcement provisions closely follow the NYC grounds.
Sweden	Swedish Arbitration Act (SAA).	Yes in substance – Sweden did not formally adopt the Model Law’s text, but the SAA contains substantive similarities. Applies equally to domestic and international arbitrations.	SAA sets certain qualifications (e.g. legal capacity, impartiality) beyond Model Law minima. Sweden is strongly pro-enforcement. As an NYC party, it enforces foreign awards under NYC terms.
Spain	Spanish Arbitration Act 60/2003 (SAA).	Yes – The 2003 Act was heavily based on the 1985 UNCITRAL Model Law.	Arbitral awards are enforceable as final judgments (no appeal on merits). The High Courts of Justice hear actions to annul awards on limited grounds. Foreign awards are recognized under the NYC. Spanish courts generally uphold awards absent clear NYC Article V grounds.
Italy	Code of Civil Procedure (CCP).	No – Italian arbitration law is not directly based on the Model Law, though it shares many of its core principles.	The Courts of Appeal have jurisdiction over recognition and enforcement of foreign awards (Articles 839–840 CCP). Italy applies NYC criteria for refusal of enforcement. Domestic awards are enforced after the Court of Appeal confirms there are no grounds to set aside.

AI Arbitration in Germany

Below is a high-level analysis of how AI-based arbitration might fit into the wording of the German Arbitration Act (ZPO Book 10). The analysis is somewhat speculative, since the Act does not directly address AI at all.

A. No Direct Prohibition on AI

A first observation: nowhere in Book 10 is there an explicit rule banning or limiting the use of AI for arbitral proceedings. Terms such as “schiedsrichter” (arbitrator), “Person,” or “unabhängig und unparteiisch” (independent and impartial) consistently refer to human arbitrators, but do not categorically exclude the possibility of non-human decision-makers. The statutory text always presupposes a “person,” “he,” or “she” as an arbitrator; still, that is the default assumption in 1998–2018 legislative drafting, not necessarily a prohibition. One could argue that the repeated references to “Person” reflect an implicit normative stance that an arbitrator should be a human being—but from a strictly literal vantage, it is an open question if an AI “system” could serve in that role.

B. Potential Impediments to AI as Sole Arbitrator

Sections 1036–1038 speak of the requirement that arbitrators disclose conflicts of interest, remain impartial, and be capable of fulfilling the arbitrator’s duties. These requirements seem conceptually bound to human qualities (“berechtigte Zweifel an ihrer Unparteilichkeit,” “Umstände [...] unverzüglich offen zu legen,” “sein Amt nicht erfüllen”). One might argue an AI does not truly have “impartiality” or the capacity to “disclose” conflicts as a human might. A creative reading of these provisions might imply that only a human can exhibit these qualities, leading to an indirect barrier to AI arbitrators.

Even so, a forward-looking approach might interpret “unabhängig und unparteiisch” as a principle that can be satisfied technologically if the AI’s training, data, and algorithms meet certain transparency standards. However, the textual references to “Er,” “Person,” or the requirement to “disclose circumstances” do suggest a legislative design geared toward human arbitrators. If the parties themselves voluntarily designate an AI system, a court might question whether that “appointment” meets the statutory standard of an impartial “Schiedsrichter” capable of fulfilling the mandated disclosure obligations. It is unclear how an AI would spontaneously “disclose” conflicts or handle “Ablehnungsverfahren” (challenge procedures) under §§ 1036–1037.

C. Formal Requirements Under § 1035

Under § 1035, the parties “order” (ernennen) the arbitrator(s). The law contemplates an appointment by name, while also allowing the appointment method to be left to the parties’ agreement. One might attempt to list an AI platform or a specialized AI arbitral entity as the “Schiedsrichter.” Then, if the parties do not dispute that appointment, presumably the process is valid. The only textual friction is in § 1035(5) (the court must ensure the “unabhängigen und unparteiischen” arbitrator). If court assistance in appointing is requested, a judge might find an AI does not meet the statutory criteria, effectively refusing to “install” it. But if the parties themselves have chosen an AI system in private, it is not impossible from a purely textual standpoint—though it is an untested scenario.

D. Procedural Rights: “Notice,” “Hearing,” and “Legal Audi Alteram Partem”

Sections 1042–1048 require that each party is “to be heard” (rechtliches Gehör) and that the arbitrator handles evidence and ensures fairness. An AI system delivering a purely automated decision might be deemed to conflict with the personal oversight and reasoned assessment implied by these clauses. For instance, § 1042(1) states “the parties shall be treated equally” and “each party is entitled to be heard.” A purely algorithmic system could risk due-process concerns if it lacks human capacity to weigh “fairness” or accommodate unforeseen procedural nuances. Still, the text does not explicitly say an automaton cannot do it; rather, it insists on respect for due process. If the AI system can incorporate such procedures—ensuring parties can submit evidence, respond to each other, and have an “explainable” outcome—there is no direct textual ban.

E. Setting Aside and Public Policy

Section 1059 allows a court to set aside an award for lack of due process or if the arbitrator is not properly appointed. An AI-based award that fails to grant each party an opportunity to present their case or that obscures the basis for the decision might be at risk of annulment under § 1059(2)(1)(b) or (d). The courts might also strike down an AI-run arbitration under “public policy” (ordre public) if it is deemed that the process is too opaque or not a “fair hearing.” So although no explicit clause forbids AI arbitrators, the effect could be that an AI award is challenged under §§ 1059, 1052 (decision by a collegium?), or 1060(2).

France

A. Domestic Arbitration: Article 1450 Requires a Human Arbitrator

Article 1450 (Titre I, Chapitre II) provides, in part:

“La mission d’arbitre ne peut être exercée que par une personne physique jouissant du plein exercice de ses droits.Si la convention d’arbitrage désigne une personne morale, celle-ci ne dispose que du pouvoir d’organiser l’arbitrage.”

This is the single most direct statement in the Act that speaks to who (or what) may serve as arbitrator. It clearly states that the function of deciding the case (“la mission d’arbitre”) can only be carried out by a “personne physique” (a natural person) enjoying full civil rights. Meanwhile, a personne morale (legal entity) may be tasked only with administering or organizing the proceedings, not issuing the decision.

Under domestic arbitration rules, an AI system—even if structured within a legal entity—cannot lawfully act as the actual decider, because the statute explicitly demands a natural person. This requirement amounts to an indirect but quite categorical ban on a purely machine-based arbitrator in French domestic arbitration. An AI could presumably assist a human arbitrator, but it could not alone fulfill the statutory role of rendering the award.

B. International Arbitration: No Verbatim “Personne Physique” Rule, Yet Similar Implications

For international arbitration, Article 1506 cross-references some (but not all) provisions of Title I. Article 1450 is notably not among those that automatically apply to international cases. As a result, there is no verbatim statement in the international part that “the arbitrator must be a natural person.” One might argue that, in principle, parties to an international arbitration could try to designate an AI system as their “arbitrator.”

However, the rest of the code—e.g. Articles 1456, 1457, 1458, which are incorporated by Article 1506—consistently presumes that the arbitrator is capable of disclosing conflicts, being “récusé,” having “un empêchement,” etc. These obligations appear tied to qualities of a human being: impartiality, independence, the duty to reveal conflicts of interest, the possibility of “abstention” or “démission,” etc. They strongly suggest a living individual is expected. An AI tool cannot meaningfully “reveal circumstances” that might affect its independence; nor can it be “révoqué” by unanimous party consent in the same sense as a human. Thus, even in international arbitration, the text strongly implies an arbitrator is a person who can fulfill these statutory duties.

In short, the literal bar in Article 1450 applies to domestic arbitration, but the spirit of the international arbitration provisions also envisions a human decision-maker. While there is no line that says “AI arbitrators are forbidden,” the repeated references to “l’arbitre” as someone who must disclose, resign, or be revoked for partiality push in the same direction. A French court would likely find that, under Articles 1456–1458 and 1506, an AI alone cannot meet the code’s requirements for an arbitrator.

C. Possible Indirect Challenges and Public Policy

Even if parties somehow attempted to sidestep the requirement of a “personne physique,” the code’s enforcement provisions would pose other obstacles:

Due Process (Principe de la Contradiction). Articles 1464, 1465, 1510, etc. require observance of contradiction and égalité des parties. A purely automated arbitrator might fail to show that it afforded both sides a genuine opportunity to present arguments before a human decision-maker who can weigh them in a reasoned, flexible manner.
Setting Aside or Refusal of Exequatur. If the AI-based award flouts the code’s requirement that the arbitrator have capacity and be impartial, the losing party can invoke Articles 1492 or 1520 (for domestic vs. international) to seek annulment for irregular constitution of the tribunal or for violation of fundamental procedural principles.
Manifest Contrariety to Public Policy. Articles 1488 (domestic) and 1514 (international) require that a French court refuse exequatur if the award is “manifestly contrary to public policy.” A completely AI-run arbitral process might be deemed contrary to fundamental procedural fairness.

In each respect, the Act’s structure presumes a human tribunal with discretionary powers, an obligation to sign the award, etc. An AI alone would struggle to comply.

Netherlands

Under the Dutch Arbitration Act (Book 4 of the Dutch Code of Civil Procedure), the text presupposes that an arbitrator is a human decision-maker rather than an AI system. For instance, Article 1023 states that “Iedere handelingsbekwame natuurlijke persoon kan tot arbiter worden benoemd” (“Every legally competent natural person may be appointed as an arbitrator”) . This phrasing is already suggestive: it frames “arbiter” in terms of a flesh‑and‑blood individual who has legal capacity.

Other provisions likewise assume that an arbitrator can perform tasks generally associated with a human decision-maker. For example, arbitrators must disclose potential conflicts of interest and can be challenged (wraking) if there is “gerechtvaardigde twijfel … aan zijn onpartijdigheid of onafhankelijkheid” (“justified doubt … about his impartiality or independence”) . The Act also speaks of “ondertekening” (signing) of the arbitral award (Article 1057) and grants arbitrators discretionary procedural powers, such as the authority to weigh evidence, hear witnesses, and manage hearings . All these elements lean heavily on human qualities, like independence, impartiality, and the capacity to understand and consider the parties’ arguments.

Thus, while there is no single clause that literally says, “AI is barred from serving as an arbitrator,” the overall statutory design pivots around the concept of a legally competent person. An AI system cannot realistically fulfill obligations such as disclosing personal conflicts, signing an award, or being subjected to a wraking procedure as a human would. In that sense, although the Act does not contain an explicit prohibition on “AI arbitrators,” it effectively prohibits them by tying the arbitrator’s role to natural‑person status and personal legal capacities.

Sweden

Under the Swedish Arbitration Act (Lag (1999:116) om skiljeförfarande), the statutory language implicitly assumes that an arbitrator (skiljeman) will be a human being with legal capacity, rather than an AI system. For instance, Section 7 states that “Var och en som råder över sig själv och sin egendom kan vara skiljeman” (“Anyone who has the capacity to manage themselves and their property may serve as an arbitrator”) . This phrasing strongly suggests a natural person with the requisite legal autonomy rather than a non-human entity.

The Act also repeatedly ties the arbitrator’s role to personal qualities such as impartiality (opartiskhet) and independence (oberoende) (Section 8), the ability to disclose circumstances that might undermine confidence in their neutrality (Section 9), and a duty to underwrite or “sign” the final award (Section 31) . All these provisions presuppose that the arbitrator can make discretionary judgments, weigh fairness, and be removed (skiljas från sitt uppdrag) on grounds related to personal conduct or conflicts of interest. A purely AI-driven system, which lacks the hallmarks of human capacity and accountability, could not fulfill such requirements.

Accordingly, even though the Swedish law does not explicitly state “AI is prohibited from acting as an arbitrator,” it functionally bars non-human arbitrators by defining who can serve and by imposing obligations—impartiality, personal disclosure, physical or electronic signature, and readiness to be challenged for bias—that only a human individual can meaningfully carry out.

Spain

Under the Spanish Arbitration Act (Ley 60/2003, de 23 de diciembre), several provisions implicitly treat the árbitro as a human decision‑maker rather than an AI system. For instance, Article 13 (“Capacidad para ser árbitro”) specifies that arbitrators must be natural persons “en el pleno ejercicio de sus derechos civiles.” This requirement clearly presupposes a human being who has legal capacity.

Additionally, the Act imposes duties of independence and impartiality (Article 17) and requires arbitrators to reveal any circumstances that might raise doubts about their neutrality . The law also contemplates acceptance of the arbitrators’ appointment in person (Article 16), the possibility of recusación (challenge) based on personal or professional reasons (Article 17–18), and the signing of the award (laudo) by the arbitrator(s) (Article 37). All these duties imply discretionary judgment and accountability typical of a human arbitrator.

Italy

Under the Italian Arbitration Act (Articles 806–840 of the Codice di Procedura Civile) , the text consistently assumes that an arbitro (arbitrator) is a human individual, in full legal capacity. For example:

Article 812 provides that “Non può essere arbitro chi è privo […] della capacità legale di agire” (“No one lacking legal capacity may serve as arbitrator”). An AI system cannot meaningfully satisfy this personal requirement of legal capacity.
The Act speaks of recusation, acceptance, disclosure of conflicts of interest, etc. (Articles 813, 815), all of which assume personal traits (e.g. independence, impartiality).
Arbitrators sign the final award (Articles 823, 824), act as public officials for certain tasks, and bear personal liability (Articles 813-bis, 813-ter).

Hence, though the law does not explicitly forbid “AI arbitrators,” it effectively bars non-human arbitrators by imposing requirements linked to human legal capacity, personal judgment, and accountability. An autonomous AI could not meet these conditions without human involvement.

Other Jurisdictions

United Arab Emirates

Under Federal Law No. 6 of 2018 Concerning Arbitration in the UAE, an arbitrator must be a natural person with full legal capacity and certain other qualifications. Specifically:

Article 10(1)(a) provides that an arbitrator must not be a minor or otherwise deprived of their civil rights, indicating they must be a living individual with legal capacity. The same article stipulates that they cannot be a member of the board of trustees or an executive/administrative body of the arbitral institution handling the dispute, and they must not have relationships with any party that would cast doubt on their independence or impartiality.
Article 10(2) confirms there is no requirement of a certain nationality or gender, but it still envisions a human arbitrator who can meet the personal requirements in Article 10(1).
Article 10(3) also requires a potential arbitrator to disclose “any circumstances which are likely to cast doubts on his or her impartiality or independence,” and to continue updating the parties about such circumstances throughout the proceedings. An AI application is not able to fulfill that personal disclosure obligation in the sense prescribed by the Law.
Article 10 BIS (introduced by a later amendment) restates that an arbitrator must be a natural person meeting the same standards – for example, holding no conflicts, disclosing membership in relevant boards, and so forth – if that person is chosen from among certain arbitration-center supervisory bodies.

Hence, although the UAE Arbitration Law (Federal Law No. 6 of 2018) does not literally declare “AI arbitrators are prohibited,” it unequivocally conditions the role of arbitrator on being a natural person with the required legal capacity and duties such as disclosure of conflicts. An autonomous AI system, by contrast, cannot fulfill the obligations that the Law imposes, whether it be impartiality, independence, or the capacity to sign the final award. Such requirements, taken together, effectively exclude AI from serving as the sole or true arbitrator in a UAE-seated arbitration.

Singapore

Under Singapore’s International Arbitration Act (Cap. 143A, Rev. Ed. 2002) (the IAA), which incorporates the UNCITRAL Model Law on International Commercial Arbitration (with certain modifications), there is no explicit statement such as “an arbitrator must be a human being.” However, the provisions of the Act and the Model Law, read as a whole, presuppose that only natural persons can serve as arbitrators in a Singapore-seated international arbitration.

A. Terminology and Structure of the Legislation

Section 2 of the IAA (Part II) defines “arbitral tribunal” to mean “a sole arbitrator or a panel of arbitrators or a permanent arbitral institution.” Likewise, Article 2 of the Model Law uses “arbitral tribunal” to refer to a “sole arbitrator or a panel of arbitrators.” Neither the IAA nor the Model Law define “arbitrator” as something that could be non-human, nor do they provide a mechanism for appointing non-person entities.

The Act consistently describes the arbitrator as an individual who can accept appointments, disclose conflicts, sign awards, act fairly, be challenged, or be replaced, among other duties.

B. Core Provisions That Imply a Natural Person Arbitrator

Appointment and Acceptance

Section 9A of the IAA (read with Article 11 of the Model Law) speaks of “appointing the arbitrator” and states that if parties fail to appoint, the “appointing authority” does so. The entire scheme contemplates a named person or individuals collectively as the arbitral tribunal.

Article 12(1) of the Model Law requires that “When a person is approached in connection with possible appointment as an arbitrator, that person shall disclose….” The word “person,” in the context of disclosing personal circumstances likely to raise doubts as to independence or impartiality, strongly suggests a natural person.
Disclosure of Potential Conflicts

Article 12 of the Model Law further requires the arbitrator to “disclose any circumstance likely to give rise to justifiable doubts as to his impartiality or independence.” The capacity to evaluate personal conflict, have impartial relationships, etc., is a hallmark of a human arbitrator. The arbitrator is also subject to challenge (Model Law Art. 13) if “circumstances exist that give rise to justifiable doubts as to his impartiality or independence” or if he lacks the qualifications the parties have agreed on.
Signatures, Liability, and Immunities

Sections 25 and 25A of the IAA provide that an arbitrator is immune from liability for negligence in discharging the arbitrator’s duties and from civil liability unless acting in bad faith. This strongly implies that the arbitrator is a natural person, because the system of professional negligence or personal immunity for “an arbitrator” does not rationally apply to a non-human machine. Article 31(1) of the Model Law (which has force of law under Section 3 of the IAA) states: “The award shall be made in writing and shall be signed by the arbitrator or arbitrators.” Plainly, an autonomous AI does not meaningfully “sign” a final award in the sense required by law.
Procedural Powers That Depend on Human Judgment

Section 12(1) of the IAA confers on the arbitral tribunal powers such as ordering security for costs, ordering discovery, giving directions for interrogatories, and so forth. The same section clarifies that the tribunal “may adopt if it thinks fit inquisitorial processes” (Section 12(3)) and “shall decide the dispute in accordance with such rules of law as are chosen by the parties” (Section 12(5), read with Article 28 of the Model Law). These provisions presume that the arbitrator can weigh and interpret evidence, evaluate fairness, impartially manage adversarial arguments, handle procedural complexities, and supply reasons in a final award. While an AI tool might assist a human arbitrator, the notion of autonomous final human-like judgment is not recognized anywhere in the Act.

C. Arbitrator’s Duties and the Necessity of Human Capacity

Many duties that the IAA imposes on arbitrators are inherently personal and judgment-based:

Fair Hearing and Due Process. Articles 18 and 24 of the Model Law stipulate that “The parties shall be treated with equality and each party shall be given a full opportunity of presenting his case,” and that “the arbitral tribunal shall hold hearings” or manage documentary proceedings. These tasks involve high-level procedural judgments, discretionary rulings, and the balancing of fairness concerns—indications that the law envisions a human decision-maker.
Ability to Be Challenged, Replaced, or Terminated. Articles 12–15 of the Model Law describe the procedure for challenging an arbitrator for partiality, bias, or inability to serve. This only works meaningfully if the arbitrator is a natural person susceptible to partiality.
Signing and Delivering the Award. The final step of the arbitration is thoroughly anchored in personal accountability: the written text is “signed by the arbitrator(s)” and delivered to the parties (Model Law Art. 31(1), (4)).

D. Permanent Arbitral Institutions vs. Automated “AI Arbitrators”

One might note that section 2 of the IAA includes “a permanent arbitral institution” in the definition of “arbitral tribunal.” This does not mean an institution by itself can decide as the “arbitrator.” Rather, it typically refers to an arbitral body that administers arbitration or that may act as the appointing authority. The actual day-to-day adjudication is still performed by an individual or panel of individuals. Indeed, the IAA draws a difference between:

The arbitral institution that may oversee or administer proceedings (e.g. SIAC, ICC, LCIA, etc.).
The arbitrator(s) who is/are physically deciding the merits of the dispute.

Ethical and Due Process Considerations

The use of AI in arbitration gives rise to several ethical and due process concerns. Arbitration is founded on principles of fairness, party autonomy, and the right to be heard; introducing AI must not undermine these fundamentals. Key considerations include:

Transparency and Disclosure: One ethical question is whether arbitrators or parties should disclose their use of AI tools. Transparency can be crucial if AI outputs influence decisions. There is currently no universal rule on disclosure, and practices vary. The guiding principle is that AI should not become a “black box” in decision-making – parties must know the bases of an award to exercise their rights (like challenging an award or understanding the reasoning). Lack of transparency could also raise enforceability issues under due process grounds. Therefore, best practice leans towards disclosure when AI materially assists in adjudication, ensuring all participants remain on equal footing.

Bias and Fairness: AI systems can inadvertently introduce or amplify bias. Machine learning models trained on historical legal data may reflect the biases present in those data – for example, skewed representation of outcomes or language that favors one group. In arbitration, this is problematic if an AI tool gives systematically biased suggestions (say, favoring claimants or respondents based on past award trends) or if it undervalues perspectives from certain jurisdictions or legal traditions present in training data. The ethical duty of arbitrators to be impartial and fair extends to any tools they use. One safeguard is using diverse and representative training data; another is having humans (arbitrators or counsel) critically review AI findings rather than taking them at face value.
Due Process and Right to a Fair Hearing: Due process in arbitration means each party must have a fair opportunity to present its case and respond to the other side’s case, and the tribunal must consider all relevant evidence. AI use can challenge this in subtle ways. There is also the concern of explainability: due process is served by reasoned awards, but if a decision were influenced by an opaque algorithm, how can that reasoning be explained? Ensuring a fair hearing might entail allowing parties to object to or question the use of certain AI-derived inputs.
Confidentiality and Privacy: Confidentiality is a hallmark of arbitration. Ethical use of AI must guard against compromising the confidentiality of arbitral proceedings and sensitive data. Many popular AI services are cloud-based or hosted by third parties, which could pose risks if confidential case information (witness statements, trade secrets, etc.) is uploaded for analysis.

AI Use Cases and Real-World Examples

Despite the concerns, AI is already making tangible contributions in arbitration practice. A number of use cases and real-world examples demonstrate how AI tools are being applied by arbitral institutions, arbitrators, and parties:

Document Review and E-Discovery: Arbitration cases, especially international commercial and investment disputes, often involve massive document productions. AI-driven document review platforms (leveraging natural language processing and machine learning) can significantly speed up this process. Tools like Relativity and Brainspace use AI to sort and search document collections, identifying relevant materials and patterns without exhaustive human review.

Language Translation and Interpretation: In multilingual arbitrations, AI has proven valuable for translation. Machine translation systems (from general ones like Google Translate to specialized legal translation engines) can quickly translate submissions, evidence, or awards. Moreover, AI is being used for real-time interpretation during hearings: recent advances have allowed live speech translation and transcription.

Legal Research and Case Analytics: AI assists lawyers in researching legal authorities and prior decisions relevant to an arbitration. Platforms like CoCounsel (by Casetext) and others integrate AI to answer legal questions and find citations from vast databases. Products like Lex Machina and Solomonic (originally designed for litigation analytics) are being applied to arbitration data to glean insights on how particular arbitrators tend to rule, how long certain types of cases take, or what damages are typically awarded in certain industries.

Arbitrator Selection and Conflict Checking: Choosing the right arbitrator is crucial, and AI is helping make this process more data-driven. Traditional selection relied on reputation and word-of-mouth, but now AI-based arbitrator profiles are available. Additionally, AI is used for conflict of interest checks: law firms use AI databases to quickly check if a prospective arbitrator or expert has any disclosed connections to entities involved, by scanning CVs, prior cases, and public records. This ensures compliance with disclosure obligations and helps avoid later challenges.

Case Management and Procedural Efficiency: Arbitral institutions have begun integrating AI to streamline case administration. Furthermore, during proceedings, AI chatbots can answer parties’ routine questions about rules or schedules, easing the administrative burden.

Another emerging idea is AI prediction for settlement: parties might use outcome-prediction AI to decide whether to settle early. For instance, an AI might predict a 80% chance of liability and a damages range, prompting a party to offer or accept settlement rather than proceed. This was reportedly used in a few insurance arbitrations to successfully settle before award, with both sides agreeing to consult an algorithm’s evaluation as one data point in negotiations. These examples show that AI is not just theoretical in arbitration – it is actively being used to augment human work, in ways both big and small.

Arbitration Institutions Implementing AI Initiatives

ICC (International Chamber of Commerce)

The “ICC Overarching Narrative on Artificial Intelligence” outlines the ICC’s perspective on harnessing AI responsibly, stressing fairness, transparency, accountability, and inclusive growth. It promotes risk-based regulation that fosters innovation without stifling competition, encourages collaboration between businesses and policymakers, and calls for global, harmonized approaches that safeguard privacy, data security, and human rights. The ICC highlights the importance of fostering trust through robust governance, empowering SMEs and emerging markets with accessible AI tools, and ensuring AI’s benefits reach all sectors of society. While it does not specifically govern arbitration, the Narrative’s focus on ethical and transparent AI use offers guiding principles that align with the ICC’s broader commitment to integrity and due process.

AAA-ICDR (American Arbitration Association & Intl. Centre for Dispute Resolution)

In 2023 the AAA-ICDR published ethical principles for AI in ADR, affirming its commitment to thoughtful integration of AI in dispute resolution. It has since deployed AI-driven tools – for example, an AI-powered transcription service to produce hearing transcripts faster and more affordably, and a “AAAi Panelist Search” generative AI system to help identify suitable arbitrators/mediators from its roster. These initiatives aim to boost efficiency while upholding due process and data security.

JAMS (USA)

JAMS introduced the ADR industry’s first specialized AI dispute arbitration rules in 2024, providing a framework tailored to cases involving AI systems. Later in 2024 it launched “JAMS Next,” an initiative integrating AI into its workflow. JAMS Next includes AI-assisted transcription (real-time court reporting with AI for instant rough drafts and faster final transcripts) and an AI-driven neutral search on its website to quickly find arbitrators/mediators via natural language queries.

SCC (Arbitration Institute of the Stockholm Chamber of Commerce)

In October 2024, the SCC released a “Guide to the use of artificial intelligence in cases administered under the SCC rules” under its rules. This guideline advises arbitration participants (especially tribunals) on responsible AI use. Key points include safeguarding confidentiality, ensuring AI does not diminish decision quality, promoting transparency (tribunals are encouraged to disclose any AI they use), and prohibiting any delegation of decision-making to AI.

CIETAC (China International Economic and Trade Arbitration Commission)

CIETAC has integrated AI and digital technologies into its case administration. By 2024 it implemented a one-stop online dispute resolution platform with e-filing, e-evidence exchange, an arbitrator hub, and case management via a dedicated app – enabling fully paperless proceedings. CIETAC reports it has achieved intelligent document processing, including full digital scanning and automated identification of arbitration documents, plus a system for detecting related cases. CIETAC’s annual report states it is accelerating "the application of artificial intelligence in arbitration” to enhance efficiency and service quality.

Silicon Valley Arbitration & Mediation Center

The SVAMC Guidelines on the Use of Artificial Intelligence in Arbitration (1st Edition, 2024) present a comprehensive, principle-based framework designed to promote the responsible and informed use of AI in both domestic and international arbitration proceedings. These guidelines aim to ensure fairness, transparency, and efficiency by providing clear responsibilities for all arbitration participants—including arbitrators, parties, and counsel. Key provisions include the obligation to understand AI tools' capabilities and limitations, safeguard confidentiality, disclose AI usage when appropriate, and refrain from delegating decision-making authority to AI. Arbitrators are specifically reminded to maintain independent judgment and uphold due process. The guidelines also address risks like AI hallucinations, bias, and misuse in evidence creation. A model clause is provided for integrating the guidelines into procedural orders, and the document is designed to evolve alongside technological advancements.

The information provided is not legal, tax, investment, or accounting advice and should not be used as such. It is for discussion purposes only. Seek guidance from your own legal counsel and advisors on any matters. The views presented are those of the author and not any other individual or organization. Some parts of the text may be automatically generated. The author of this material makes no guarantees or warranties about the accuracy or completeness of the information.