THE AUTHOR:
Rida Ahmed, Marketing Manager US at Jus Mundi
The discourse surrounding Artificial Intelligence in dispute resolution has transitioned from speculative hype to operational reality. In 2026, the relevant inquiry is no longer whether AI will impact arbitration, but how practitioners can govern the tools that are already reshaping the field.
To navigate this paradigm shift, the Silicon Valley Arbitration and Mediation Center (SVAMC) and Jus Mundi recently inaugurated a four-part webinar series. The premier session, “AI and Arbitration: The Current State of Play,” convened Professor Abdi Aidid (Professor at the University of Toronto Faculty of Law and Canada Research Chair in AI and Access to Justice) and Annie Lespérance (Head of Americas at Jus Mundi) to delineate a practical roadmap for AI adoption.
For those unable to attend the live broadcast, the consensus was unambiguous: while AI significantly elevates the baseline of legal quality, it introduces novel risks that the arbitration community is only beginning to conceptualize.
Watch the Full Webinar Recording Here (passcode: @wmjV9R0)
Below are the five critical takeaways for the modern arbitration practitioner.
The Paradigm Shift: From Predictive to Agentic AI
The most profound development in legal technology is not merely an increase in velocity or accuracy, but a fundamental shift toward autonomy.
Historically, “legal AI” referred to predictive analytics; tools designed to identify patterns within static datasets. These systems could forecast case outcomes by correlating factual similarities with past rulings, yet they remained sophisticated pattern-matchers, constrained by the boundaries of their training data.
The advent of Generative AI marked the next phase. Large Language Models (LLMs) moved beyond analysis to synthesis, mastering the structural logic of language to draft contracts, memoranda, and arguments de novo.
We have now entered the era of Agentic AI. Unlike its predecessors, Agentic AI does not simply execute discrete tasks; it manages comprehensive workflows autonomously, rather than requiring a human to open documents, execute searches, and synthesize results. An agentic system receives a high-level command (“research and draft a memorandum on X”) and executes the entire chain of reasoning without iterative human intervention.
For arbitration practice, this necessitates a complete reimagining of workflow architecture. Practitioners must identify which multi-step processes — such as argument viability analysis, conflict checking combined with arbitrator profiling, or timeline construction paired with contradiction detection — are ripe for end-to-end automation. This transition represents a qualitative leap, requiring a strategic reassessment of which practice areas are ready for autonomous assistance.
AI Tools: Market Consolidation and the Rise of Hybrid Models
Lespérance explained that the legal technology landscape is undergoing a period of rapid maturation and consolidation. Understanding this market structure is essential for informed procurement.
Initially, the market was bifurcated. Legacy publishers (e.g., Thomson Reuters, LexisNexis, Wolters Kluwer) integrated AI layers into their proprietary databases, leveraging their competitive advantage in comprehensive, curated legal content. Conversely, a wave of new entrants (e.g., Harvey, Legora) focused on internal workflow optimization, allowing firms to analyze their own proprietary data without maintaining external legal repositories.
However, these distinct categories are converging. Through significant M&A activity —Thomson Reuters acquiring Casetext, LexisNexis acquiring Henchman, and Clio acquiring vLex — the market is racing toward vertical integration, offering both external research and internal workflow capabilities.
Simultaneously, providers like Jus Mundi are engineering hybrid models from the outset. These platforms allow practitioners to upload confidential documents to a secure “vault” while simultaneously querying verified external databases, effectively unifying internal document analysis with comprehensive legal research.
For the buyer, the distinction is critical: Are you purchasing a research engine, a workflow engine, or a hybrid ecosystem? Resources such as the Legal Technology Hub are invaluable for comparing vendors against these evolving metrics. Ultimately, specialized tools architected specifically for the nuances of arbitration are delivering superior value compared to general-purpose models.
The “Equalizer Effect” of AI: Empirical Data on Legal Quality
Research conducted by the University of Minnesota offers a compelling, data-driven corrective to assumptions about AI’s impact on legal competence.
The study stratified law students by objective performance metrics (GPA and LSAT scores) and tasked them with drafting memoranda, contracts, and complaints using tools like ChatGPT. While speed increased universally, quality improvements followed a distinct “equalization” pattern. Students previously producing “D-level” work advanced to “C-level” quality; “C-level” performers rose to “B-level”; and “B-level” students achieved “A-level” results.
Notably, top-tier performers saw negligible quality gains unless they invested significant additional effort to refine the AI’s output.
These findings suggest that AI functions as a floor-raiser, not a ceiling-raiser. It is exceptionally effective at standardizing quality across a firm, allowing junior associates to produce competent work rapidly. However, deep substantive expertise remains the differentiator; technology does not obviate the need for experience. When top performers leverage AI strategically, they do not just maintain their lead, they extend it.
Real-world validation reinforces this academic data. When Jus Mundi recruited 20 leading arbitration practitioners to stress-test Jus AI on complex research queries, the system achieved an average rating of 4.2 out of 5, with zero failures. This confirms that when properly designed, specialized AI tools meet the rigorous standards of international practice.
Workflow Mapping as Competitive Advantage
Lespérance underscored a pivotal insight: competitive advantage derives not from the mere possession of AI tools, but from the strategic mapping of these capabilities against specific phases of the arbitration lifecycle.
- Legal Research: AI compresses days of manual review into minutes, allowing for granular analysis of how specific arbitrators have adjudicated narrow issues across dozens of awards.
- Legal Analysis: In document-heavy disputes, AI excels at systematic review: identifying factual patterns, constructing timelines, and flagging contradictions between witness testimony and documentary evidence.
- Strategic Drafting: Acting as an “sparring partner,” AI can stress-test arguments, anticipate opposing counsel’s counterclaims, and interpret arbitration clauses against a backdrop of historical case law.
- Legal Translation: With relevant precedents often existing in languages other than English, AI-powered multilingual search ensures no strategic intelligence is lost to language barriers.
Crucially, the application of these tools varies by stage. During tribunal constitution, AI facilitates comprehensive conflict checks and behavioral analysis. During written submissions, it tailors arguments to the specific predilections of the tribunal. The practitioners who proactively map these workflows, identifying bottlenecks and quality control gaps, will deploy AI strategically rather than reactively.
The Ethical Frontier: Disclosure and Deepfakes
The discussion addressed two immutable challenges: the evolving standards of disclosure and the evidentiary threat of deepfakes.
The Disclosure Debate: The regulatory framework for disclosing AI use remains nascent. While the EU AI Act categorizes substantive decision-making as high-risk (requiring disclosure), the use of AI for stylistic or linguistic polish exists in a “gray area.”
Debate persists regarding whether AI-assisted drafting of procedural histories differs materially from delegation to a junior associate. However, given that AI carries distinct risks regarding data integrity and “hallucinations,” the emerging best practice is one of reciprocal transparency: arbitrators should disclose their use of AI to the extent they would expect the parties to do the same.
The Deepfake Problem: Unlike “hallucinations,” which are technical errors that can be mitigated, deepfakes represent an adversarial threat. Incentives align toward making deepfakes more deceptive and realistic, creating a permanent arms race between generation and detection.
The risk is amplified by the psychology of remote hearings. Participants are conditioned to forgive video lag, sync issues, and low resolution, effectively lowering the threshold for a deepfake to be convincing. Because detection tools rely on the same learning data as generation tools, there is no permanent defensive advantage, and the responsibility is increasingly shifting to counsel to certify the authenticity of digital evidence.
The Road Ahead
Professor Aidid’s closing analogy encapsulates the path forward: AI functions akin to modern aviation. It provides the most efficient transit between two points, yet it demands rigorous oversight: a “pilot in the cockpit,” strict regulatory protocols, and robust failsafes.
The challenge facing the arbitration community is to adopt these tools with a clear-eyed view of their capabilities and their limitations; verifying the hallucinations we can detect, while remaining vigilant against the deepfakes we cannot.
This four-part webinar series is dedicated to resolving these complexities. The conversation continues the week of April 13th.
About Jus Mundi
Founded in 2019 and recognized as a mission-led company, Jus Mundi is a pioneer in the legal technology industry dedicated to powering global justice through artificial intelligence. Headquartered in Paris, with additional offices in New York, London, and Singapore. Jus Mundi serves over 150,000 users from law firms, multinational corporations, governmental bodies, and academic institutions in more than 90 countries. Through its proprietary AI technology, Jus Mundi provides global legal intelligence, data-driven arbitration professional selection, and business development services.
*The views and opinions expressed by authors are theirs and do not necessarily reflect those of their organizations, employers, or Daily Jus, Jus Mundi, or Jus Connect.
