AUTHOR- KAJAL PRAJAPATI
UNIVERSITY- SHRI RAMSWAROOP MEMORIAL UNIVERSITY
Headline of the Article
The Rise of Artificial Intelligence in Dispute Resolution: A Paradigm Shift with Legal and Ethical Implications
Abstract
This article examines the increasing adoption of Artificial Intelligence (AI) in dispute resolution, highlighting its transformative efficiency, cost-effectiveness, and analytical power. It evaluates doctrinal and practical implications—particularly concerning due process, data privacy, liability, and oversight. The paper draws on recent arbitration jurisprudence, legislative reforms, and ethical frameworks, ultimately asserting that while AI enhances legal practice, it cannot supplant human judgment.
To the Point
AI is gaining traction in legal research, document analysis, predictive analytics, and arbitration assistance.
The 2025 International Arbitration Survey suggests 91% of lawyers expect AI to become pervasive in data-intensive cases within five years
Ethical, transparency, and liability concerns confront AI’s integration in judicial and arbitral contexts.
Use of Legal Jargon
Terms such as algorithmic adjudication, automated document review, predictive coding, due process, opaque decision-making mechanisms, adversarial fairness, and judicial oversight feature prominently throughout this inquiry into AI’s juridical impact.
The Proof
Empirical Data: The 2025 International Arbitration Survey found 91% of practitioners anticipate AI’s routine use in research and analytics within five years; however, only 15% support AI drafting legal reasoning
Academic Analysis: ArXiv research identifies major ethical concerns surrounding AI in judicial settings—including bias, accountability, and hallucinations .
Case Laws
- Gayatri Balasamy v ISG Novasoft Technologies Ltd (April 30, 2025)
The Supreme Court, in a five-judge bench, clarified that courts have limited power under Section 34 of the Arbitration and Conciliation Act to modify arbitral awards, but only in discrete scenarios—clerical errors, post-award interest, or severable portions—while reaffirming party autonomy
- State of Tamil Nadu v Governor of Tamil Nadu (April 8, 2025)
Although this case focuses on constitutional limits on the Governor’s veto, it highlights the judiciary’s willingness to define precise frameworks for decision-making power—a useful analog to regulating AI discretion .
Discussion
Efficiency Gains vs Ethical Risks
AI significantly accelerates legal workflows—document reviews and data analytics—reducing costs and workload. For example, predictive coding allows faster identification of relevant documents in complex litigation. Yet, only a minority of practitioners (15%) trust AI to draft legal awards, underscoring persistent concerns about accuracy and interpretability
Accountability, Bias, and Due Process
Algorithmic opacity raises questions: Who is responsible if AI misjudges facts or misapplies law? Existing case law (e.g., Gayatri Balasamy) permits limited judicial correction, but not wholesale AI adjudication. Ethical authors stress the importance of transparent datasets and human oversight
Privacy, Data Protection, and Security
Legal data is inherently sensitive—contracts, personal histories, arbitration submissions. Ensuring confidentiality and regulatory compliance with frameworks such as GDPR is essential.
Regulatory and Legislative Landscape
Global regulatory measures are emerging: the EU’s draft AI Act mandates risk assessments for high-stakes systems, while various U.S. statutes (like the “TAKE IT DOWN Act” for deepfakes) reflect growing legislative attention
The Human Factor
Despite AI’s strengths, human legal professionals remain indispensable for contextual understanding, moral judgments, and client trust. The 2025 Arbitration Survey notes that AI serves as a tool—not a substitute—for human decision-making
Conclusion
AI is ushering in a revolution in dispute resolution—streamlining research, document analysis, and predictive analytics. However, integration must be balanced with robust safeguards: transparency, liability structures, and regulatory clarity. Courts like in Gayatri Balasamy reinforce that judicial oversight remains central. Ultimately, AI should function as an assistant—not an arbiter—in preserving both fairness and efficiency in justice delivery.
FAQ
What role can AI play in arbitration?
AI assists in document review, legal research, and outcome prediction, improving efficiency; but arbitral decisions must continue to be drafted and signed by human arbitrators.
What safeguards are needed when using AI?
Meatdcontrols: bias audits, robust data protection, mechanisms for appeal or correction, and human approval for final outputs.
Is AI-generated evidence admissible in court?
Currently yes—as long as its source, methodology, and limitations are disclosed and human authentication is assured.
Who is liable for AI-generated errors?
Liability may rest with deploying entities—law firms or tech providers—unless express contract provisions shift responsibility or indemnity.
When might AI replace human lawyers?
In routine, high-volume tasks (e.g., document classification). But for nuanced judgment, client empathy, and adversarial advocacy, human experts will continue to lead.
