Use Of AI In Indian Judiciary - Challenges, Opportunities And Constitutional Concerns
Author: LawSphereX
Category: Constitutional Law
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USE OF AI IN INDIAN JUDICIARY: CHALLENGES,
OPPORTUNITIES AND CONSTITUTIONAL CONCERNS
Suneha Goria, B.A. LL.B., NIMS University, School of Law, Jaipur, Rajasthan.
ABSTRACT
AI is reshaping judicial administration in India through tools such as virtual courts, e-filing systems, SUPACE (search and analytics), and SUVAS (Supreme Court Vidhik Anuvaad Software)- to improve efficiency and reduce pendency. These tools show potential for enhancing legal research, streamlining case management, and expanding access to justice, but their growing use raises constitutional, ethical, and legal concerns This paper critically analyses opportunities and challenges in integrating AI into the Indian judicial process. It argues that AI can assist in speeding up case disposal, increasing transparency, and improving administrative functioning while also creating risks of algorithmic bias, threats to privacy, accountability gaps, and erosion of reasoned principles under Articles 14 and 21 (equality, privacy, and fair trial).
After surveying recent judicial opinionsincluding “Supreme Court’s March 2026 warning on AI-generated citations as “misconduct” and “Gujarat High Court’s April 2026 restriction on judicial use of AI”, the paper proposes safeguards – human-in-the-loop rules, explainability standards, data governance, audits, and pilot-based evaluationso that AI functions as an aid to judges rather than a substitute for judicial discretion. 1 The paper concludes that a transparent, human-centric governance framework can modernize the Judiciary without undermining constitutional protections. Keywords: Artificial Intelligence, Indian Judiciary, Constitutional Law, Article 14, Article 21, Judicial Technology, Access to Justice, Algorithmic Bias, SUPACE, SUVAS. 1BBC News, India’s Top Court Angry After Junior Judge Cites Fake AI-Generated Orders (Mar. 3, 2026), https://www. bbc. com/news/articles/c178zzw780xo
1 https://www.medianama.com/2026/03/223-supreme-court-ai-fake-case-laws-misconduct/
1 https://www.nationalheraldindia.com/national/gujarat-hc-bars-ai-from-judicial-decision-making-drafting-oforders-and-judgments 1 https://www.barandbench.com/news/gujarat-high-court-bans-use-of-ai-by-judges-court-staff-in-judicial-work
INTRODUCTION:
The judiciary constitutes an independent constitutional institution entrusted with administering justice in India’s socially and economically diverse society. With an enormous backlog - currently estimated at over 52 million cases in subordinate courts, millions in High Courts and tens of thousands before the Supreme Court according to the National Judicial Data Grid (NJDG) – the pressure to modernize is acute.2 Technology is already reshaping the system: platforms such as SCC Online, SUPACE, SUVAS and e-filing, and the e-courts Project Phase III are expanding access to judicial information and administrative capacity.
The Government has allocated ₹7,210 crore for e-courts Phase III, including ₹53.57 crore specifically earmarked for AI and Blockchain technologies across High Courts up to 2027. These initiatives can reduce delay, improve legal research, and make justice more accessible, particularly for litigants with limited resources.3 At the same time, introducing AI into judicial processes raises constitutional concerns about fairness, transparency, privacy, and the preservation of judicial discretion. Judicial decision-making involves values, contextual empathy, and normative reasoning that cannot be mechanically captured. This paper evaluates how AI can be integrated in a way that enhances access and efficiency while remaining subject to constitutional safeguards.
RESEARCH METHODOLOGY:
This study adopts a doctrinal and analytical research methodology. Primary sources include constitutional provisions, judicial decisions, policy documents of the Supreme Court e- Committee, government reports, and official judicial initiatives relating to artificial intelligence. Secondary sources include academic articles, legal commentaries, reports of international organizations, and scholarly literature on AI governance and judicial technology. The study critically examines the constitutional challenges arising from AI adoption in judicial processes and evaluates existing safeguards through a constitutional lens.
2 https://indiadatamap.com/2025/10/18/pending-court-cases-in-india-2025/
2 https://www.scobserver.in/journal/july-2025-pendency-soars-to-a-staggering-87000-cases/
2 https://www.scobserver.in/journal/june-2025-supreme-court-records-highest-pendency-of-the-year-so-far/ 2 National Judicial Data Grid (NJDG), E-Committee, Supreme Court of India, https://njdg.ecourts.gov.in/
2 https://njdg.ecourts.gov.in/hcnjdg_v2/
3 https://ommcomnews.com/india-news/rs-7210-crore-project-to-boost-use-of-ai-tech-in-courts-arjun-rammeghwal/
RESEARCH QUESTIONS:
1. What role can artificial intelligence play in improving the efficiency of the Indian
Judiciary?
2. What constitutional concerns arise from the integration of AI into judicial processes?
3. Can AI-assisted judicial administration coexist with judicial independence and due
process requirements?
4. What safeguards are necessary to ensure responsible and constitutional-compliant use
of AI in courts?
OBJECTIVES OF THE STUDY:
o To examine the existing use of AI tools within the Indian judicial system. o To evaluate the opportunities offered by AI in enhancing judicial efficiency and access to justice. o To analyze constitutional concerns relating to equality, privacy, accountability, and fair trial rights. o To study recent judicial opinions and policy developments concerning AI. o To propose a framework for responsible AI governance in the judiciary.
LITERATURE REVIEW:
Contemporary scholarship on artificial intelligence in judicial systems presents both optimistic and cautionary perspectives. Several scholars argue that AI can significantly improve legal research, case management, and administrative efficiency. Others warn that algorithmic decision-making may reproduce historical biases and undermine procedural fairness.4 International organizations such as UNESCO and the OECD emphasize transparency,
4 https://www.tandfonline.com/doi/full/10.1080/0270319X.2026.2617784
4 https://www.nextias.com/ca/editorial-analysis/21-05-2026/ai-judiciary-india
4 Vidhi Centre for Legal Policy, Responsible AI for the Indian Justice System: A Strategy Paper (2021), https://vidhilegalpolicy.in/research/responsible-ai-for-the-indian-justice-system-a-strategy-paper/
accountability, and human oversight as foundational principles for trustworthy AI. Indian legal scholars generally support the use of AI for administrative and research purposes while cautioning against its deployment in core adjudicatory functions that require human judgment, constitutional reasoning, and ethical evaluation.5
RESEARCH GAP:
Although existing literature extensively discusses the technological potential of AI and comparative experiences from foreign jurisdictions, limited scholarship has examined the constitutional implications of AI-assisted judicial administration in India in light of recent policy developments and judicial responses. This study seeks to bridge that gap by critically evaluating the opportunities and risks associated with AI adoption in the Indian judiciary through the framework of Articles 14. 19, and 21 of the Constitution and by proposing safeguards for constitutionally compliant implementation.6
CHALLENGES AND CONSTITUTIONAL CONCERNS:
Practical limits of AI for judicial decision-making: AI can improve court administration and legal research, but it cannot replicate the normative judgment required for many judicial decisions. Courts must weigh social realities, empathy, constitutional morality, and proportionality – factors that depend on normative evaluation and context-sensitive discretion. Excessive reliance on predictive or prescriptive systems may reduce adjudication to algorithmic outputs that fail to adequately account for contextual and normative considerations. - Risk of inequality and digital exclusion: India’s social and digital divides mean technology-driven mechanisms can exclude vulnerable groups. Rural litigants, the poor, the elderly, and those with limited digital literacy may face barriers to accessing AI-enabled services.
Without affirmative inclusion measures, AI could exacerbate existing inequities, contrary to Article 14’s equality mandate. 5 https://vidhilegalpolicy. in/research/responsible-ai-for-the-indian-justice-system-a-strategy-paper/ 6 https://www. nationalheraldindia. com/national/gujarat-hc-bars-ai-from-judicial-decision-making-drafting-oforders-and-judgments
6 https://www.bbc.com/news/articles/c178zzw780xo
Algorithmic bias and fairness (Article 14): AI systems trained on historical judicial records or administrative data may replicate past bias (caste, gender, class, socioeconomic status). If these systems influence outcomes- even indirectly via case prioritization or risk scores – they can perpetuate discriminatory patterns, undermining Article 14’s promise of equal treatment. 7 - Freedom of Speech and Access to Information (Article 19): The deployment of AI within judicial institutions may also raise concerns under Article 19(1)(a) of the Constitution. Algorithmic filtering, automated legal information systems, and Access to legal information forms an important component of the right to receive information under Article 19(1)(a).
Any opaque algorithmic filtering of legal databases or court information may affect citizens’ ability to access legal knowledge and participate effectively in judicial processes. - Data protection and privacy: Judicial records often contain sensitive personal information. Use of court data for AI training and processing raises privacy risks. The Supreme Court’s recognition of privacy as a fundamental right (K. S. Puttaswamy v. Union of India) implies that the state must ensure adequate safeguards when using personal data. Data minimization, anonymization standards, and secure storage must guide any AI deployment. 8 - Accountability and transparency: When AI tools influence judicial administration or recommendations, responsibility must be clearly allocated. Who is accountable for errors – the developer, the agency operating the system, or the presiding judge?
Courts require transparency about data sources, model logic, and error rates; independent audits and public documentation (model cards) should be mandatory for high-risk uses. Recent incidents underscore these risks: In a 2024 incident at a Vijayawada trial court dismissed a case citing four Supreme Court judgments that were later found to be completely fabricated by AI. The Supreme Court termed this “misconduct” in March 2026 and flagged “institutional concerns” about AI hallucinations in judicial orders. 9 7 https://www. thehinducentre. com/incoming/ai-and-the-indian-judiciary-the-need-for-a-rights-based-approachhtml-version/article68917505. ece 8 https://vidhilegalpolicy. in/research/responsible-ai-for-the-indian-justice-system-a-strategy-paper/
9 https://www.medianama.com/2026/03/223-supreme-court-ai-fake-case-laws-misconduct/
OPPORTUNITIES: TRANSLATING TECH INTO EFFICIENCY:
While the structural and constitutional risks of AI demand rigorous scrutiny, the technological tools currently deployed across the Indian legal landscape present unprecedented opportunities to streamline auxiliary judicial operations. These interventions do not replace judicial reasoning: instead, they serve as cognitive escalators that address the procedural bottlenecks crippling the administration of justice. Democratizing the Language of the Court: India’s multilingual reality has historically functioned as a barrier to legal literacy and access to justice. The Supreme Court Vidhik Anuvaad Software (SUVAS) directly addresses this by utilizing machine learning trained on specialized legal corpora to translate complex English Judgments into vernacular languages.
10 - By translating tens of thousands of judgments into regional languages (including Hindi, Tamil, Marathi, and Kannada) via the e-SCR portal by early 2024, SUVAS minimizes litigant’s structural dependence on expensive, English-fluent appellate counsel. - This linguistic inclusion is further augmented by “Su Sahay” launched May 10, 2026 by CJI Surya Kant, an AI-powered interactive conversational assistant deployed on the Supreme Court website. Su Sahay acts as intuitive front-end guide, converting complex portal navigation into natural language interactions for common citizens. 11 Optimizing Information Extraction and Research Velocity: Judicial preparation often requires examining thousands of pages of legacy records, depositions, and pleadings.
Platforms such as the Supreme Court Portal for assistance in Court Efficiency (SUPACE) and the Legal Research Analysis Assistant (LegRAA) operate as advanced legal search engines. 12
9 https://www.bbc.com/news/articles/c178zzw780xo
10 https://www.linkedin.com/pulse/ai-apex-court-how-suvas-supace-shaping-indias-eew7c
10 https://indiaai.gov.in/article/can-artificial-intelligence-ai-revolutionize-india-s-judiciary-system 11 https://www.newindianexpress.com/amp/story/nation/2026/May/11/cji-surya-kant-launches-one-case-onedata-initiative-announces-ai-chatbot-su-sahay
12 https://www.drishtiias.com/daily-updates/daily-news-analysis/ai-portal-supace
1. Instead of performing rudimentary keyword searches, these tools utilize Natural
Language Processing (NLP) to extract relevant facts, trace doctrinal history, and cluster parallel precedents within criminal and civil dockets.
2. By automating the mechanical gathering of case history, these assistants dramatically
lower the time required for a judge’s chamber to compile a case brief, allowing judicial minds to focus more time on core normative adjudication. Administrative Integration via “One Case One Data”: The administrative silo between the subordinate courts, High Courts, and the Supreme Court frequently results in asymmetric information tracking and scheduling conflicts. The implementation of the “One Case One Data” launched May 2026, establishes a uniform, interconnected digital database across all judicial tiers. This platform enables reciprocal data access, automated electronic scrutiny for filing defects, and intelligent, machine-driven docket scheduling. By systematically detecting anomalies in listing dates and organizing files across a centralized network, the system reduces routine clerical delays and suppresses tactical adjournment requests by counsel.
COMPARATIVE INTERNATIONAL PERSPECTIVE:
China has extensively implemented AI-driven ‘smart courts’ for case management, document analysis, and online dispute resolution. While these systems have enhanced efficiency, concerns regarding transparency and algorithmic accountability persist. The European Union follows a rights-based approach through the EU AI Act, which classifies judicial AI systems as high-risk technologies and requires strict human oversight, transparency, and accountability measures. In the United States, AI tools are primarily used for legal research and risk assessment. However, controversies involving predictive algorithms such as COMPAS have highlighted concerns regarding bias and procedural fairness. These international experiences demonstrate that while AI can improve judicial administration, human oversight and constitutional safeguards remain essential. India should adopt a balanced
model that encourages innovation while preserving judicial independence and fundamental rights.13
RECENT JUDICIAL OPINIONS AND POLICY INITIATIVES:
The intersection of algorithmic intervention and statutory adjudication has driven recent policymaking and high-level judicial declarations in India. Rather than issuing binding statutory regulations, the Supreme Court has favored a cautious approach that balances technological convenience with systemic safeguards. a) The Chief Justice’s Directives on Core Adjudication: Addressing the growing global trend of Judges utilizing generative AI chatbots for automated drafting, the Chief Justice of India issued a definitive structural boundary regarding the limits of automation in trial and appellate courts. The Court emphasized that while AI creates immense procedural convenience, the “independence and human discretion of judges must remain central to the Indian justice system.
”14 The directive explicitly establishes that AI systems are strictly restricted to producing reference material and administrative outputs. Under no circumstances may an automated system generate a final, authoritative judgment or replace a judge’s personal assessment of evidentiary elements. b) The Gujarat High Court’s April 2026 Policy Ban In a landmark policy unveiled on April 4, 2026, the Gujarat High Court prohibited the use of AI in judicial decision-making, reasoning, and drafting of orders or judgments. The policy states that AI tools cannot be used for “any aspect of judicial decision, adjudication, reasoning or final judgment”. 15 The court has barred AI from being used in: • Judicial reasoning and interpretation of law.
13 https://www.tandfonline.com/doi/full/10.1080/0270319X.2026.2617784
14 https://www.pib.gov.in/PressReleseDetailm.aspx?PRID=2113224
15 https://www.barandbench.com/news/gujarat-high-court-bans-use-of-ai-by-judges-court-staff-in-judicial-work
Drafting of orders, judgments, or bail decisions. • Determination of rights, liabilities, or sentencing. • Evaluation of evidence or facts. It also prohibits relying on AI-generated citations and legal references without independent verification. c) The Supreme Court White Paper on Judiciary and AI: The Supreme Court e-committee’s comprehensive policy documentation aligns India’s internal digital transition with international governance benchmarks- specifically drawing from the UNESCO and OECD frameworks on responsible AI. 16 The policy mandates that any technology embedded within the Case Information Systems (CIS 4.
0) or the Integrated Case Management & Information System (ICMIS) must abide by three strict operational criteria: Human Verification: Any case summary, precedent mapping, or structural translation produced by tools like LegRAA or SUVAS must undergo mandatory manual verification by a human officer before admitted into court records. Lawyer Accountability: Counsel cannot shield professional errors behind technological failure; legal practitioners remain personally liable for the factual accuracy and authenticity of every citation submitted. The presentation of AI-generated “hallucinated” or fictional case citations is officially classified as professional misconduct.
Administrative Oversight: Dedicated sub-committees comprising High Court judges and technical experts hold the exclusive mandate to audit algorithmic models for data privacy leaks, ensuring that court archives are not commercialized or scraped by private legal tech developers.
PROPOSED SAFEGUARDS: A HUMAN-CENTRIC FRAMEWORK:
To prevent the gradual erosion of constitutional guarantees, the integration of AI within the Indian Judiciary must be governed by a multi-tiered accountability architecture. The following 16 https://visionias.in/current-affairs/news-today/2025-11-25/polity-and-governance/supreme-courts-centre-forresearch-and-planning-releases-white-paper-on-artificial-intelligence-and-the-judiciary
five-part framework establishes the technical and legal protocols required to keep technology subordinate to human judgment.
1. The Doctrine of the Non-Delegable Core:
A structural rule must be codified within court rules across all jurisdictions to define a nonnegotiable boundary between administrative assistance and active adjudication. AI systems must be completely banned from generating prescriptive recommendations on: o Criminal sentencing metrics. o Bail evaluations. o The determination of witness credibility or intent (mens rea). The judicial footprint of machine learning must be locked within auxiliary tasks, such as mathematical calculations for motor accident claims, traffic violations, property title tracing and linguistic translation.
2. Mandatory Explainable AI (XAI) Architectures:
The judiciary must enforce a zero-tolerance policy against proprietary, closed source “black box” algorithms in court management. If an AI tool is deployed to prioritize cases or group dockets, it must utilize transparent models or post-hoc explainability frameworks (such as LIME or SHAP).17 A judge, litigant, or reviewing counsel must be capable of tracing the exact statistical
parameters and data weights that led to a specific algorithmic output. This transparency is vital to preserve the right to a fair trial and to protect the long-standing requirement for a reasoned judicial order.
3. Rigorous Data Governance and Anonymization Protocols:
In strict compliance with the data protection mandates recognized in K.S. Puttaswamy v. Union of India, Phase III’s Judicial Digital Repositories must feature decentralized, client-
17 https://www.nextias.com/ca/editorial-analysis/21-05-2026/ai-judiciary-india
side data minimization pipelines.18 Before any historical trial court record is ingested into a training database for machine learning models, sensitive personal identifiers- including the names of victims of genderbased violence, matrimonial disputes, juvenile records, and witness identification datamust be permanently and irreversibly masked. This approach guarantees that public data repositories do not become tools for automated corporate profiling or privacy violations.
4. Independent Algorithmic Auditing for Socioeconomic Bias:
Every AI model integrated into the court system must undergo mandatory, periodic auditing conducted by independent, interdisciplinary oversight bodies comprising senior judges, data scientists, and civil society advocates. These audits must actively test models against curated datasets to detect embedded systemic biases along lines of gender, caste, religion, and socio-economic vulnerability. Any model displaying a skewed error rate or a discriminatory trend against marginalized populations must be taken offline immediately for retraining.
5. Pilot-Based Controlled Sandbox Evaluation:
No AI-driven court management application should be scaled globally without undergoing a phased trial inside a controlled regulatory sandbox. These models must first run as parallel background systems in select pilot dockets, such as specialized commercial divisions or small-claims traffic courts. Their outputs must be rigorously evaluated against concurrent decisions made by human judges to measure variance, error rates, and user friction. Only after satisfying strict benchmarks for reliability, data accuracy, and equity should these systems be approved for wider deployment.
KEY FINDINGS:
AI has substantial potential to improve judicial efficiency through enhanced legal 18 https://vidhilegalpolicy.in/research/responsible-ai-for-the-indian-justice-system-a-strategy-paper/
research, translation services, and administrative automation.19 • Existing judicial initiatives such as SUPACE and SUVAS demonstrate that AI can function effectively as an assistive technology.20 • Constitutional concerns relating to equality, privacy, transparency and accountability remain significant obstacles to wider adoption.21 • Recent judicial and policy developments indicate a strong institutional preference for maintaining human control over adjudicatory functions.22 • A human-centric regulatory framework is essential to ensure that AI supports, rather than undermines, the constitutional values underlying the justice system.23
LIMITATIONS OF THE STUDY:
This study is primarily doctrinal in nature and relies upon judicial decisions, policy documents, and secondary academic literature. The rapidly evolving nature of artificial intelligence means that future technological developments may alter the legal and constitutional issues discussed herein. Furthermore, the limited availability of empirical data regarding the performance of AI systems within courts restricts quantitative evaluation of their effectiveness.
CONCLUSION:
BALANCING
INNOVATION
WITH
CONSTITUTIONAL
FIDELITY
The integration of AI into India’s judiciary represents not merely a technological upgrade but a constitutional test. As this paper has demonstrated, AI tools like SUPACE and SUVAS offer transformative potential- accelerating legal research, breaking language barriers, and reducing administrative bottlenecks that have plagued the Indian justice system for decades. The governments ₹7,210 crore investment in e-Courts Phase III signals a serious commitment to
19 https://www.tandfonline.com/doi/full/10.1080/0270319X.2026.2617784
20 https://www.linkedin.com/pulse/ai-apex-court-how-suvas-supace-shaping-indias-eew7c
21 https://www.thehinducentre.com/incoming/ai-and-the-indian-judiciary-the-need-for-a-rights-based-approachhtml-version/article68917505.ece
22 https://www.bbc.com/news/articles/c178zzw780xo
23 https://www.nextias.com/ca/editorial-analysis/21-05-2026/ai-judiciary-india
digital modernization.24 However, the recent controversy over AI-generated hallucinated judgments- and the Supreme Court’s unequivocal labeling of such reliance as ‘misconduct’ – serves as a sobering reminder that efficiency cannot come at the cost of judicial integrity. The Gujarat High Court’s April
2026 policy, which explicitly bars AI from judicial decision-making, reasoning, and judgment
drafting, reflects a growing institutional consensus: AI must remain a tool, not a substitute. 25 The constitutional concerns raised in this paper- algorithmic bias violating Article 14, privacy infringements contravening Article 21, and accountability gaps undermining the rule of laware not theoretical. They are urgent, tangible risks that demand proactive governance. The fivepart safeguard framework proposed here- non-delegable core, explainable AI, data governance, independent auditing, and sandbox evaluation- provides a practical roadmap for responsible integration. 26 Ultimately, the Indian judiciary’s adoption of AI must be guided by a simple principle: technology should amplify human judgment, not replace it. Judicial decision-making extends beyond computational analysis and involves moral reasoning, contextual evaluation, and human judgment.
AI can help judges process information faster, access precedents more efficiently, and communicate with litigants in their native languages. But the core acts of adjudication- weighing evidence, interpreting constitutional values, exercising empathy, and delivering reasoned orders- must remain firmly in human hands.
FUTURE ROADMAP: A CALL FOR COLLABORATIVE GOVERNANCE:
Looking ahead, India’s journey with AI in the judiciary requires sustained collaboration across multiple stakeholders: For the Supreme Court e-Committee; • Establish a National Judicial AI Governance Council comprising judges, technologists, 24 https://www.thehawk.in/news/india/rs-7210-crore-project-to-boost-use-of-ai-tech-in-courts-arjun-rammeghwal
25 https://www.medianama.com/2026/03/223-supreme-court-ai-fake-case-laws-misconduct/
26 https://www.nextias.com/ca/editorial-analysis/21-05-2026/ai-judiciary-india
civil society representatives, and privacy experts to oversee AI deployment standards. 27 • Develop binding model rules on AI use that all High Courts must adopt, creating uniformity across jurisdictions. • Create a public registry of approved AI tools with transparency reports on performance, error rates, and audit findings. For the Legislature; • Enact specific legislation governing AI in judicial processes, filling the current regulatory gap. • Amend the Information Technology Act and Evidence Act to address AI- generated content, hallucinations, and digital authentication. 28 • Mandate parliamentary oversight of Ai spending and implementation in the justice sector. For the Legal Community; • Integrate AI literacy training into Bar Council curriculum and continuing legal education requirements.
29 • Develop ethical guidelines for lawyers using AI tools, with clear consequences for misconduct. • Create bar association oversight committees to monitor AI-related professional ethics violations. For technology Developers; • Prioritize open-source, auditable models over proprietary black boxes for judicial
27 https://www.nextias.com/ca/editorial-analysis/21-05-2026/ai-judiciary-india
28 https://www.bbc.com/news/articles/c178zzw780xo
29 https://www.nextias.com/ca/editorial-analysis/21-05-2026/ai-judiciary-india
applications.30 • Implement bias testing protocols before deployment, with regular third-party audits. • Design human-in-the-loop interfaces that make AI assistance visible and reviewable. For Civil Society and Academia; • Conduct independent research on AI’s impact on marginalized communities in the justice system.31 • Build public awareness campaigns about AI’s capabilities and limitations in legal contexts. • Develop community monitoring mechanisms to hold courts accountable for transparent AI use.
FINAL THOUGHTS:
India stands at a critical juncture. The choices made today about AI in the judiciary will shape the administration of justice for generations. If approached with caution, transparency, and constitutional fidelity, AI can help realize the promise of the Indian Constitution-to secure justice, liberty, equality, and dignity for all citizens. But if rushed, unregulated, or deployed without adequate safeguards, AI risks entrenching existing inequalities, eroding public trust, and compromising the very foundation of judicial independence. The path forward requires not technological optimism alone, but wisdom, humility, and an unwavering commitment to the human dimensions of justice. As the Supreme Court has rightly observed, the independence and human discretion of judges must remain central. AI can be the judiciary’s most powerful assistant-but it must never become its master.
30 https://www.nextias.com/ca/editorial-analysis/21-05-2026/ai-judiciary-india
31 https://www.thehinducentre.com/incoming/ai-and-the-indian-judiciary-the-need-for-a-rights-based-approachhtml-version/article68917505.ece
BIBLIOGRAPHY
PRIMARY SOURCES (Official Government & Judicial Documents)
1. Constitutional Provisions:
INDIA CONST. arts. 14,19, 21.
2. Case Law:
K.S. Puttaswamy v. Union of India, (2017) 10 SCC 1.
3. Statutes & Policy Documents:
i. Supreme Court of India, Centre for Research and Planning (CRP), “White Paper on Artificial Intelligence and Judiciary” (Supreme Court e-Committee, November
2025) https://www.sci.gov.in/reports/
ii. Gujarat High Court, “Policy on Use of Artificial Intelligence in Judicial and Court Administration” (April 4, 2026) https://www.nationalheraldindia.com/national/gujarat-hc-bars-ai-from-judicialdecision-makinh-drafting-of-orders-and-judgments iii. E-Committee, Supreme Court of India, “National Judicial Data Grid (NJDG) https://njdg.ecourts.gov.in (accessed May, 2026). iv. Department of Justice, Government of India, “Phase-III of e-Courts Mission Mode Project” https://doj.gov.in/phase-iii/ (updated August 22, 2025). v. Press Information Bureau, Government of India, “Use of AI in Supreme Court Case Management” (November 19, 2025) https://pib.gov.in/PressReleasePage.aspx?PRID=2113224
SECONDARY SOURCES
1. Books & Book Chapters:
Baxi, Upendra, “On How Not to Judge the Judges,” 25 JILI 211(1983).
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Prasad, Malavika, “Gujarat High Court Bars Judges from Using Artificial Intelligence in Decision Making, Reasoning, Interpretation,” LiveLaw (April 4, 2026) https://www. nationalheraldindia. com/national/gujarat-hc-bars-ai-from-judicialdecision-making-drafting-of-orders-and-judgments • “Gujarat high court bans AI in key judicial processes,” Rediff (April 3, 2026) https://www. rediff. com/news/report/gujarat-hc-bans-ai-in-decision-makingjudgments/20260404. htm • “AI ‘Hallucination’ Again in a Court Order, SC Talks of ‘Institutional Concern,” Indian Express (March 2026) https://indianexpress. com/article/legal-news/aihallucination-again-in-a-court-order-sc-talks-of-institutional-concern-10561833/ • “India’s Top Court Angry After Junior Judge Cites Fake AI-Generated Orders,” BBC News (March 3, 2026) https://www. bbc.
com/news/articles/c178zzw780xo • “AI and Blockchain to Enhance India e-Courts Under Phase III with ₹7,210 Crore Investment,” CIO Elet (February 6, 2025) https://ommcomnews. com/india-news/rs- 7210-crore-project-to-boost-use-of-ai-tech-in-courts-arjun-ram-meghwal/ • “AI Based Portal ‘SUPACE,” Testbook (July 27, 2022)
https://www.drishtiias.com/daily-updates/daily-news-analysis/ai-portal-supace • “AI in the Apex Court: How SUVAS and SUPACE are Shaping India’s Judiciary,” LinkedIn (November 16, 2024) https://www.linkedin.com/pulse/ai-apex-court-howsuvas-supace-shaping-indias-eew7c • “How AI is Transforming Legal Research in Indian Courts,” ApuaLegal (January 9,
2026) https://www.apualegal.com/blog/ai-transforming-legal-research/
“AI for Justice: Ethical, Fair and Robust Adoption in India’s Courts,” UNDP India https://vidhilegalpolicy.in/research/responsible-ai-for-the-indian-justice-system-astrategy-paper/ • “Responsible AI for the Indian Judicial System: A Strategy Paper,” Vidhi Centre for Legal Policy (April 2021) https://vidhilegalpolicy.in/wpcontent/uploads/2021/04/Responsible-AI-for-the-Indian-Judicial-System-A-Strategy- Paper.pdf