From Courtrooms to Cloudrooms: The Evolution of Consumer Dispute Resolution in the Algorithmic Age – A Comparative Analysis with Special Reference to India

Introduction: the death of distance and the jurisdictional vacuum

In the contemporary digital economy, the nature of consumer grievances has changed significantly with the rapid digitisation of global commerce, rendering traditional, “analogue” litigation increasingly outdated. The “death of distance” has created a jurisdictional vacuum for consumer disputes in the digital age.¹ Consider a single transaction that involves a consumer in Mumbai, a website based in Delaware, and a manufacturer in Shenzhen. Multiple jurisdictions are implicated, and when a dispute arises, the threshold difficulty lies in locating the competent forum. For this modern problem, a modern solution, namely ODR, has been developed.

ODR refers to the resolution of disputes on digital platforms, outside the traditional court system. It reshapes the operation of justice by allowing technology to structure conversations, filter issues, and suggest solutions through algorithms. The shift is not merely a technical upgrade; it is a change in the fundamental philosophy of justice.²

A. Statement of the research problem

Traditional court systems, with their physical presence and high costs, are structurally ill-equipped and disproportionately burdensome for small-value digital claims.³ Courts are slow, local, and too expensive for minor online transactions. This “analogue” approach to “digital” problems has produced systemic inefficiencies, judicial lethargy, and mounting backlogs, forcing consumers to forfeit their rights because seeking traditional legal redress is economically irrational. This has necessitated the rise of Online Dispute Resolution, where technology acts not merely as a medium but as an active “Fourth Party” in the resolution process.⁴

B. Existing gap in the literature

In the existing academic discourse, there remains a notable absence of analysis on “native” ODR systems. The literature also lacks a holistic, multi-jurisdictional perspective that connects the rights-based, human-centric approach of the European Union, the market-oriented model of the United States, and India’s rapidly evolving digital public grievance redressal system. Most importantly, current scholarship does not sufficiently assess the legal incorporation of innovative decentralised solutions, particularly blockchain-based smart contracts, self-executing justice, and digital forensic technologies, within the statutory frameworks of developing economies.

C. Significance of the study

As the global marketplace thrives on the speed of light, the justice system cannot remain tethered to the speed of paper. This study demonstrates how ODR can practically democratise access to justice for a billion-user market such as India, for which it must move beyond simple video conferencing toward a decentralised, blockchain-backed architecture that prioritises transparency and immutability. By illustrating that ODR can reduce hearing expenses by an estimated 60 to 70 per cent and mitigate the substantial national wage loss caused by physical court attendance, this research offers a scalable blueprint to decongest overburdened judiciaries. It provides a future-proof legal framework that directly addresses modern algorithmic harms.

D. Outline of the manuscript

The manuscript first establishes the operational matrix of the modern e-commerce ecosystem and the technological architecture of native ODR platforms. It then balances the merits of convenience and asynchronicity against the technical challenges of algorithmic bias, cybersecurity threats, and the digital divide. Next, it explores the blockchain revolution, examining how self-executing smart contracts and digital forensics introduce empirical accountability under modern statutory mandates such as the Bharatiya Sakshya Adhiniyam, 2023 and the Bharatiya Nagarik Suraksha Sanhita, 2023. The paper then conducts a global comparative analysis juxtaposing the divergent regulatory philosophies of the European Union and the United States with India’s unique hybrid model. Finally, it contextualises India’s digital architecture, including flagship portals such as e-Jagriti and the Supreme Court’s draft Regulations for Use of Artificial Intelligence in Courts, 2026, before concluding with targeted recommendations for legislative reform across the Consumer Protection Act, 2019 and the Mediation Act, 2023.

The modern consumer ecosystem and emerging solution mechanisms in the algorithmic age

With the advent of technology, traditional markets have been absorbed into the virtual marketplace. With the rapid expansion of e-commerce, consumer transactions have become increasingly virtual, anonymous, and multi-layered. This has introduced complexities such as information asymmetry, cross-border jurisdictional ambiguity, privacy and data security concerns, and difficulty in identifying liable parties.

The opacity of online transactions and the global dispersion of stakeholders significantly complicate enforcement and accountability.⁵ Moreover, generative AI and personalised algorithms have introduced new forms of consumer harm, including manipulative advertising and behavioural targeting.⁶

To address such issues, redressal mechanisms must evolve from paper service to cloud service. Beyond conventional ADR mechanisms, video conferencing and native ODR, drawing on advanced automated systems, AI-driven negotiation, predictive analytics tools, digital evidence, and blockchain methodologies, have advanced on the digital frontier.

The Online Dispute Resolution system: technological architecture, imperative, merits, and demerits

A. Technological architecture

ODR has turned conflict resolution into a digital process where negotiation, mediation, and arbitration take place online through advanced digital platforms. There is also “native ODR,” which dispenses with the traditional courtroom entirely. It uses smart tools⁷ that rely on AI to settle disputes without face-to-face interaction. For instance, AI-driven negotiation tools such as Smartsettle ONE do not merely process offers; they learn party priorities, using algorithms and “blind bidding”⁸ so that the first reasonable compromise is prioritised. On the analytical side, platforms such as Lex Machina mine prior cases to identify patterns and generate statistics.

In short, modern ODR platforms integrate multiple technologies: AI-driven case management for predictive analysis; chatbots for initial dispute handling; video conferencing for hearings; and blockchain and smart contracts for enforcement.

B. The imperative for ODR with special reference to India

India faces significant judicial backlog and procedural inefficiencies, making ODR a necessity.⁹ The COVID-19 pandemic and the rapid expansion of digital payments have accelerated the need for ODR mechanisms to decongest courts and provide efficient dispute resolution pathways.¹⁰ This necessity is further driven by the sheer volume and speed of e-commerce. India’s internet penetration has surged from around 4 per cent in 2007 to nearly 70 per cent by 2026.¹¹ However, this growth is shadowed by systemic inefficiencies: judicial lethargy, verbose procedural formalism, and an enormous backlog of cases.

C. Merits of the ODR framework

Pecuniary proportionality and wage loss. Traditional litigation is often economically irrational for consumers.¹² In India, the average annual loss of wages and business due to attending court hearings is substantial.¹³ When a dispute involves a small e-commerce refund, the cost of a lawyer and physical travel renders the “right to redressal” a hollow promise.¹⁴ ODR reduces these barriers, lowering hearing expenses by an estimated 60 to 70 per cent.¹⁵

Convenience and asynchronicity. ODR eliminates scheduling conflicts and instead uses email and online forums to enable parties to prepare, review, and execute agreements with ease and at their own pace.¹⁶ This asynchronous structure enhances accessibility while reducing procedural delays and logistical burdens.¹⁷ By allowing participants from different time zones to take part without being online simultaneously, ODR reduces participation costs for consumers and small businesses, and for people who live in remote or under-served areas. Asynchronous tools allow parties to collect evidence, consult experts, and carefully frame their submissions, leading to improved quality of pleadings and fairer resolution. Additionally, ODR relieves pressure on dispute resolution professionals, enabling them to manage caseloads and provide reasoned decisions. Finally, ODR permits recording and audit-trail processes, increasing transparency and easing subsequent review and enforcement.

Informed decision-making. Algorithms can now analyse the merits of a case and predict a party’s likelihood of success before a dispute is even initiated.¹⁸ Predictive models encourage optimal decision-making by assisting users in deciding whether to proceed with a claim, settle, or seek mediation, thereby mitigating wasted time and cost. By surfacing relevant case law, legislation, and likely outcomes, ODR allows the user to form more realistic expectations and bargaining positions.

D. Demerits and technical challenges

The digital divide. There is a risk that ODR remains inaccessible to those without digital literacy or high-speed internet, potentially creating an “inequality of access.”¹⁹ Users from rural backgrounds, the elderly, and less affluent customers may be alienated. Unreliable connectivity can also disrupt the process or cause missed deadlines to their disadvantage.

Algorithmic bias. Algorithms reflect the users and data for which they were created. When models trained on biased data or reflecting historically unfair decision-making are integrated into systems designed to make automated suggestions, they may continue to disadvantage certain communities. Algorithms can be coded to maximise gain at the expense of equity.²⁰ Decisions made by AI mediators may lack transparency, necessitating a legally mandated “right to an explanation,” without which consumers may feel they are victims of a “faceless” judgment.²¹

Cybersecurity threats. India is among the most targeted nations for cyber-attacks.²² It reportedly faces numerous cyber threats every second, necessitating a robust cybersecurity regime within ODR platforms.²³ Compromised platforms could leak sensitive financial and personal information, strip confidentiality from settlement negotiations, and empower actors to tamper with evidence. Common attack vectors range from phishing campaigns and account takeovers to the exploitation of vulnerable or poorly documented APIs and reliance on third-party plugins.

Effectiveness of ODR

Through an architectural shift leveraging multilingual interfaces and deep mobile integration, ODR has democratised consumer redressal, effectively bypassing the historical barriers of geographical distance and prohibitive litigation costs.²⁴ However, its enforceability remains a challenge. Because a substantial cross-section of ODR outcomes relies primarily on voluntary compliance, the finality of these resolutions remains fragile, punctuated by an inherent power asymmetry between corporate entities and individual consumers.²⁵

Unlike court orders, ODR outcomes often lack binding force unless formally recognised by judicial bodies.²⁶ In the Indian context, this creates a distinct regulatory dichotomy. While an ODR outcome structured as an online arbitral award or a conciliated settlement enjoys formal legal recognition under the Arbitration and Conciliation Act, 1996, which deems such outcomes enforceable as decrees of a civil court, pure private ODR negotiations and algorithmic mediations frequently operate within a regulatory grey area.²⁷ Without explicit legislative codification within consumer protection law, these digital settlements are often treated merely as basic contractual obligations rather than executable titles. Consequently, if a non-compliant e-commerce platform defaults on an ODR settlement, the consumer is forced back into the traditional judicial loop to seek enforcement.

The blockchain revolution: toward smart contract mediation and self-executing justice

The anomalies in conventional dispute resolution often originate from excessive human intervention and the requirement of physical presence.²⁸ Integrating smart contracts within a blockchain-based ODR framework can bypass these bottlenecks and holds potential for improving access to justice.²⁹ Blockchain enables secure, immutable record-keeping.³⁰ Smart contracts facilitate automated dispute resolution.³¹ Decentralised platforms such as Kleros demonstrate blockchain-based adjudication.³² The following are the principal benefits of the blockchain approach.

A. The security of the immutable ledger

Blockchain technology offers an open, distributed, and tamper-proof ledger that guarantees secure and auditable transactional integrity.³³ In a consumer dispute, a blockchain record ensures that the transaction history and communication logs cannot be modified by either the platform or the consumer.³⁴ This ensures that the “genesis of the dispute” is preserved in its original form, promoting a culture of trust and procedural stability.³⁵

B. Smart contracts as mediators

By utilising autonomous smart contracts, blockchain-based ODR supports self-enforcing agreements.³⁶ For instance, a smart contract can automatically trigger a refund if a delivery is not acknowledged within a pre-defined window, reducing human interference and pre-emptively avoiding disputes.³⁷

C. Participatory design and gamification

The proposed model suggests a “participatory design” with a focus on end-user involvement.³⁸ A justice-oriented framework can be gamified, with the platform rewarding parties who settle disputes amicably and swiftly.³⁹ This encourages a culture of reconciliation over adversarial litigation. Platforms such as Kleros and the Aragon Network demonstrate that decentralised arbitration, in which crowdsourced jurors use blockchain to vote, can settle disputes equitably without the need for conventional courts and intermediaries.⁴⁰

Digital forensics: the scientific backbone of evidence

As e-commerce moves away from face-to-face trust toward virtual interactions, the identification of parties and the verification of claims become difficult. This is where digital forensics becomes indispensable. It provides reliable electronic evidence such as metadata and IP logs.⁴¹ It engages with the data trails that identify liabilities. By extracting and collecting these immutable electronic records, forensic techniques introduce an empirical layer of accountability to the virtual market, building a quantitative foundation of responsibility into it. This framework adheres to principles of objectivity and addresses the issue of trust in transnational digital trade by offering ODR settings a scientifically measurable basis upon which to allocate responsibility.

A. Moving beyond testimonial evidence

The classic investigative approach relies on eyewitness accounts and physical documentation. Traditional consumer forums, too, often decide cases on affidavits and oral testimony. Such testimonial and conventional evidence is highly susceptible to fabrication. In the digital realm, digital forensics deals with data in the cyber domain that can conclusively point to potential offenders. Evidence in the e-commerce and virtual market is difficult to forge; owing to encryption and real-time recording, fabrication is nearly impossible.

B. Admissibility under the Bharatiya Sakshya Adhiniyam, 2023

Under Section 39 of the Bharatiya Sakshya Adhiniyam, 2023, corresponding to Section 45 of the Indian Evidence Act, 1872, expert opinions on science and technology are admissible and often decisive in complex disputes. In Selvi v. State of Karnataka, the Supreme Court recognised the role of advanced scientific techniques in investigation while emphasising procedural safeguards.⁴² In consumer litigation, digital forensic evidence such as metadata, IP logs, and blockchain hashes is far more reliable than testimonial evidence, which can be easily fabricated.⁴³

This statutory framework is further strengthened by Section 61 of the Bharatiya Sakshya Adhiniyam, 2023, which provides that an electronic or digital record cannot be denied admissibility solely because it is in electronic form.⁴⁴ In establishing the procedural integrity of such data, Section 63 of the Act replaces the erstwhile Section 65B of the Indian Evidence Act, 1872, reinforcing strict parameters for secondary electronic records through mandatory certification protocols to guarantee that the information was regularly processed and stored in the ordinary course of digital business.⁴⁵ Furthermore, by legally validating distributed networks and cloud infrastructure, the legislature has provided ODR platforms with the statutory basis to recognise complex algorithmic trails as pillars of proof.⁴⁶

As noted in New India Assurance Co. Ltd. v. Sree Sree Madan Mohan Rice Mill, expert opinions may be sought on the evidence obtained in consumer litigation.⁴⁷ The regime should move toward one in which digital forensic reports are given decisive weight in cases of algorithmic fraud, where human witnesses cannot reasonably be expected to understand the underlying code.

C. The chain of custody

India requires specialised cyber cells equipped to handle digital evidence in consumer disputes. The procedure for search and seizure of digital or electronic devices must be strictly followed to establish an authentic chain of custody before the adjudicatory bodies, including consumer forums.⁴⁸

This requirement is now a statutory directive under Section 193(3) of the Bharatiya Nagarik Suraksha Sanhita, 2023, which mandates that a police report formally include the sequence of custody whenever an electronic device is involved in an investigation.⁴⁹ Section 105 of the Sanhita further requires that the entire process of conducting a search and taking possession of any electronic device be mandatorily recorded through audio-video electronic means.⁵⁰ Consequently, strict adherence to these recording protocols is essential to ensure that electronic records remain judicially viable and immune to allegations of retroactive fabrication before a consumer commission.⁵¹

Multi-jurisdictional study

Table 1 sets out a comparative framework of consumer ODR regimes across the principal jurisdictions examined in this study.

Table 2 presents a comparative study of the features and application modes of the different ODR regimes.

Global comparative analysis: divergent regulatory philosophies

A. The European Union: the rights-based model

The European Union adopts a rights-based framework that prioritises data sovereignty and human-centric AI. The Union is stringent in ensuring consumer welfare through the General Data Protection Regulation (GDPR) and the Unfair Commercial Practices Directive (UCPD), emphasising data privacy, transparency, and accountability.⁵² Under the UCPD, any material distortion of the economic behaviour of consumers through algorithmic means is prohibited, and the GDPR requires that any processing of personal data be lawful and fair.⁵³ The landmark Google Spain SL v. Agencia Española de Protección de Datos decision established the “right to be forgotten,” emphasising that digital memory is not limitless and ensuring that digital history does not permanently prejudice a consumer.⁵⁴ Emerging frameworks such as the proposed AI Liability Directive and the EU AI Act further aim to regulate AI systems according to risk levels.⁵⁵

B. The United States: the market-led enforcement model

The US Federal Trade Commission (FTC) focuses on preventing “unfair or deceptive acts or practices” rather than heavy prescriptive regulation.⁵⁶ For example, in the matter of Fashion Nova, LLC, the FTC took action against the company for suppressing negative customer reviews of its products.⁵⁷ The US model places a relatively higher burden on the consumer to demonstrate substantial injury.⁵⁸ The United States remains reluctant to over-regulate dynamic pricing models for fear of stifling innovation. While the California Consumer Privacy Act (CCPA) offers some protection, the threshold for establishing actionable injury remains comparatively high.⁵⁹ Private-sector ODR, such as eBay’s resolution system, which has handled millions of cases, remains the primary efficiency driver.⁶⁰

The United States follows a fragmented regulatory model with federal and state-level consumer protection laws. While flexible, this approach struggles to address emerging AI-related risks such as algorithmic bias and automated decision-making.⁶¹ The prevailing philosophy is to let the market operate and to intervene only after a company commits a clear, deceptive act, relying heavily on private companies to build their own internal dispute platforms.

C. India: the hybrid model

India is at a transformative juncture. The Consumer Protection Act, 2019 explicitly recognises online transactions and establishes the Central Consumer Protection Authority to address, among other things, class actions.⁶² Other rules and regulations facilitate the ODR regime in India, including the Consumer Protection (E-Commerce) Rules, 2020⁶³ and the Digital Personal Data Protection Act, 2023.⁶⁴ Flagship portals such as e-Daakhil⁶⁵ and the AI-powered e-Jagriti,⁶⁶ which is reported to have disposed of over 1.27 lakh cases in 2025, demonstrate India’s capacity to use technology to address its staggering judicial pendency.⁶⁷

To understand India’s hybrid model, one may imagine a system borrowing the consumer-first protections of the European Union while adopting the practical, technology-driven efficiencies of the United States. Instead of leaving ODR entirely to private technology corporations, the Indian government actively builds state-backed digital portals to resolve complaints. This approach allows India to respect consumer data privacy while deploying AI within consumer commissions to clear pendency.

The Indian context: scaling for a billion

India’s legal ecosystem provides both explicit and implicit support for ODR mechanisms. From the Consumer Protection Act, 2019⁶⁸ to e-Jagriti, India’s digital redressal architecture has transitioned from a traditional consumer protection regime to a technology-integrated framework designed for the internet age.⁶⁹ Surveys suggest that a substantial majority of Indian participants now prefer out-of-court settlements over traditional litigation.⁷⁰

A. Legal framework

The Information Technology Act, 2000 grants legal recognition to e-contracts and digital signatures, ensuring the enforceability of online agreements.⁷¹ The Arbitration and Conciliation Act, 1996 permits arbitration in electronic form, while Section 89 of the Code of Civil Procedure, 1908 promotes ADR mechanisms that can be extended into the digital domain.⁷²

Further, the Consumer Protection Act, 2019 replaced the earlier 1986 Act, specifically introducing provisions for the digital age.⁷³ It expanded the definition of a “consumer” to include online transactions⁷⁴ and multi-level marketing. The Consumer Protection (E-Commerce) Rules, 2020 require every e-commerce entity to establish a proper grievance redressal mechanism, appoint a grievance officer, acknowledge complaints within forty-eight hours, and resolve them within a prescribed period.⁷⁵ This is supported by the Digital Personal Data Protection Act, 2023, which introduces the concept of “data fiduciaries” and significant penalties for non-compliance.⁷⁶ The Central Consumer Protection Authority (CCPA), established as a proactive regulator, has the power to recall dangerous goods, order refunds, and penalise misleading advertisements.⁷⁷

B. e-Daakhil and e-Jagriti: portals for justice

India has launched flagship digital initiatives against a backdrop of severe judicial pendency.⁷⁸ e-Daakhil is a unified portal that allows consumers to file complaints online from anywhere in India at any time. It facilitates digital payment of fees and the uploading of documents, removing the need for physical presence.⁷⁹ e-Jagriti, an AI-powered multilingual interface, has reportedly facilitated over 1.3 lakh case filings and 1.27 lakh disposals as of late 2025.⁸⁰ It provides real-time tracking via SMS and email alerts, ensuring that users, including non-resident Indians, do not miss deadlines. The e-Jagriti platform was awarded a Silver Award at the National Awards for e-Governance under the Government Process Re-engineering category.⁸¹ Following its integration, which consolidated older legacy applications such as e-Daakhil and CONFONET into a single paperless architecture, the reported national consumer case disposal rate rose significantly.⁸²

C. The Supreme Court’s draft Regulations for Use of Artificial Intelligence in Courts, 2026

To complement rapid digital transitions, the AI Committee of the Supreme Court of India released the draft Regulations for Use of Artificial Intelligence in Courts, 2026.⁸³ This regulatory framework is stated to apply to all courts, tribunals, and statutory commissions performing adjudicatory functions across Indian territory.⁸⁴ The core philosophy of these regulations rests on the principle of “human primacy,” dictating that AI tools must remain strictly subservient to human judgment and can never supplant independent judicial authority.⁸⁵ Consequently, while the framework permits AI deployment for administrative optimisation, legal research, translation, and case management, it prohibits algorithms from making actual adjudicatory decisions, determining outcomes, or engaging in predictive risk-scoring.⁸⁶

Regulation 43 introduces a mandatory disclosure protocol, requiring lawyers and litigants to execute a formal certificate whenever AI tools are used to prepare pleadings, submissions, or evidence.⁸⁷ Under these guidelines, the legal professional remains fully accountable for the accuracy of the filing; if an algorithm hallucinates a fictitious precedent or fabricates facts, the human signatory cannot invoke the machine to escape liability for professional misconduct.⁸⁸ By creating a permanent apex body at the Supreme Court level to audit and approve judicial technology, this development seeks to ensure that as India transitions toward automated ODR systems, core constitutional principles of due process, transparency, and explainability are preserved.⁸⁹

Government and private ODR infrastructure

A. Government ODR infrastructure

National Internet Exchange of India (NIXI) domain dispute settlement mechanism. NIXI adopted the .IN Domain Name Dispute Resolution Policy (INDRP), which establishes the rules and guidelines for settling disputes involving the registration and use of a .in internet domain name. Online complaint filing is permitted, and an arbitrator decides the conflict on the basis of written submissions. The procedure has dispensed with in-person hearings for the resolution of such disputes.⁹⁰

National Consumer Helpline (NCH) and the INGRAM portal. These have significantly increased accessibility, with complaints rising markedly over recent years.⁹¹

Online Conciliation and Mediation Centre (OCMC). To make online mediation the preferred method for settling consumer disputes, the Ministry of Consumer Affairs established the OCMC at the National Law School of India University in 2016.⁹²

Mediation cells. Under Section 74 of the Consumer Protection Act, 2019, consumer mediation cells facilitate conciliation with enforceable outcomes.⁹³ In 2023, the Department of Consumer Affairs undertook an initiative to design, develop, and implement an online dispute resolution platform for consumer mediation.⁹⁴

RBI ODR system. The Reserve Bank of India’s ODR system for digital payments mandates automated dispute resolution for failed transactions.⁹⁵

B. Private-sector participation

Private ODR platforms and corporate grievance systems play a complementary role. Companies operate internal ODR systems via chatbots and return portals. A study reports that a major private-sector bank uses a technology partner’s system to resolve large volumes of customer disputes.⁹⁶ Legal-technology start-ups such as Presolv360 and CADRE are emerging as key players.⁹⁷ SAMA and CADRE have gained momentum in India, particularly since the COVID-19 pandemic, for resolving commercial and landlord-tenant disputes using AI-driven tools.⁹⁸

Landmark Indian case law

The Indian judiciary and consumer fora are increasingly holding digital platforms accountable for deficiencies and unfair practices. A few illustrative matters are noted below.

E-commerce marketplace liability. In consumer proceedings against major e-commerce marketplaces, adjudicatory fora have examined the liability of platforms for allegedly fake products and misleading discounts offered by third-party sellers, and have emphasised pricing transparency.⁹⁹

Surge pricing and algorithmic pricing. In Samir Agrawal v. Competition Commission of India, the Supreme Court examined allegations of anti-competitive conduct arising from the surge-pricing algorithms of app-based cab aggregators; the Court upheld the findings of the Competition Commission and the National Company Law Appellate Tribunal, declining to find cartelisation, while the broader question of algorithmic pricing transparency continues to attract regulatory scrutiny.¹⁰⁰

Data protection and fraud. In Dabur India Ltd. v. Ashok Kumar, the Delhi High Court observed that the Digital Personal Data Protection Act, 2023 is an enabling framework that preserves privacy without shielding fraudulent conduct in the digital ecosystem.¹⁰¹

Ed-tech refunds. In a consumer matter against an ed-tech platform, the District Consumer Disputes Redressal Commission, Baramulla directed the refund of fees for services not rendered, affirming that retention of fees without corresponding access constitutes an unfair trade practice.¹⁰²

Critical issues in e-commerce litigation: the algorithmic black box, the digital divide, and ethical concerns

Algorithmic bias. Algorithms can be coded to maximise gain at the expense of equity, requiring a legally mandated right to an explanation. This systemic opacity leaves consumers unable to scrutinise whether an automated denial of a refund or claim was driven by discriminatory variables. Without a structured mechanism to demystify these computational choices, the standard of proof becomes an almost insurmountable hurdle for the aggrieved.

Dynamic and personalised pricing. Using AI to predict consumer behaviour allows businesses to practise targeted advertising and dynamic pricing. Personalised pricing based on an individual’s affluence is much harder to justify legally and may attract liability under unfair trade practice laws. This practice covertly extracts the maximum possible price from a consumer by exploiting real-time location history and purchasing urgency.

Dark patterns. These are manipulative interfaces and opaque processes that nudge consumers into unwanted decisions without their full awareness. The rise of AI-driven personalisation has intensified the use of dark patterns, in which algorithmically curated interfaces exploit consumer vulnerabilities, increase information asymmetry, and subtly manipulate decision-making.¹⁰³ This deliberate distortion of digital choice architecture directly compromises the legal requirement of free consent under contract law.

The digital divide. While internet penetration is growing, there is a risk that ODR remains inaccessible to those without digital literacy. This divide is particularly pronounced in rural and underdeveloped regions where access to digital infrastructure, low-bandwidth systems, and technological awareness remains limited, restricting equitable access to justice.¹⁰⁴

Intermediary liability. The increasing reliance on AI-driven platforms has blurred traditional liability frameworks, making it difficult to attribute responsibility between platform operators, third-party sellers, and the algorithmic systems that influence consumer outcomes.¹⁰⁵ E-commerce safe-harbour protections historically shielded intermediaries who acted merely as passive conduits for third-party inventory. However, because modern platforms actively curate, price, and promote products using proprietary algorithms, their safe-harbour immunities warrant reassessment to ensure direct accountability.

Data privacy and security. The exponential growth of e-commerce has led to extensive collection and processing of consumer data, raising serious concerns about privacy and data misuse. Consumers often lack control over how their personal data is used, leading to risks such as identity theft, fraud, and unauthorised profiling.¹⁰⁶ The concentration of data within a few digital platforms exacerbates concerns of market-power abuse, anti-competitive practices, and reduced consumer choice.¹⁰⁷ This data asymmetry leaves individuals vulnerable to continuous behavioural surveillance.

Misleading advertisements and algorithmic manipulation. AI-powered advertising systems increasingly enable hyper-personalised marketing strategies that may mislead consumers by exploiting behavioural data. Such targeted advertising amplifies deceptive practices and raises concerns regarding transparency and ethical data usage.¹⁰⁸ By deploying deep psychological profiling, these automated systems can identify and target specific consumer vulnerabilities.

Recommendations for legislative reform

To institutionalise the vision of an advanced, technology-friendly jurisprudence, the following reforms are proposed.

Amend the Commercial Courts Act, 2015. Section 12A should be modified to specifically legitimise ODR and smart-contract-based blockchain mediation for pre-institution settlement. This change would ensure that parties do not view online mediation as an optional, informal exchange, but as a mandatory prerequisite before filing a commercial suit.

Amend the Consumer Protection Act, 2019. The Act should broaden the definition of mediation to include “e-mediation” by express mention, and should acknowledge mediation by electronic means as legally enforceable. The Act already reflects a shift toward digital consumer protection by recognising e-filing and proactive regulatory oversight through the Central Consumer Protection Authority, which can investigate unfair trade practices and misleading advertisements in digital markets.¹⁰⁹

Update the Mediation Act, 2023. The Act is currently silent on the concept of a machine as mediator. It should be updated to validate settlements reached via autonomous algorithms and pre-defined code. With increasing reliance on AI-driven dispute resolution tools, regulatory frameworks must address algorithmic bias, transparency, and accountability to ensure fairness in automated decision-making. The scope of the Act should be amended to include provisions facilitating blockchain mediation and establishing its enforceability.

Digital forensic integration. Cyber cells must be equipped with the necessary technology to ensure a proper chain of custody for electronic data presented in consumer forums. A specialised branch of professionals should be created to help consumer forums analyse electronic evidence accurately. Integration of AI-assisted forensic tools can enhance evidence analysis, ensuring authenticity, traceability, and admissibility of digital records in ODR proceedings.

Mandatory algorithmic transparency. E-commerce entities should disclose the logic of the algorithm behind dynamic pricing to prevent unfair trade practices. Drawing inspiration from global practice, particularly the European Union’s emphasis on transparency under data protection regimes, India should mandate explainability of algorithmic decisions affecting consumers.

Dedicated ODR legislation. Instead of forcing digital disputes into laws designed for paper and physical courts, a single, dedicated ODR statute would create a unified rulebook for the entire country. India should enact comprehensive ODR-specific legislation that formally defines ODR processes, prescribes ethical and procedural standards, and ensures the enforceability of digitally mediated settlements.¹¹⁰

Strengthening awareness and accessibility. Government-led initiatives such as multilingual outreach programmes, integration with digital platforms, and the establishment of ODR kiosks in rural areas can bridge the digital divide and enhance accessibility.¹¹¹ Through these measures, the state can demystify the technology among the rural population.

Institutional integration with the judiciary. Court-annexed ODR platforms and the mandatory referral of small-value disputes to online mediation can reduce judicial backlog and institutionalise ODR within the formal justice delivery system.

Conclusion

Navigating a technologically advanced digital ecosystem, one may observe that modern complexities require modern solutions. The transition from courtrooms to “cloudrooms,” and from ADR mechanisms to ODR and blockchain-based redressal, is not merely a technical upgrade but a fundamental shift in the locus of trust and the philosophy of justice.

By formalising blockchain-based ODR and digital forensics, the legal system can break free from the constraints of physical necessity and ensure that justice is not merely a physical location but a seamless service. ODR platforms, through tools such as AI-driven case management, chatbots, and virtual hearings, have demonstrated their ability to deliver cost-effective, time-efficient, and accessible dispute resolution, particularly for low-value, high-volume disputes. These tools enable faster, data-driven resolution, but also raise concerns regarding transparency and accountability.

In the Indian context, much is already underway, yet a concerted effort from stakeholders is required to ensure that technology does not exacerbate existing inequalities. By institutionalising digital forensics and blockchain mediation, India can move from a state of judicial pendency toward a position of leadership in digital redressal, ensuring that justice is not merely a physical place but a digital right. To ensure a truly equitable global marketplace, regulators must harmonise standards that balance the efficiency of the United States, the rights-based approach of the European Union, and India’s innovative scalability. Regulatory frameworks must evolve simultaneously to address risks related to algorithmic bias, data privacy, and cross-border enforcement. The goal is a future-proof legal framework in which technology facilitates, rather than dictates, the resolution of human conflicts.

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Footnotes

1. Frances Cairncross, The Death of Distance 1–5 (Harv. Bus. Sch. Press 2001).

2. Amitabh Kant, CEO, NITI Aayog, Keynote Address at the Webinar, Online Dispute Resolution: Opportunities and Challenges (June 27, 2020).

3. Richard Susskind, Online Courts and the Future of Justice 34–36 (Oxford Univ. Press 2019).

4. Ethan Katsh & Janet Rifkin, Online Dispute Resolution 93–95 (Jossey-Bass 2001).

5. See, e.g., Christopher Hodges, Law and Corporate Behaviour: Integrating Theories of Regulation, Enforcement, Compliance and Ethics (Hart Publ’g 2015).

6. See, e.g., Shoshana Zuboff, The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power (PublicAffairs 2019).

7. U.N. Comm’n on Int’l Trade Law, Technical Notes on Online Dispute Resolution (2017).

8. Colin Rule, Online Dispute Resolution for Business 45–47 (Jossey-Bass 2002).

9. NITI Aayog, Designing the Future of Dispute Resolution: The ODR Policy Plan for India 5–10 (2021); DAKSH, State of the Indian Judiciary (2016).

10. Narendra Kumar, Online Dispute Resolution (ODR) in E-Commerce: Effectiveness and Challenges, Vintage Legal (last visited Apr. 11, 2026).

11. DataReportal, Digital 2026: India (2026).

12. NITI Aayog, supra note 9, at 5–6.

13. Cf. DAKSH, State of the Indian Judiciary: A Report by DAKSH 32–35 (2016).

14. Vidhi Ctr. for Legal Pol’y, Strengthening Consumer Dispute Resolution in India (2018).

15. NITI Aayog, supra note 9, at 8–9.

16. U.N. Comm’n on Int’l Trade Law, supra note 7, at 30–35.

17. Ethan Katsh & Orna Rabinovich-Einy, Digital Justice: Technology and the Internet of Disputes 64–68 (2017).

18. Richard Susskind, supra note 3, at 102–05; Kevin D. Ashley, Artificial Intelligence and Legal Analytics 211–18 (2017).

19. NITI Aayog, supra note 9, at 23–25.

20. Cathy O’Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy 21–25 (2016).

21. Regulation 2016/679, General Data Protection Regulation, art. 22, 2016 O.J. (L 119) 1 (EU).

22. IBM Security, Cost of a Data Breach Report (2023).

23. NortonLifeLock, Cyber Safety Insights Report (2023).

24. Chih-Chung Kao, Online Consumer Dispute Resolution and the ODR Practice in Taiwan: A Comparative Analysis, 5 Asian Soc. Sci. 113 (2009).

25. Wannes Vandenbussche & Piet Taelman, Consumer Protection Proceedings, SSRN Electronic Journal (2024).

26. Kumar, supra note 10.

27. NITI Aayog, supra note 9.

28. Katsh & Rabinovich-Einy, supra note 17, at 33–36.

29. World Bank, World Development Report 2016: Digital Dividends 140–42 (2016).

30. Satoshi Nakamoto, Bitcoin: A Peer-to-Peer Electronic Cash System 2–4 (2008).

31. Nick Szabo, Smart Contracts: Building Blocks for Digital Markets, 16 Extropy 18, 18–20 (1996); Primavera De Filippi & Aaron Wright, Blockchain and the Law (2018).

32. Federico Ast, Kleros: Short Paper v1.0 1–5 (2018).

33. Nakamoto, supra note 30.

34. Arvind Narayanan et al., Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction 45–47 (2016).

35. World Econ. Forum, Realizing the Potential of Blockchain 6–8 (2017).

36. Szabo, supra note 31.

37. Kevin Werbach & Nicolas Cornell, Contracts Ex Machina, 67 Duke L.J. 313, 331–35 (2017).

38. Henry Sanoff, Community Participation Methods in Design and Planning 10–14 (2000).

39. Kevin Werbach, The Blockchain and the New Architecture of Trust 152–55 (2018).

40. Ast, supra note 32, at 1–6; Aragon Ass’n, Aragon Whitepaper (2017).

41. Eoghan Casey, Digital Evidence and Computer Crime (3d ed. 2011); Israel D. Fianyi, Curbing Cyber-Crime and Enhancing E-Commerce Security with Digital Forensics, 12 Int’l J. Comp. Sci. Issues 78 (2015).

42. Selvi v. State of Karnataka, (2010) 7 SCC 263, 327–30 (India).

43. Stephen Mason & Daniel Seng, Electronic Evidence 58–65 (4th ed. 2017).

44. The Bharatiya Sakshya Adhiniyam, 2023, § 61, No. 47, Acts of Parliament, 2023 (India).

45. See id. § 63(2); see also Shikhar Goel, Paper in the Age of the Digital: The Curious Case of 65-B Certificates in India, 11 Asian J.L. & Soc’y 435 (2024).

46. The Bharatiya Sakshya Adhiniyam, 2023, § 63(3) (India).

47. New India Assurance Co. Ltd. v. Sree Sree Madan Mohan Rice Mill, R.P. No. 2008 of 2012 (NCDRC Feb. 11, 2012) (India).

48. See The Information Technology Act, 2000, §§ 65B, 67C, No. 21 of 2000 (India); see also Anvar P.V. v. P.K. Basheer, (2014) 10 SCC 473, 482–85 (India).

49. The Bharatiya Nagarik Suraksha Sanhita, 2023, § 193(3), No. 46, Acts of Parliament, 2023 (India).

50. Id. § 105.

51. Justice V. Ramkumar, Section 193(3) of the BNSS: Sequence of Custody, LiveLaw (Mar. 15, 2024).

52. Directive 2005/29/EC of the European Parliament and of the Council of 11 May 2005 Concerning Unfair Business-to-Consumer Commercial Practices, 2005 O.J. (L 149) 22; Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 (General Data Protection Regulation), 2016 O.J. (L 119) 1.

53. Directive 2005/29/EC, supra note 52, art. 5; Regulation (EU) 2016/679, supra note 52, arts. 5–6.

54. Case C-131/12, Google Spain SL v. Agencia Española de Protección de Datos, ECLI:EU:C:2014:317, ¶¶ 93–99 (May 13, 2014).

55. Philipp Hacker, The European AI Liability Directives: Critique of a Half-Hearted Approach and Lessons for the Future (2023).

56. Federal Trade Commission Act, 15 U.S.C. § 45(a)(1) (2018).

57. Complaint at 2–5, In re Fashion Nova, LLC, No. C-4759 (F.T.C. Mar. 3, 2022).

58. Joshua D. Wright & Elyse Dorsey, Reassessing the FTC’s Role in Consumer Protection, 72 Geo. Wash. L. Rev. 221, 230–35 (2014).

59. California Consumer Privacy Act of 2018, Cal. Civ. Code §§ 1798.100–1798.199 (West 2023).

60. Rule, supra note 8, at 45–48.

61. Cary Coglianese & David Lehr, Regulating by Robot: Administrative Decision Making in the Machine-Learning Era, 105 Geo. L.J. 1147, 1160–65 (2017).

62. The Consumer Protection Act, 2019, §§ 2(16), 10, No. 35 of 2019 (India).

63. The Consumer Protection (E-Commerce) Rules, 2020, G.S.R. 462(E) (India).

64. The Digital Personal Data Protection Act, 2023, No. 22 of 2023 (India).

65. See Dep’t of Consumer Affairs, Ministry of Consumer Affairs, Food & Pub. Distribution, Gov’t of India, e-Daakhil Portal (launched Sept. 7, 2020).

66. See Dep’t of Consumer Affairs, Ministry of Consumer Affairs, Food & Pub. Distribution, Gov’t of India, e-Jagriti Portal (last updated Nov. 12, 2025).

67. See Press Release, Ministry of Consumer Affairs, Food & Pub. Distribution, Gov’t of India, e-Jagriti Revolutionizes Consumer Justice in 2025 (Nov. 16, 2025); Digital Redressal: Government’s e-Jagriti Portal Resolves Over 1.27 Lakh Cases, Times of India (Nov. 2025).

68. The Consumer Protection Act, 2019, No. 35 of 2019 (India).

69. Siddharth Kapoor & Ananya Singhal, Online Dispute Resolution: Creating a Level-Playing Field in Small-Value Claims, 2.2 IRI Arb. 95 (2022).

70. Id.

71. The Information Technology Act, 2000, §§ 4, 5, 10A, No. 21 of 2000 (India); Kumar, supra note 10.

72. The Arbitration and Conciliation Act, 1996, § 7 (India); The Code of Civil Procedure, 1908, § 89 (India); Kumar, supra note 10.

73. The Consumer Protection Act, 2019, pmbl., No. 35 of 2019 (India).

74. Id. § 2(7).

75. The Consumer Protection (E-Commerce) Rules, 2020, rr. 4(4), 4(5) (India).

76. The Digital Personal Data Protection Act, 2023, §§ 2(13), 33, No. 22 of 2023 (India).

77. The Consumer Protection Act, 2019, §§ 10, 18, 20–21, No. 35 of 2019 (India).

78. National Judicial Data Grid (last visited Apr. 11, 2026).

79. e-Daakhil Portal, supra note 65.

80. Press Release, supra note 67.

81. Press Information Bureau, e-Jagriti Wins Silver Award at National Awards for e-Governance 2026, Ministry of Consumer Affairs, Food & Public Distribution (June 7, 2026).

82. Id.

83. Supreme Court of India, Notice: Seeking Views/Suggestions on Draft Regulations for Use of Artificial Intelligence (AI) in Courts, 2026 (issued June 3, 2026).

84. Id. at ch. I, reg. 2.

85. Id. at ch. II, reg. 4.

86. Id. at ch. III, reg. 20.

87. Id. at ch. IV, reg. 43(3).

88. Id. at ch. IV, reg. 43(6); see also ch. II, reg. 8.

89. Id. at ch. V; see also ch. II, reg. 7.

90. INDRP Rules of Procedure r. 11; Mansi Jain Garga, AI and Mediation: A Threat or Helpful Tool for Mediators—An Indian Perspective, 3.4 J. Com. L. & Just. 175 (2023).

91. National Consumer Helpline (last visited Apr. 11, 2026); Kumar, supra note 10; Dep’t of Consumer Affairs, Ministry of Consumer Affairs, Food & Pub. Distribution, Gov’t of India, Annual Report 2020–2021.

92. Garga, supra note 90.

93. Kumar, supra note 10.

94. Dep’t of Consumer Affairs, Gov’t of India, Invitation for Expression of Interest for Appointment of Agency to Design, Develop, Implement and Manage the Online Dispute Resolution Platform (2026).

95. Kumar, supra note 10.

96. Id.

97. Online Dispute Resolution, The Legal School (last visited Apr. 11, 2026).

98. Krishna Kumar Yadava & Vinay Kumar Yadav, The Impact of Emerging Technologies on Business Laws, 5.4 J. Com. L. & Just. 70 (2025).

99. Ravneet Bansal v. Flipkart Internet Pvt. Ltd., Appeal No. A/205/2023 (State Consumer Disputes Redressal Comm’n, U.T. Chandigarh, Feb. 1, 2024) (India).

100. Samir Agrawal v. Competition Commission of India, (2021) 3 SCC 136 (India).

101. Dabur India Ltd. v. Ashok Kumar, 2025 SCC OnLine Del (Del. H.C.) (India).

102. Irshad Rashid Dand v. Physics Wallah Pvt. Ltd., Consumer Complaint No. 46/2025 (Dist. Consumer Disputes Redressal Comm’n, Baramulla (J&K), Mar. 17, 2026) (India).

103. N. Jain & A. Jain, AI-Based Content Creation and Product Recommendation Applications in E-Commerce: An Ethical Overview (2025).

104. Kumar, supra note 10; World Bank, supra note 29, at 88–92.

105. V.S. & N.D.N., Legal Challenges of Artificial Intelligence in India’s Cyber Law Framework (2024).

106. Elizabeth Atieno Otieno, Data Protection and Privacy in E-Commerce Environment: Systematic Review, 22(1) GSC Advanced Rsch. & Revs. 238 (2025).

107. Ritesh Kumar Singhal et al., AI-Powered Personalization in E-Commerce: Consumer Perceptions, Trust, and Purchase Decision-Making, Advances in Consumer Research 3779 (2025).

108. Raji et al., E-Commerce and Consumer Behavior: A Review of AI-Powered Personalization and Market Trends, 18(3) GSC Advanced Rsch. & Revs. 66 (2024).

109. Hariom Gupta & Amit Singh, The Consumer Protection Act, 2019: A Comparative Analysis of Legislative Frameworks in India and Other Jurisdictions, 4 Int’l J. Crim., Common & Statutory L. 155 (2024).

110. Kumar, supra note 10.

111. Id.