INTRODUCTION
Online reviews now serve as a substitute for traditional word-of-mouth trust. Since buyers can’t examine goods or services beforehand, they rely on feedback from other customers.[1] Generative artificial intelligence has changed the nature of what constitutes a ‘fake review’. It is no longer simply a paid or forced human endorsement. It can now be generated by machines at scale, using language that sounds like authentic customer experiences.[2] This creates a genuine issue for Indian law. Consumer protection law presumes a human offender, while cyber law finds it difficult to determine responsibility, whether it lies with the seller, the platform, or the company that developed the review-writing tool.[3] This piece examines whether Indian consumer and cyber laws adequately address AI-generated fake reviews and identifies regulatory gaps.
UNDERSTANDING AI-GENERATED FAKE REVIEWS
An AI-generated fake review is a fabricated endorsement created by a large language model or automated software, designed to mimic a real customer’s experience even though no purchase took place.[4] The U.S. Federal Trade Commission has recognised the role of generative AI in creating fraudulent reviews. In collaboration with the Department of Consumer Affairs, the Bureau of Indian Standards launched IS 19000:2022, India’s first standard outlining how online reviews should be gathered, managed, and shared.[5] It was written with traditional, paid reviews in mind, not AI-generated ones. Still, its emphasis on verifying reviewers and holding moderators responsible positions it as India’s nearest equivalent to a regulatory solution for AI-generated reviews.
LEGAL FRAMEWORK IN INDIA
There is no Indian law that directly addresses AI-generated reviews. What exists must be assembled from consumer protection and information technology statutes.[6] The Consumer Protection Act 2019 defines ‘unfair trade practice’ under section 2(47), which includes false or misleading representations concerning goods or services. The Act also defines ‘misleading advertisement’ under section 2(28), encompassing any unfair method employed to promote a sale, such as false statements. The Central Consumer Protection Authority (CCPA), established under Section 10, has the power to take action against unfair trade practices and misleading advertisements as outlined in Section 18.[7] Exercising that authority, the CCPA released the Guidelines for Preventing Misleading Advertising and Endorsements in 2022. Clause 13(1) requires that an endorsement express the endorser’s true and up-to-date opinion, grounded in experience with the product or service. [8] The Consumer Protection (E-Commerce) Rules 2020 extend further and address review manipulation directly. Rule 4 mandates that all e-commerce entities must operate a grievance redressal mechanism. Rule 5(3) mandates that marketplace platforms reveal their methods for ranking items or sellers, and Rule 6(2) is the most explicit provision: it prohibits a seller from pretending to be a consumer and posting reviews of their own products.
The Information Technology Act 2000[9] regulates the digital environment in which these reviews exist. Section 43 of the Information Technology Act, 2000 imposes civil liability for unauthorised access to, or damage to, a computer resource, while Section 66 [10]criminalises the same conduct where it is done dishonestly or fraudulently. Beyond these general provisions, Section 66D [11] specifically penalises cheating by personation using a computer resource, and may become relevant in cases involving AI-generated reviews, although its application in this context remains untested by Indian courts.
Section 79 of the Information Technology Act, 2000 provides conditional safe-harbour protection to intermediaries for third-party information, subject to statutory requirements and due-diligence obligations. In Shreya Singhal v. Union of India, the Supreme Court interpreted ‘actual knowledge’ under Section 79(3)(b) as arising from a court order or notification by the appropriate government or its agency, rather than a private complaint.[12] The Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Amendment Rules, 2026, effective from 20 February 2026, reduced the time for removing unlawful information following a court order or reasoned government intimation from thirty-six hours to three hours.[13]The amendments also introduced specific due-diligence obligations concerning synthetically generated information (SGI), including prevention, labelling and traceability, with enhanced duties for Significant Social Media Intermediaries. [14]Since SGI is defined with reference to audio, visual and audio-visual information, text-only AI-generated fake reviews may fall outside its specific definition.[15]However, their creation, publication and liability remain subject to other applicable legal provisions, leaving important questions of responsibility unresolved.
CHALLENGES IN FIXING LEGAL LIABILITY
When this framework is tested against AI-generated fake reviews, several practical shortcomings become evident. The simplest form is attribution. A human reviewer can be identified and held accountable. AI-generated reviews may involve the commissioning business, the AI tool provider, and the publishing platform. The unfair trade practice provisions are aimed at the trader who gains from the deception, and this adequately addresses the commissioning business. They say almost nothing about a separate, possibly foreign, technology provider that created the content. There is also the issue of what the safe harbour in section 79 was originally intended to cover. It was designed for platforms that merely display user-generated content, not for those whose ranking algorithms could inadvertently elevate synthetic reviews to prominence via standard engagement-based sorting.
Indian courts have demonstrated some flexibility on this issue in a related context. In My Space Inc v Super Cassettes Industries Ltd, the Delhi High Court’s Division Bench ruled in a copyright dispute that a platform forfeits its safe harbour protection upon acquiring specific knowledge of infringing content; it does not always require a court order to trigger this loss.[16] It remains untested whether that same flexible interpretation could extend to platforms that promote AI-generated reviews, and the comparison is limited, as My Space’s case centred on copyright rather than consumer protection. It introduces an additional complication, as it is still voluntary. A platform that disregards it incurs no penalty unless its actions independently violate the 2019 Act, leaving a significant loophole for platforms that opt not to implement reviewer-verification systems capable of detecting synthetic content. Ultimately, the criminal provisions of the IT Act presume that an act is carried out by a human with intent- someone acting dishonestly or fraudulently. When an AI system creates content independently in response to a prompt, the assumption becomes more complex, especially when the company that commissioned the content claims it wasn’t aware of how its instructions would be carried out.
CRITICAL ANALYSIS
India’s regulatory response encompassing the Consumer Protection Act, CCPA guidelines, and BIS standards demonstrates genuine recognition of review manipulation. But it is reactive and centred on a human actor. The unfair trade practice framework assigns liability to the trader who benefits from deception, which sounds sound in theory but falters when responsibility diffuses among AI tool developers and intermediaries, each of whom can shift blame.[17] The safe-harbour rule in Shreya Singhal, intended to safeguard free speech, was never conceived for a digital era in which content itself, rather than merely its hosting, can be generated by machines. In other areas, The EU’s Digital Services Act mandates that very large online platforms identify, evaluate, and address systemic risks stemming from their services and recommender systems. India’s Intermediary Guidelines have not yet required anything this specific. India’s edge lies in speed: the CCPA can act immediately, bypassing the delays of civil litigation. However, the 2022 Guidelines have never been applied to AI-generated content, and the term ‘ endorser’ is defined in a way that presumes a human, not an AI system.[18]
SUGGESTIONS AND WAY FORWARD
A few specific actions could help bridge these gaps. The CCPA might update its Guidelines to classify AI-generated or synthetically written reviews as false representation, extending the existing ban outlined in rule 6(2) of the e-Commerce Rules. Certification for review authenticity could shift from voluntary to mandatory for platforms exceeding a specific size, with such certification linked to real reviewer-verification systems able to detect synthetic text. India has already taken steps in this direction in other areas of cyber law. In October 2025, MeitY announced revisions to Rule 3(1)(d) of the Intermediary Guidelines and launched a draft for public feedback, proposing that synthetically created content, including deepfakes, must be labelled. A comparable labelling requirement for AI-generated reviews would align well with that approach. Platforms might also be required to reveal whether they employ automated tools for generating reviews, with the level of scrutiny adjusted according to their scale. Liability rules ought to assign shared responsibility to both the trader ordering fake reviews and any tool provider that knowingly assists in generating them, thereby addressing the attribution gap mentioned earlier. Clear authenticity markers would help consumers identify synthetic reviews.
CONCLUSION
AI-created fake reviews challenge a consumer protection and cyber law framework designed for an earlier form of deception. The Consumer Protection Act 2019, Information Technology Act 2000, CCPA Guidelines, and BIS standard provide practical tools, though not comprehensive ones. Their common shortcoming is that AI-driven deception involves multiple actors, including commissioners, tool providers, and platforms. Closing that gap does not require a rewrite of Indian consumer law. It requires a focused solution grounded in mandatory technical standards, more defined responsibilities for intermediaries, and provisions for shared accountability to ensure the law evolves alongside the technology it now oversees.
Author(s) Name: Aarti Rani (S.G.T university, Gurugram)
References:
[1] OECD, Understanding Online Consumer Reviews (OECD Digital Economy Papers No 253, 2019)
[2] Federal Trade Commission, ‘Federal Trade Commission Announces Final Rule Banning Fake Reviews and Testimonials’ (14 August 2024) <https://www.ftc.gov/news-events/news/press-releases/2024/08/federal-trade-commission-announces-final-rule-banning-fake-reviews-testimonials> accessed 22 August 2026
[3] Consumer Protection Act 2019; Information Technology Act 2000.
[4] Federal Trade Commission, ‘Federal Trade Commission Announces Final Rule Banning Fake Reviews and Testimonials’ (14 August 2024) https://www.ftc.gov/news-events/news/press-releases/2024/08/federal-trade-commission-announces-final-rule-banning-fake-reviews-testimonials > accessed 22 August 2026
[5] Bureau of Indian Standards, IS 19000:2022 Online Consumer Reviews Principles and Requirements for their Collection, Moderation and Publication (BIS 2022).
[6] Consumer Protection Act 2019; Information Technology Act 2000.
[7] Consumer Protection Act 2019, ss 10, 18.
[8] Central Consumer Protection Authority, Guidelines for Prevention of Misleading Advertisements and Endorsements for Misleading Advertisements, 2022, cl 13(1).
[9]Information Technology Act 2000, s 43.
[10] Information Technology Act 2000, s 66.
[11] Information Technology Act 2000, s 66D.
[12] Shreya Singhal v Union of India (2015) 5 SCC 1, 117–19.
[13] Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Amendment Rules 2026, GSR 120(E), Gazette of India, 10 February 2026, r 3(1)(d).
[14] ibid r 3(3).
[15]Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Amendment Rules 2026, GSR 120(E), Gazette of India, 10 February 2026, r 2(1) (wa).
[16] My Space Inc v Super Cassettes Industries Ltd (2017) 69 PTC 1 (Del) (DB).
[17] Consumer Protection Act 2019, ss 2(47), 18.
[18] Central Consumer Protection Authority, Guidelines for Prevention of Misleading Advertisements and Endorsements for Misleading Advertisements, 2022, cls 2(f), 13.