Artificial Intelligence and Securities Regulation: Rethinking SEBI’s Approach to AI-Generated Financial Advice in India

Abstract

The increasing use of Artificial Intelligence (“AI”) in financial services has transformed the manner in which investment-related information is generated, disseminated, and consumed.[1] AI-powered tools, ranging from robo-advisers to generative AI systems, are now capable of producing investment recommendations that influence investor behaviour without direct human intervention.[2] While these technologies enhance accessibility, efficiency, and financial inclusion, they also raise significant regulatory concerns relating to accountability, transparency, investor protection, and market integrity.[3] India’s securities regulatory framework, primarily administered by the Securities and Exchange Board of India (“SEBI”), was developed at a time when investment advice was predominantly provided by human advisers and research analysts.[4] Consequently, uncertainty remains regarding the extent to which existing regulations adequately address the challenges posed by AI-generated financial advice.[5] This article examines the limitations of the current regulatory framework, analyses the legal risks associated with AI-driven advisory systems, and evaluates comparative approaches adopted in other jurisdictions.[6] It argues that SEBI must move beyond traditional regulatory assumptions and develop a specialised framework capable of addressing the unique risks of AI-generated financial advice while preserving the benefits of technological innovation within India’s securities markets.[7]

Keywords: Artificial Intelligence, Securities Regulation, SEBI, AI-Generated Financial Advice, Robo-Advisers, Investor Protection, Financial Technology, Algorithmic Accountability, Capital Markets, Regulatory Reform.

Introduction

Artificial Intelligence (“AI”) is increasingly reshaping the financial services industry by transforming the manner in which investment-related information is generated, analysed, and disseminated.[8] From automated trading systems and portfolio management tools to sophisticated generative AI platforms, technological innovation has enabled market participants to access financial insights with unprecedented speed and efficiency.[9] As these technologies become more widely available, investors are increasingly relying upon AI-driven systems for investment-related guidance and decision-making.[10]

The adoption of AI within financial markets presents several advantages. AI-powered tools can process vast quantities of data, identify patterns that may not be readily observable to human analysts, and provide recommendations at a significantly lower cost than traditional advisory services.[11] These developments have the potential to improve financial inclusion by making investment-related information more accessible to retail investors who may otherwise lack access to professional financial advice.[12]

Despite these benefits, the growing use of AI-generated financial advice raises important legal and regulatory concerns.[13] Existing securities regulations were developed on the assumption that investment advice would be provided by identifiable individuals or regulated entities capable of being supervised and held accountable for their conduct.[14] AI systems challenge this assumption by generating recommendations through complex algorithms that may operate with varying degrees of autonomy. Questions therefore arise regarding accountability, transparency, investor protection, and the adequacy of existing regulatory safeguards.

In India, the Securities and Exchange Board of India (“SEBI”) regulates investment advisers, research analysts, and other market intermediaries through a comprehensive framework designed to protect investors and maintain market integrity. However, these regulations were formulated before the widespread emergence of advanced AI technologies capable of generating investment-related recommendations. Consequently, uncertainty remains regarding the extent to which existing laws can effectively govern AI-driven advisory services.

This article examines the regulatory challenges posed by AI-generated financial advice and evaluates whether India’s existing securities framework is equipped to address them. It argues that SEBI must adopt a more specialised regulatory approach that balances technological innovation with accountability, transparency, and investor protection.

1. Understanding AI-Generated Financial Advice

Artificial Intelligence has become an increasingly important component of modern financial services. While technology has long been used to support investment decisions, recent advances in machine learning and generative AI have significantly expanded the role of automated systems within the financial sector. AI is now capable of analysing market trends, processing large volumes of financial data, identifying investment opportunities, and generating recommendations that may influence investor behaviour.

AI-generated financial advice may broadly be understood as investment-related guidance produced wholly or partially through artificial intelligence systems. Such advice may be delivered through robo-advisers, algorithmic recommendation engines, AI-powered chatbots, or generative AI platforms capable of responding to user-specific financial queries. These systems often rely upon historical market data, economic indicators, corporate disclosures, and user-provided information to generate investment-related outputs.

One of the earliest and most widely adopted forms of AI-driven advisory services is the robo-adviser. These platforms utilise algorithms to recommend investment portfolios based on factors such as financial objectives, risk tolerance, and investment horizon. More recently, generative AI tools have expanded the scope of automated financial assistance by engaging directly with users and providing responses in natural language. As a result, investors increasingly interact with AI systems in a manner that resembles consultation with a human adviser.

The growing accessibility of AI-powered financial tools has contributed significantly to their adoption. Investors can obtain market information and investment recommendations quickly and often at a lower cost than traditional advisory services. This development has the potential to promote financial inclusion by improving access to investment-related information for retail investors.

However, the increasing reliance on AI-generated recommendations also introduces regulatory concerns. Investors may not fully understand the limitations of AI systems, the quality of the underlying data, or the assumptions embedded within algorithmic models. Consequently, AI-generated financial advice occupies a unique position within contemporary securities markets, combining the efficiency of automation with functions traditionally performed by regulated financial professionals. This convergence raises important questions regarding accountability, transparency, and investor protection, which existing regulatory frameworks may not be fully equipped to address.

2. Existing Indian Regulatory Framework and Its Limitations

India’s securities markets are regulated by the Securities and Exchange Board of India (“SEBI”), which is entrusted with the responsibility of protecting investor interests and ensuring the orderly development of capital markets. The principal legislation governing the securities market is the Securities and Exchange Board of India Act, 1992, which grants SEBI broad powers to regulate intermediaries, prevent unfair market practices, and safeguard investors. In addition to the parent legislation, investment advisory activities are governed by the SEBI (Investment Advisers) Regulations, 2013, while securities research and recommendations are regulated under the SEBI (Research Analysts) Regulations, 2014.

These regulations establish registration requirements, disclosure obligations, conflict-management standards, and professional responsibilities for persons engaged in providing investment advice or securities research. The regulatory framework is designed to ensure that investors receive recommendations from qualified and accountable individuals or entities operating under regulatory supervision. In this respect, the existing framework has played an important role in promoting transparency and investor confidence within India’s securities markets.

However, the regulatory architecture was developed on the assumption that investment advice originates from identifiable human actors or regulated entities. AI-generated financial advice challenges this assumption. Where investment recommendations are generated through automated systems, it becomes difficult to determine whether responsibility should be attributed to the software developer, the platform operator, the financial institution deploying the technology, or another intermediary involved in the advisory process. Existing regulations provide limited guidance on how such responsibility should be allocated.

Recent regulatory initiatives concerning finfluencers demonstrate SEBI’s willingness to address emerging forms of financial influence in digital environments. Nevertheless, these measures primarily focus on human actors and commercial relationships rather than autonomous or semi-autonomous advisory technologies. As a result, important questions relating to algorithmic accountability, automated decision-making, and AI-driven investment recommendations remain largely unaddressed.

An additional difficulty arises from the absence of significant Indian judicial guidance on the regulation of AI-generated financial advice. While Indian courts have addressed various issues relating to technology, data governance, and digital platforms, they have not yet directly examined questions concerning liability, accountability, or investor protection in the context of AI-driven investment recommendations. Consequently, regulators and market participants must navigate this evolving area without the benefit of settled judicial principles, further contributing to regulatory uncertainty.

This regulatory uncertainty highlights the need to reassess whether existing securities laws remain adequate in an era where technology is increasingly performing functions once reserved for regulated financial professionals.

3. Legal Challenges Created by AI-Generated Financial Advice

3.1 Accountability and Liability
A central challenge posed by AI-generated financial advice is determining responsibility when investors suffer losses due to inaccurate or misleading recommendations. Traditional securities regulation assumes that investment advice originates from identifiable individuals or entities capable of being subjected to regulatory oversight and legal liability. AI systems complicate this framework by introducing multiple actors into the advisory process, including software developers, platform operators, financial institutions, and data providers.

Where an AI-generated recommendation results in investor harm, existing regulations provide limited guidance regarding which party should bear responsibility. This uncertainty may weaken investor confidence and create difficulties in regulatory enforcement. As AI systems become increasingly sophisticated and autonomous, questions of liability are likely to assume greater significance within securities markets.

3.2 Transparency and Explainability
Another significant concern relates to the transparency of AI-driven decision-making. Many advanced AI systems operate through complex algorithms that are not easily understood by investors or regulators. Consequently, users may receive investment recommendations without knowing the factors that influenced the outcome or the limitations of the underlying model.

This lack of explainability presents challenges for investor protection. Securities regulation traditionally relies upon disclosure and informed decision-making as mechanisms for safeguarding investors. If investors are unable to understand how recommendations are generated, they may find it difficult to assess their reliability. Similarly, regulators may face obstacles when investigating misconduct or evaluating compliance with existing legal standards.

3.3 Investor Protection Concerns
Although AI systems can process information efficiently and improve access to financial services, they remain vulnerable to errors arising from inaccurate data, flawed algorithms, or biased training models. Such weaknesses may result in recommendations that are unsuitable for particular investors.

A related concern is the tendency of users to place excessive trust in technological systems. Investors may assume that AI-generated recommendations are inherently objective or more reliable than human judgment. This perception can encourage overreliance on automated advice and reduce independent assessment of investment decisions, particularly among retail investors with limited financial expertise.

3.4 Market Integrity and Manipulation Risks
The increasing use of AI-generated financial advice also raises concerns regarding market integrity. If large numbers of investors rely upon similar recommendation systems, market behaviour may become increasingly concentrated, potentially contributing to volatility and inefficient price discovery.

In addition, AI technologies may be misused to generate misleading financial content or influence investor sentiment at scale. The speed and reach of digital platforms amplify the potential impact of such activities, creating new challenges for regulators seeking to preserve fair and orderly markets.

Collectively, these concerns demonstrate that AI-generated financial advice presents challenges extending beyond technological innovation. The issues of accountability, transparency, investor protection, and market integrity reveal significant regulatory gaps that existing securities laws are not fully equipped to address.

4. Comparative Regulatory Approaches: Lessons from the United States, European Union, and United Kingdom

The challenges posed by AI-generated financial advice are not unique to India. Regulators across the world are increasingly examining how artificial intelligence affects investor protection, market integrity, and regulatory accountability. Although no jurisdiction has yet adopted a comprehensive framework specifically governing AI-generated financial advice, several approaches offer valuable guidance.

In the United States, the Securities and Exchange Commission (“SEC”) generally applies existing securities laws to AI-driven advisory services. Robo-advisers and algorithm-based investment platforms remain subject to fiduciary obligations, disclosure requirements, and investor protection standards applicable to traditional advisers. At the same time, the SEC has expressed growing concern regarding the use of predictive analytics and artificial intelligence in influencing investor behaviour, emphasising that technological innovation does not diminish regulatory responsibility.

The European Union has adopted a more structured approach through the European Union Artificial Intelligence Act (“EU AI Act”). The legislation establishes a risk-based framework that imposes obligations relating to transparency, risk management, governance, and human oversight for certain categories of AI systems. Although not directed exclusively at financial services, the Act reflects a regulatory preference for addressing AI-related risks before significant harm occurs. Its emphasis on accountability and explainability offers useful lessons for financial regulators.

The United Kingdom has favoured a principles-based model. The Financial Conduct Authority (“FCA”) has encouraged innovation while continuing to emphasise accountability, fairness, transparency, and consumer protection. Rather than introducing extensive AI-specific legislation, the FCA seeks to adapt existing regulatory principles to emerging technologies.

Despite their differences, these approaches reveal common regulatory priorities. Transparency, accountability, and human oversight are increasingly regarded as essential safeguards for AI-driven systems. For India, the comparative experience suggests that neither complete regulatory restraint nor excessive intervention is desirable. A balanced framework that promotes innovation while protecting investors is likely to provide the most effective response to the growing use of AI-generated financial advice.

5. The Case for a Dedicated SEBI Framework for AI-Generated Financial Advice

The increasing use of artificial intelligence in investment-related services highlights the need for a regulatory framework specifically tailored to AI-generated financial advice. While existing securities regulations provide a foundation for regulating traditional investment advisers and research analysts, they do not adequately address the unique challenges created by automated and algorithm-driven recommendations. As AI systems become more sophisticated and influential, regulatory clarity will become essential for both investor protection and market confidence.

A dedicated SEBI framework should first clarify the circumstances in which AI-generated recommendations constitute regulated investment advice. Clear regulatory definitions would reduce uncertainty for market participants and ensure that AI-driven advisory services remain subject to appropriate oversight. Such clarification would also assist in distinguishing personalised investment recommendations from general financial information or educational content generated through AI systems.

Transparency should form a central component of any future regulatory regime. Investors should be informed whenever investment-related recommendations are generated wholly or substantially through artificial intelligence. Meaningful disclosure requirements would allow investors to better understand the nature of the advice they receive and make more informed decisions. In addition, regulated entities should maintain records concerning the data sources, methodologies, and assumptions used by AI systems.

Accountability must also remain a core regulatory principle. Regardless of the sophistication of the technology involved, responsibility for compliance should remain with identifiable legal entities rather than the AI system itself. Financial institutions and platform operators deploying AI-driven advisory tools should therefore remain accountable for regulatory breaches, governance failures, and investor harm arising from the use of such technologies.

SEBI may also consider introducing periodic algorithmic audits and risk assessment requirements. Independent reviews could help identify biases, operational weaknesses, and conflicts of interest before they adversely affect investors. Such measures would strengthen confidence in AI-driven financial services while encouraging responsible innovation.

Ultimately, the objective of regulation should not be to restrict technological development but to ensure that innovation occurs within a framework that safeguards investor interests. A dedicated regulatory framework would provide legal certainty, strengthen accountability, and better equip India’s securities markets to respond to the challenges presented by rapidly evolving AI technologies.

Conclusion

Artificial Intelligence is rapidly transforming the manner in which financial advice is generated, delivered, and consumed within modern securities markets. While AI-driven technologies offer significant benefits in terms of efficiency, accessibility, and financial inclusion, they also challenge many of the assumptions underlying traditional securities regulation. Existing Indian regulations governing investment advisers and research analysts were designed primarily for human actors and therefore provide limited guidance on issues unique to AI-generated financial advice.

This article has demonstrated that the increasing use of AI in investment-related activities creates important concerns relating to accountability, transparency, investor protection, and market integrity. Comparative developments in the United States, the European Union, and the United Kingdom further indicate that regulators worldwide are grappling with similar challenges and are increasingly recognising the need for appropriate safeguards governing AI-driven financial services.

As artificial intelligence becomes more deeply integrated into capital markets, regulatory inaction may create uncertainty for both investors and market participants. A dedicated SEBI framework that promotes transparency, accountability, and responsible innovation would help ensure that technological progress develops alongside effective investor protection and regulatory confidence. The challenge for regulators is not whether AI should be permitted to participate in financial markets, but how it can be governed in a manner that preserves both innovation and trust.

References

[1] Securities and Exchange Board of India Act, 1992, No. 15 of 1992, India Code (1992).
[2] Securities and Exchange Board of India (Investment Advisers) Regulations, 2013, Gazette of India, pt. III sec. 4 (Jan. 7, 2013).
[3] Securities and Exchange Board of India (Research Analysts) Regulations, 2014, Gazette of India, pt. III sec. 4 (Sept. 1, 2014).
[4] Regulation (EU) 2024/1689 of the European Parliament and of the Council laying down harmonised rules on Artificial Intelligence (Artificial Intelligence Act), 2024 O.J. (L 1689).
[5] Securities and Exchange Board of India, Consultation Paper on Association of SEBI Registered Intermediaries/Regulated Entities with Unregistered Entities (including Finfluencers) (Aug. 25, 2023).
[6] Securities and Exchange Board of India, Details/Clarifications on Provisions Related to Association of Persons Regulated by the Board with Persons Engaged in Prohibited Activities (Circular dated Jan. 29, 2025).
[7] U.S. Securities and Exchange Commission, Conflicts of Interest Associated with the Use of Predictive Data Analytics by Broker-Dealers and Investment Advisers, Exchange Act Release No. 34-97990 (July 26, 2023).
[8] Financial Conduct Authority, AI Update: A Discussion Paper on Artificial Intelligence in Financial Services (2024).
[9] International Organization of Securities Commissions (IOSCO), Artificial Intelligence and Machine Learning in Capital Markets (Final Report, 2021).
[10] Cary Coglianese & Alicia Lai, Algorithm versus Human Advice, 71 Duke L.J. 1 (2023).
[11] Harry Surden, Artificial Intelligence and Law: An Overview, 35 Ga. St. U. L. Rev. 1305 (2019).
[12] Organisation for Economic Co-operation and Development (OECD), Artificial Intelligence in Society (OECD Publishing, 2023).
[13] World Economic Forum, The Future of Artificial Intelligence in Financial Services (2024).
[14] Manojkumar Bansode, Artificial Intelligence and Securities Regulation: Rethinking SEBI’s Approach to AI-Generated Financial Advice in India (2026).