Impact Of AI And Emerging Technologies On Corporate Governance
Author: LawSphereX
Category: Corporate & Insolvency
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IMPACT OF AI AND EMERGING TECHNOLOGIES ON
CORPORATE GOVERNANCE
Riya Singh, Symbiosis Law School, Pune
ABSTRACT
By improving the efficiency of the decision-making process, regulatory compliance, risk management, and communication with stakeholders, Artificial intelligence (AI) and new technologies are revolutionizing corporate governance. New technologies such as machine learning, blockchain, and big data analysis allow for greater transparency and efficiency of operations. However, such developments are associated with various legal issues concerning the obligations of the directors, accountability of algorithms, data protection, and corporate liability. Although some countries have already begun regulating the use of AI, the Indian corporate governance system under the Companies Act, 2013, and SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015, does not have any specific regulations aimed at regulating AI-Based corporate decision-making.
This paper uses doctrinal and comparative methodology to evaluate the effect of AI on corporate governance in India. It explores the normative framework, court rulings, global regulations, and analysis of major failures in corporate governance in order to determine whether AI can ensure greater corporate responsibility while complying with the existing laws. The study indicates that artificial intelligence could play a very important role in improving fraud detection, assessment of risk, and transparency of the organisations, which are necessary for its effective application. It is emphasized that AI support rather than replacement of human intelligence is crucial in governing organizations.
The comprehensive act introducing statutory amendments, policies on governance of artificial intelligence, making assessments mandatory, and enhancing the level of control at the board should be introduced. Keywords: Companies Act, 2013, SEBI, Artificial Intelligence, Corporate Governance, Director’s duties, Algorithmic Accountability, Emerging Technologies.
INTRODUCTION
Corporate governance has long been regarded as the foundation of modern corporate law, ensuring that companies are governed with accountability, transparency, fairness, and responsibility towards stakeholders. Historically, mechanisms of governance have relied on human discretion, oversight by the board of directors, and mechanisms of regulatory compliance. However, the rapid development of Artificial Intelligence (AI) and other technologies such as blockchain, machine learning, big data analysis, and the Internet of Things (IoT) is dramatically changing the operational dynamics of corporations and the use of governance mechanisms. AI-based technologies now enable businesses to process and analyse large volumes of financial and operational data simultaneously, identify anomalies that could imply fraudulent actions, and enhance board-level decision-making.
Blockchain technology, defined by its immutable, decentralised, and distributed keeping of records, also has the capacity to revolutionize shareholder votes, compliance tracking, and transparency of records. Similarly, predictive analytics will refine systems of managing risks by identifying potential risks before they materialise before they actually occur. These technologies hold the promise of greater efficiency and accountability, consistent with the underlying goals of corporate governance. At the same time that the integration of artificial intelligence and new technologies fosters complex legal, ethical, and regulatory issues, liability expands into fiduciary duties, accountability, cybersecurity, and data protection when decisions by the board are influenced or even made by algorithms.
Concerns over data privacy, algorithmic bias, cybersecurity threats, and a lack of express statutory provisions governing technology-based governance practices add another dimension of ambiguity. Though jurisdictions like the European Union are moving towards an overarching regime of artificial intelligence with treaties like the Artificial Intelligence Act, India’s Companies Act of 20131, and Securities and Exchange Board of India (SEBI) guidelines otherwise continue to be silent regarding the issue of governance entailed by new technologies. Therefore, this study thoroughly examines whether India’s Present corporate governance system is primed to regulate Artificial Intelligence and similar technologies. In this context, it
1 Companies Act, No. 18 of 2013, Acts of Parliament, 2013 (India).
examines the potential advantages and challenges of AI-based corporate governance. It deliberates on how responsive regulations can support innovation without compromising the core values of transparency, accountability, justice, and stakeholder protection. RATIONALE OF THE STUDY: The rationale for this study is based on the growing impact of Artificial Intelligence (AI) and other emerging technologies on global corporate governance. Conventionally, structures of governance have been heavily dependent on-board monitoring, fiduciary obligations, statuterelated disclosure, and human deliberation to maintain accountability, transparency, and fairness in corporate procedures. However, heightened incorporation of AI, blockchain, big data analysis, and machine learning within corporate frameworks has strained the conventional mechanisms2.
Even as the technologies bear the potential for improved monitoring and regulatory compliance, they introduce new risks never anticipated by established corporate structures of governance. The importance of this research is also underscored by the continued occurrence of corporate failures, both internationally and in India. Corporate failures such as Enron in the United States or Satyam or IL&FS in India demonstrate how ineffective oversight and information manipulation can have catastrophic effects on shareholders, workers, and the economy more broadly. Emerging technologies have the potential to address these gaps. AI-enabled systems have the potential to detect irregularities in financial reporting, blockchain technology can protect against alteration of shareholder registers, and predictive analytics has the potential to help corporations better forecast risk3.
This research is then based on the premise that technology has the potential not merely to address existing governance gaps but also to reshape the foundations of corporate governance. In parallel, the use of artificial intelligence raises overarching questions concerning accountability, liability, and moral responsibility. If decisions are taken or materially guided by algorithms, it is unclear whether the human board of directors or the automated system should bear the burden of liability. Moreover, questions of algorithmic bias, data protection, and cyber threats illuminate the potential danger of new technologies to compromise, but not 2 Martin Petrin, The Impact of AI and New Technologies on Corporate Governance and Regulation (2023 Kwa Geok Choo Distinguished Visitors Lecture) (Aug. 1, 2023), available at SSRN.
3 Vydhrithi Reddy, Corporate Boards
Human or Bot?, SCRIPTed, Vol. 22, Issue 1 (2025). strengthen, norms of fairness and transparency4. There also lies the danger of over-reliance on electronic instruments, which has the potential to de-emphasize human judgment and fiduciary obligations, which are an inherent core of corporate law. These challenges highlight the immediate imperative to scrutinize whether the prevailing legal and regulatory framework is poised to effectively respond to these technological developments. RESEARCH HYPOTHESIS/ QUESTIONS: The study is based on the hypothesis that AI and future technologies can strengthen corporate governance with improved compliance, transparency, and decision-making, but, unless regulated correctly, also raise accountability and ethical issues. To investigate this, the following research questions are constructed:
1. In what ways do AI and new technologies influence corporate governance’s
compliance, risk management, and shareholder rights?
2. What are the legal benefits and challenges associated with integrating AI into corporate
decision-making processes? 3. Are the current Indian corporate governance laws adequate for the regulation of AIdriven practices, or is reform required?
LITERATURE REVIEW
The corporate governance-technology relationship has been extensively examined in international scholarly literature. OECD Principles of Corporate Governance (2015) emphasize the significance of transparency, accountability, and equity and describe how technology can play a pivotal role in enhancing these aims. Deloitte’s (2022) and World Economic Forum’s (2023) reports describe how artificial intelligence technologies strengthen fraud detection, broaden monitoring of compliance, and offer predictive analytics to reinforce risk management, while blockchain technologies maintain transparency in voting and shareholder recordkeeping5. 4 Jan Lieder, From Corporate Governance to Algorithm Governance, in The Cambridge Handbook of Responsible Artificial Intelligence, ch. 19 (2022).
5 Martin Petrin, The Impact of AI and New Technologies on Corporate Governance and Regulation, SSRN
Researchers, like Armour and Eidenmüller (2019), posit that artificial intelligence causes issues with common notions of fiduciary obligation through the transfer of decision-making authority from human boards to algorithms, thus causing issues of liability6. Indian academic literature, including Sarkar and Sarkar (2018), has been centered on post-scandal reform of corporate governance through the lens of Satyam-type scandals, but there remains limited scholarly discussion of the effects of artificial intelligence and information technologies in general from academic writing7. Also, studies on algorithmic government and ethics caution that while efficiency improves with automation, it might also embed hidden biases and reduce human oversight, and hence make government less accountable8.
Comparative research reveals that places like the United States and the European Union are already moving towards bespoke frameworks of governing artificial intelligence in corporate networks, while India has still not developed a clear policy direction9. Existing scholarship demonstrates the possibility of artificial intelligence and new technologies stimulating effective governance, while also noting the potential danger posed by algorithmic bias, over-dependence, and lack of accountability10. There is a noticeable knowledge void with respect to the efficacy of Indian company laws in meeting such challenges, especially vis-à-vis international regimes like the European Union's proposed AI Act (2021). Existing research on Artificial Intelligence and corporate governance has grown over the years.
However, the specific question of whether the existing Indian laws relating to corporate governance apply to AI-enabled decision-making has not received much attention. This research seeks to address that gap by examining the applicability of the Indian corporate governance framework in the context of AI-driven governance.
METHODOLOGY
This study adopts a doctrinal and exploratory research approach, focusing on the legal and (Aug. 1, 2023),
6 Vydhrithi Reddy, Corporate Boards
Human or Bot?, 22 SCRIPTed 1 (2025).
7 Jan Lieder, From Corporate Governance to Algorithm Governance, in The Cambridge Handbook of
Responsible Artificial Intelligence 356 (Markus D. Dubber, Frank Pasquale & Sunit Das eds., 2022). 8 Peter Cihon et al., Corporate Governance of Artificial Intelligence in the Public Interest, 12 Info. 275 (2021).
9 Ibid.
10 Supra note 7, at 4.
policy aspects of corporate governance concerning Artificial Intelligence (AI) and new technologies. The study primarily adopts a qualitative research methodology. It relies on analyzing statutes, regulatory frameworks, court decisions, and academic commentary to look at how technology is changing governance mechanisms. The main sources for this research include the Companies Act, 2013; relevant parts of the SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015; and international frameworks like the OECD Principles of Corporate Governance (2015) and the European Union's proposed AI Act (2021). These legal documents help assess whether current governance structures are adequate for regulating technology use.
The secondary sources consist of academic articles, books, policy papers, and reports from international organizations like the World Economic Forum, Deloitte, and PwC. These sources provide insights into how AI is being applied in corporate governance. The study also looks at comparisons with countries like the United States, the United Kingdom, and the European Union to understand global trends and possible models for reform. The study further incorporates case studies of corporate governance failures, such as Enron (2001), Satyam Computers (2009), and IL&FS (2018). This analysis evaluates whether new technologies might have prevented these failures or lessened their effects. By combining doctrinal research with case studies, the paper aims to evaluate the opportunities and risks that AI brings to governance and suggest reforms that fit the Indian legal system.
CASE
ANALYSIS
Understanding the significance of Artificial Intelligence and emerging technologies in corporate governance lies in analysing some of the serious corporate collapses, as well as their legal repercussions – a series of infamous corporate scandals that highlight how ineffective supervision, lack of visibility, and failure to implement efficient compliance policy caused the bankruptcy of a lot of corporations. Although technology itself cannot resolve governance issues, AI-supported surveillance of activities, prediction analysis, and blockchain technologies for recordkeeping might have improved internal controls and positively influenced the compliance processes significantly, and allowed to identify discrepancies earlier. The Enron scandal in 2001 is often seen as a pivotal moment in discussions about corporate governance11.
Enron committed accounting fraud by hiding debt through Special Purpose Entities, which led to one of the largest bankruptcies ever12. The court case Arthur Andersen LLP v. United States13 arose from Enron's downfall. “It brought attention to auditor liability and evidence destruction”. AI-based auditing tools and blockchain technology, if used, could have made financial reporting more transparent and secure. This might have revealed problems sooner and prevented significant investor losses. In India, the Satyam Computers scandal in 2009 showed serious issues in corporate governance and auditing14. The chairman admitted to inflating profits and falsifying accounts, resulting in one of the biggest frauds in India15. In the case Satyam Computer Services Ltd. v.
Union of India16, the Supreme Court stressed “the importance of investor protection and allowed the government to step in to protect stakeholders”. AI-driven compliance monitoring and blockchain-based accounting could have reduced the chances of such fraud by making financial data secure and enabling real-time detection of irregularities17. The IL&FS crisis in India in 2018 showed the risks of poor risk management in key financial institutions18. While there was no single major judgment, regulatory actions and investigations followed to deal with the governance failure. This case relates to judicial comments in Union of India v. Reliance Industries Ltd. 19, where the Court highlighted “the need for corporate accountability and compliance to protect the public”. Predictive AI models could have signaled IL&FS’s worsening financial condition early, prompting regulatory checks sooner.
A more recent example is Tesla, Inc. , where there are concerns about corporate governance, especially the CEO's control over decision-making20. In Tesla, Inc. Stockholder Litigation, C. A. No. 2018-0408-KSJM (Del. Ch. 2022)21, the Delaware Court of Chancery examined
11 William W. Bratton, Enron and the Dark Side of Shareholder Value, 76 Tul. L. Rev. 1275 (2002).
12 Ibid.
13 Arthur Andersen LLP v. United States, 544 U.S. 696 (2005).
14 Umakanth Varottil, The Satyam Scandal
A Case Study of India’s Corporate Governance Failure, SSRN (Mar. 6, 2010), 15 Jayati Sarkar & Subrata Sarkar, Corporate Governance in India: Evolution and Challenges, 39 Indus. Rel. J. Econ. & Soc’y 589 (2004) (contextual analysis of weak governance structures that enabled scandals like Satyam).
16 Satyam Computer Servs. Ltd. v. Union of India, (2011) 2 SCC 781 (India).
17 Arpita Mukherjee & Debashis Chakraborty, Corporate Governance in India—Is it Still Work in Progress?, Indian Council for Research on International Economic Relations (ICRIER) Working Paper No. 377 (2019).
18 Somasekhar Sundaresan, The IL&FS Debacle
Lessons for Corporate Governance in India, Econ. & Pol.
Wkly., Vol. 53, No. 43 (2018).
19 Union of India v. Reliance Indus. Ltd., (2018) 17 SCC 581 (India).
20 Matt Levine, Tesla’s Board Independence on Trial, Bloomberg Opinion (Apr. 28, 2022).
21 In re Tesla, Inc. Stockholder Litig., C.A. No. 2018-0408-KSJM (Del. Ch. Apr. 27, 2022).
board independence and shareholder rights in deals involving Elon Musk. This case demonstrates “the risks of relying too much on technology-driven decisions and concentrated leadership, emphasizing the need for governance checks, even in innovative companies”. The Tesla case illustrates that the use of new technologies has not reduced the responsibilities of directors. No matter how much AI facilitates decision-making in companies, directors must still have their own opinions and act honestly and in the interests of their companies and stakeholders. AI may support the governance for an organisation, but it cannot substitute the legal obligations directors have under corporate law. Another crucial case is the Kingfisher Airlines crisis in India in 2012, where poor management, high debt, and lack of accountability caused the airline's failure.
Although it didn’t lead directly to a major judicial ruling, cases like State Bank of India v. Kingfisher Airlines Ltd. 22 showed “how bad governance harmed creditor interests and public funds”. AI-based risk assessment tools could have raised alarms about unsustainable borrowing and resource misuse, helping to protect stakeholder interests. Similarly, the Nirav Modi–Punjab National Bank scam in 2018 exposed major flaws in the internal controls of financial institutions23. While the legal proceedings are still ongoing, cases like Punjab National Bank v. Nirav Modi24 highlight “the judiciary’s focus on corporate accountability”. If blockchain ledger systems or AI fraud detection tools had been in place, the issuance of fraudulent Letters of Undertaking could have been either avoided or detected much sooner, reducing the losses faced by public institutions.
These cases illustrate two important points. First, traditional governance systems often fail to spot or stop misconduct in time, leading to significant harm for investors, creditors, and the economy. Second, AI and new technologies can help provide better transparency, accountability, and risk detection. However, these tools need to fit within a strong legal framework because technology alone cannot replace ethical governance and judicial oversight. The mentioned case studies illustrate that artificial intelligence should not be seen as a replacement for successful corporate governance but rather as an instrument that strengthens
22 State Bank of India v. Kingfisher Airlines Ltd., (2012) (Karnataka High Court, India).
23 R. Gandhi, PNB Scam
Lessons in Governance, Risk, and Compliance for Indian Banks, Econ. & Pol. Wkly., Vol. 53, No. 9 (2018).
24 Punjab Nat’l Bank v. Nirav Modi, (2018) (Special CBI Court, Mumbai, India).
current governance systems. The efficiency of artificial intelligence ultimately relies on the proper legislation, careful supervision by humans, and definite standards of accountability. Thus, technology must support, not replace, the basic principles of corporate governance.
FINDINGS
The findings indicate that the role of Artificial Intelligence and emerging technologies in corporate governance reveals several important findings: Persistent Gaps in Traditional Governance Mechanisms: The case studies of Enron, Satyam, IL&FS, Kingfisher, and the PNB scam show that traditional corporate governance methods, such as board oversight, statutory audits, and regulatory compliance, often fail to catch fraud and mismanagement early. These shortcomings highlight the need for technology to improve accountability and transparency. Potential of AI and Emerging Technologies: Artificial Intelligence, blockchain, and data analytics can transform corporate governance. They offer real-time monitoring, predictive risk assessment, and fraud detection, which can lessen the reliance on human judgment alone.
In cases like Satyam and PNB, these technologies could have reduced or prevented financial misreporting and fraud. Judicial Recognition of Governance Failures: Judicial rulings, including Satyam Computer Services Ltd. v. Union of India25 and Arthur Andersen LLP v. United States26, emphasize the courts’ focus on transparency, accountability, and protecting investors. Although these cases did not involve AI directly, they highlight governance principles that technology could support. Challenges of Over-Reliance on Technology: The Tesla litigation shows that even in tech-savvy companies, excessive reliance on strong leadership and unchecked decision-making can create governance risks. This finding suggests that technology should enhance ethical leadership and robust institutional frameworks, not
25 Supra note 17, at 7.
26 Supra note 14, at 6.
replace them. SUGGESTIONS: This research suggests that while Artificial Intelligence and new technologies have great potential to change corporate governance, their use must be regulated and integrated thoughtfully. A complete approach is necessary. At the legal level, corporate governance frameworks like the Companies Act, SEBI regulations, and related rules need to be reviewed and updated. They should include clear guidelines for using AI, blockchain, and automated decision-making tools in compliance, auditing, and reporting. These changes would provide legal clarity, prevent misuse, and promote responsible innovation. On the institutional side, companies should be encouraged to use AI in governance, not just in financial auditing but also for board decision-making, communicating with shareholders, and managing risk.
However, these systems need to operate under the supervision of independent directors, audit committees, and regulators to maintain accountability. The ethical principles of fairness, transparency, and fiduciary duty must remain intact, and technology should support governance, not replace it. Universities, research institutions, and professional organizations should work together to create specialized courses on law, governance, and new technologies to prepare future corporate leaders. At the same time, safeguards must be put in place to manage the risks that come with adopting technology. Concerns such as data privacy, cybersecurity, algorithmic bias, and dependence on automation need strict regulatory oversight.
A solid data protection law, along with specific industry guidelines, should make sure that while transparency and accountability improve, the rights of shareholders and stakeholders are protected.
CONCLUSION
This study demonstrates that Artificial Intelligence and new technologies can significantly change corporate governance by improving transparency, accountability, and risk management. A review of literature, case studies, and legal frameworks makes it clear that these technologies can strengthen compliance, enhance decision-making, and provide insights that traditional governance often does not achieve. However, the research also points out that technology by itself cannot ensure effective governance. Relying too much on AI or automated systems without proper human oversight may lead to ethical issues, biased algorithms, and gaps in accountability. Legal cases and corporate scandals discussed in this study reveal that the basic principles of fiduciary duty, ethical leadership, and regulatory compliance are still essential for good governance.
The findings also show that while regions like the European Union have started to create rules for AI in corporate governance, Indian laws, including the Companies Act of 2013 and SEBI regulations, need major updates to tackle technological challenges and opportunities. Combining AI with strong legal, ethical, and institutional safeguards is crucial to maximizing benefits and reducing potential risks. In conclusion, the mix of technology, law, and ethics offers a chance to reshape corporate governance in India. By responsibly adopting AI and new technologies and incorporating them into solid regulatory frameworks, companies can achieve better governance, protect stakeholder interests, and build trust in the corporate sector, leading to sustainable growth and accountability.