We expect financial reports to tell the truth. But managers have their discretion in how they present numbers, and sometimes, they use that flexibility to polish the reality. This is called ‘Earnings Management’ (Dechow et al., 2010), and it quietly erodes investor trust. The problem runs deeper in emerging markets, when a handful of promoters calls the shots and governance rules are still evolving, earnings management can easily fly under the radar. Now, enter AI. Artificial Intelligence is transforming how companies report, how boards oversee, and how regulators detect trouble. Smart algorithms can scan millions of transactions, flag suspicious patterns, and alert auditors in real time. In theory, AI could make earnings management much harder to hide. But technology alone is not enough. This paper asks a simple question: as AI reshapes financial reporting, can stronger governance and smarter ownership structures keep earnings management in check? Or will new tools just create new ways to game the system? Rather than running fresh models, this study synthesizes decades of research on why ownership matters, how boards and audit committees guard transparency, and where institutional investors make a difference (Jensen & Meckling, 1976; Shleifer & Vishny, 1997). It then brings these insights into the AI era, asking whether old governance rules still apply when machines are part of the picture. The takeaway? AI-driven tools can certainly strengthen oversight. But they work best when grounded in robust governance frameworks. Technology without strong oversight is just speed without direction.
corporate governance, earnings management, ownership structure, emerging markets, India, AI text analytics, theoretical framework.
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