Mismatch between AI recommendations and accounting standards

The increasing use of AI in accounting and finance is transforming how organisations record, analyse and report financial information. AI-driven systems are increasingly implemented to automate tasks, enhance analytical efficiency, and support managerial decision-making. However, this rapid adoption has sparked an important debate regarding whether AI systems can truly align with the judgment-driven nature of accounting standards. This study examines the mismatch between AI recommendations and principle-based accounting frameworks such as IFRS and Ind AS. To study this issue, annual reports of 30 Indian and Global companies were analysed, and each company was assigned an AI score, reflecting the extent of AI-related disclosures and a judgment score indicating the degree of judgment-intensive accounting language.  The findings show that despite increased AI disclosure, reliance on professional judgment remains prevalent across sectors. This implies that the relationship between algorithm-based systems and principle-based accounting frameworks reflects a structural difference. While AI enhances efficiency and analytical capability, accounting standards remain interpretative and responsibility-driven. The study concludes that the future of financial reporting is not human versus machine, but human with machine. AI is most valuable when it supports human judgment, not when it attempts to replace it.