Artificial Intelligence and Managerial Decision-Making: Implications for Accounting Practices

Citation

Zainuddin, Siti Afiqah and Talha, Mohammad and Yeo, Sook Fern and Baharudin, Dayana Mastura and Aina, Soyebo Yusuf and Zainuddin, Siti Hanis (2026) Artificial Intelligence and Managerial Decision-Making: Implications for Accounting Practices. In: Leveraging AI and Big Data for Business Innovation. Springer Science and Business Media Deutschland GmbH, pp. 377-385. ISBN 978-3-032-20411-0, 978-3-032-20412-7

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Abstract

Artificial intelligence (AI) is transforming management decision making by improving data analytics, pattern recognition, predictive modeling and automation. AI has important consequences for decision making in accounting, which includes how decisions are made, how decisions are evaluated, and how managerial decisions are controlled. This conceptual paper discusses AI’s role in improving management decision making through the transformation of accounting functions including budgeting, forecasting, risk assessments, and performance evaluation. The paper proposes a conceptual framework linking AI’s capabilities to management decision making outcomes and discusses how AI will impact the accounting function in terms of management decision making through the lens of theoretical perspectives including decision theory, bounded rationality, and sociotechnical systems theory. With review of literature dated 2019–2025, the paper identifies the opportunities, boundaries, and ethical implications of AI systems related to implementation of decision aiding associated with accounting.

Item Type: Book Section
Uncontrolled Keywords: Accounting practices, Artificial intelligence, Decision support systems
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management > HD30.2 Electronic data processing. Information technology. Including artificial intelligence and knowledge management
Divisions: Faculty of Business (FOB)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 28 Oct 2026 07:11
Last Modified: 28 Oct 2026 07:11
URII: http://shdl.mmu.edu.my/id/eprint/16943

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