Ethical and Practical Considerations

Sunil Kumar (), Atreya ‘Chuck’ Chakraborty () and Poojan Patel ()
Additional contact information
Sunil Kumar: Roger Williams University
Atreya ‘Chuck’ Chakraborty: University of Massachusetts System
Poojan Patel: Bryant University

Chapter 13 in Prompt Engineering for Accounting and Finance, 2026, pp 453-509 from Springer

Abstract: Abstract This chapter examines the ethical, legal, and operational implications of integrating AI into accounting and finance practices. It analyzes key risk domains, including hallucinations, bias and fairness concerns, lack of explainability, professional overreliance, intellectual property exposure, data confidentiality, regulatory compliance, and accountability challenges. Through real-world finance scenarios, the chapter illustrates how AI systems can introduce material risks if deployed without governance structures. It proposes practical mitigation strategies such as bias audits, explainable AI tools, human-in-the-loop oversight, model documentation, data protection safeguards, and structured AI risk assessment workflows. The chapter further emphasizes the importance of professional training, ethical AI guidelines, and technical monitoring systems to ensure responsible implementation. By framing AI adoption within established accounting principles of transparency, stewardship, and accountability, this chapter positions ethical governance as foundational to sustainable AI integration in financial environments.

Keywords: AI Ethics in Finance; Algorithmic Bias; Explainable AI; Data Confidentiality; AI Governance; Professional Accountability; Responsible AI Implementation (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-11195-1_13

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DOI: 10.1007/978-3-032-11195-1_13

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