Ethical and Data Privacy Risks in AI-Driven Accounting: A Mixed-Methods Study

Artificial intelligence (AI) is increasingly integrated into accounting, automating tasks such as data processing, risk assessment and financial reporting. While AI offers efficiency gains, it raises ethical and data privacy risks, challenges professional accountability and tests the effectiveness of governance frameworks. This study investigates how these risks are perceived, managed and governed in AI-driven accounting environments. A mixed-methods approach was adopted, combining semistructured interviews and surveys with 24 accounting professionals in the Bristol and Bath area. The findings indicate that AI system opacity, algorithmic bias and sensitive data handling are key ethical concerns, while accountability depends on both organisational mechanisms and individual experience with AI. Governance and regulatory alignment support trust but are insufficient without ethical embedding and professional oversight. Based on these insights, the study recommends enhancing AI transparency, implementing clear accountability frameworks and embedding ethics into organisational culture.