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We investigate the integration of Artificial Intelligence (AI) and Data Analytics (DA) into continuous auditing. We adopt a qualitative approach with in-depth interviews with audit professionals, banking executives, data governance, and technology experts. We find that while the integration of AI and DA promises to improve audit practices significantly, its success depends on overcoming some significant challenges. These include the need for substantial investments in technology and training, ensuring data quality, and fostering a cultural shift towards innovation within audit departments. Overall, the results suggest that a strategic and holistic approach to integration is essential for realizing the full potential of AI and DA in auditing.

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Integrating Artificial Intelligence and Data Analytics: Implication for Auditing Practice

  • 会议论文

  • 发表日期：

    2025年

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  • Ahmed Beloucif,
  • Alyaa Darwish,
  • Brahim Saadouni

摘要

We investigate the integration of Artificial Intelligence (AI) and Data Analytics (DA) into continuous auditing. We adopt a qualitative approach with in-depth interviews with audit professionals, banking executives, data governance, and technology experts. We find that while the integration of AI and DA promises to improve audit practices significantly, its success depends on overcoming some significant challenges. These include the need for substantial investments in technology and training, ensuring data quality, and fostering a cultural shift towards innovation within audit departments. Overall, the results suggest that a strategic and holistic approach to integration is essential for realizing the full potential of AI and DA in auditing.