The AI Wave Hitting The Audit Profession: A Systematic Litterature Review

Abstract

This thesis explores the impact of artificial intelligence (AI) on the audit profession, focusing on the benefits, challenges, and necessary adaptations. Through a comprehensive literature review, four key themes emerge: enhancing audit quality, addressing implementation challenges, adjusting workforce and education, and managing legal and ethical considerations.

AI has the potential to improve decision-making, enhance audit quality, and automate repetitive tasks, freeing auditors to focus on complex analysis. However, human judgment remains crucial, and the complete replacement of auditors is not expected. Skill acquisition, cost, algorithm interpretability, and maintaining professional identity are key challenges in AI adoption. Furthermore, ethical and legal considerations to take into account encompass issues with accountability, bias, data privacy, and job displacement. Clear guidelines and standards are essential for responsible AI use in auditing. Ongoing research and practical insights are needed to validate findings and keep pace with evolving AI developments.

In conclusion, this thesis provides a comprehensive overview of AI's impact on auditing. By acknowledging the importance of human expertise, addressing challenges, and ensuring ethical practices, auditors can navigate the AI landscape and embrace its potential. Further research and dialogue will guide the profession toward a future where AI and auditors collaborate effectively.

This thesis explores the impact of artificial intelligence (AI) on the audit profession, focusing on the benefits, challenges, and necessary adaptations. Through a comprehensive literature review, four key themes emerge: enhancing audit quality, addressing implementation challenges, adjusting workforce and education, and managing legal and ethical considerations.

AI has the potential to improve decision-making, enhance audit quality, and automate repetitive tasks, freeing auditors to focus on complex analysis. However, human judgment remains crucial, and the complete replacement of auditors is not expected. Skill acquisition, cost, algorithm interpretability, and maintaining professional identity are key challenges in AI adoption. Furthermore, ethical and legal considerations to take into account encompass issues with accountability, bias, data privacy, and job displacement. Clear guidelines and standards are essential for responsible AI use in auditing. Ongoing research and practical insights are needed to validate findings and keep pace with evolving AI developments.

In conclusion, this thesis provides a comprehensive overview of AI's impact on auditing. By acknowledging the importance of human expertise, addressing challenges, and ensuring ethical practices, auditors can navigate the AI landscape and embrace its potential. Further research and dialogue will guide the profession toward a future where AI and auditors collaborate effectively.