Abstract

Conducting an artificial intelligence (AI) audit involves technical and organizational demands, which make it complicated. Throughout the AI auditing process, stakeholders may face challenges in carrying out their responsibilities. Challenges have the potential to reduce the efficiency and effectiveness of the audit. However, knowing these challenges allows stakeholders to take action to address them. Therefore, this systematic literature review (SLR) aims to investigate the challenges of auditing AI in the literature. In this research-in-progress study, 34 main challenges were identified, and then categorized into three groups, technology, organization, and environment, following the Technology Organization Environment (TOE) framework. After detailed analysis, repetitive challenges were identified, and 27 unique challenges, 12 technology challenges, 6 organization challenges, and 9 environment challenges were obtained. Understanding the challenges in AI auditing enables stakeholders to take precautions against them. By categorizing these challenges, stakeholders can better comprehend their origins and identify additional challenges within these categories.

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