Author(s)

Geby Patricia Siregar, Nadiyah Salsabil, Iskandar Muda^*

Affiliation(s)

Universitas Sumatera Utara, Medan, Indonesia.

Corresponding Author

Iskandar Muda

ABSTRACT

With the rapid advancement of artificial intelligence (AI) and machine learning technologies, auditing IT systems that integrate these technologies has become increasingly important. This paper examines the challenges faced in auditing IT systems that utilize AI and machine learning to ensure ethical, secure, and reliable operations. The primary focus of this study is the identification of critical issues in the implementation of AI in IT environments, such as algorithmic transparency, data accuracy, and the social and ethical impacts involved. Additionally, the paper discusses the importance of developing relevant audit standards, enhancing data security, and ensuring privacy protection in AI-based systems. To achieve these goals, an adaptive and sustainable auditing approach is required to address the complexity and dynamics of the ever-evolving technological landscape. This study provides valuable insights for audit practitioners and policymakers to ensure that AI-driven IT systems operate in accordance with appropriate principles, uphold integrity, and mitigate potential risks.

KEYWORDS

Algorithmic bias; Data integrity; Accountability in AI-powered systems

CITE THIS PAPER

Geby Patricia Siregar, Nadiyah Salsabil, Iskandar Muda. Auditing emerging technologies: challenges in AI-driven IT environments. Innovation and Technology Studies. 2025, 2(1): 17-21. DOI: https://doi.org/10.61784/its3007.

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