NAVIGATING ETHICS AND RISK IN ARTIFICIAL INTELLIGENCE APPLICATIONS WITHIN INFORMATION TECHNOLOGY: A SYSTEMATIC REVIEW

Abstract

Advancements in artificial intelligence (AI) have profoundly transformed a wide array of sectors, with Information Technology (IT) standing at the forefront of this revolution. AI technologies have reshaped IT operations by introducing new levels of automation, predictive capabilities, decision-making precision, and efficiency, resulting in sweeping changes across organizational infrastructures and service delivery models. However, alongside these technological breakthroughs, the integration of AI has surfaced numerous ethical concerns and associated risks that warrant critical and comprehensive exploration. Issues such as algorithmic bias, privacy breaches, lack of transparency, accountability dilemmas, and cybersecurity vulnerabilities remain pervasive, posing significant challenges for organizations seeking to deploy AI responsibly. Recognizing these complexities, this study focuses on examining the ethical challenges, risk factors, and essential considerations surrounding the deployment of AI within IT environments. This research addresses the urgent and growing necessity for organizations to adopt robust ethical frameworks and effective risk management strategies to ensure that AI integration promotes fairness, transparency, and accountability. A comprehensive synthesis of existing literature further enriches this foundation by offering diverse perspectives on the ethical and risk-related challenges posed by AI, highlighting both the transformative potential and the vulnerabilities associated with its integration into IT systems. Through this review, key gaps in the current body of knowledge are identified, particularly regarding the practical implementation of ethical standards and risk mitigation strategies across varied organizational contexts. Adopting a qualitative research methodology, the study employs a case study approach to explore the intricate, multifaceted issues involved in AI integration within IT operations. This methodological choice allows for a nuanced understanding of real-world scenarios, organizational behaviors, and stakeholder dynamics related to AI deployment. Data collection is meticulously based on trustworthy sources, including peer-reviewed academic journals, authoritative industry reports, regulatory and governmental publications, and credible news articles, ensuring the comprehensiveness and reliability of insights gathered. By triangulating data across multiple domains, the study captures a holistic view of the ethical landscape surrounding AI in IT. Finally, the research culminates with an in-depth interpretation of findings, accompanied by practical recommendations and implications. These outcomes aim to contribute to the development of ethical, sustainable, and responsible AI integration practices within the IT industry, supporting organizations in navigating the complex interplay between technological innovation and ethical accountability.