The Impact of Artificial Intelligence on Information Systems: Opportunities and Challenges

The increased speed at which Artificial Intelligence (AI) is integrated in Information Systems (IS) is the paradigm shift in the way organizations operate, manage their data and make decisions. In this paper, the authors are going to address the multidimensional role of AI in new IS, which is characterized by both the opportunities to transform it and the urgency of challenges related to this technology. That is why the research is based on a data-driven approach, which is cross-sectional since the current paper examines empirical studies and real-life case examples and provides statistical researches in high-impact journals and technology reports around the world to study how AI technologies: e.g., machine learning, natural language processing, intelligent automation, and others redesign IS architectures across industries. The study reveals a huge improvement of operational efficiency, cost-saving, accuracy of data processing and real-time decision making. Nonetheless, it is also revealing the challenges (such as; algorithmic biases, data governance issues, ethical concerns, and cybersecurity risks). On the thematic review of 25+ credible studies, it will be found that whereas the AI-driven IS enhances scaling and responsiveness, its adoption process is not always smooth due to the lack of technical preparedness, compliance with regulations, and skepticism towards the use of AI in the decision-making process. This paper is novel because of integrating the analysis of the opportunities and the challenges, providing the balanced picture with estimable figures. The results indicate that there is strategic alignment that is required between AI innovations with IS governance framework to realize full potential of AI. Suggestions to design ethical, resilient, as well as efficient AI-augmented IS infrastructures are presented to businesses, policymakers, and system designers. It can be argued that the present paper would serve the community of academia and the field of industry strategy by laying out the step-by-step framework that involves the sustainable and secure development of AI within corporate IS ecosystems.