Challenges of Integrating Artificial Intelligence in Corporate Decision-Making Processes

Abstract

In the era of the Fourth Industrial Revolution, this study explores how artificial intelligence is progressively emerging as a strategic lever within corporate decision-making processes. Through a literature review and a comparative case analysis (Amazon, Unilever, IBM Watson Health, Target), the research traces the shift from traditional hierarchical models to automated systems based on advanced data analysis. The results highlight five functional types of decision-making AI (predictive, descriptive, generative, reactive, prescriptive), emphasizing their contributions in terms of accuracy, speed, and objectivity, while also addressing limitations related to data quality, algorithmic opacity, and organizational resistance. The study recommends a multidimensional governance framework encompassing organizational, ethical, and technical dimensions as a critical condition to fully harness the benefits of AI while effectively managing its risks.