Kingsley Ofosu-Ampong, Alexander Asmah, John Amoako, Nicholas Commey
Cite: Ofosu-Ampong, K.; Asmah, A.; Amoako, J.; Commey, N. Factors Influence Artificial Intelligence Decision-making Quality. JDS, 7(1), 11-20, (2025). https://doi.org/10.33847/2686-8296.7.1_2
Abstract.Organizations are increasingly seeking ways to harness the power of artificial intelligence (AI) to enhance decision-making and build trust in the outcomes. While AI plays a significant role in shaping organizational thinking, concerns have been raised about the quality of its decisions—a topic that has received limited attention in the literature. This study aims to identify the key factors that influence the quality of AI-driven decision-making within organizational contexts. The study found that high-velocity data streams can overwhelm processing systems, often leading to incomplete analyses that distort the underlying reality. Additionally, when data is collected for different purposes or under varying contextual conditions, its relevance and reliability for AI-driven decision-making are significantly reduced. Without mechanisms to account for these contextual nuances, AI systems become prone to generating inaccurate or misleading outcomes. The findings highlight the critical need for robust processes to track, document, and communicate changes in data collection methods—particularly in environments where data is sourced from multiple, independent actors. Ultimately, the study concludes that the quality of AI decision-making is not solely a function of algorithmic sophistication but rather the result of a complex interplay between organizational, technical, and human factors.
Keywords: Artificial intelligence, decision-making quality, AI influence.
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Published online 25.06.2025