This study investigates the quality of decision-making processes in corporate teams – a construct that is often overlooked or insufficiently operationalized in existing research. Based on the comprehensive framework by Spetzler et al. (2016), this research systematically assesses process quality, examines its influence on perceived decision-making success and identifies key factors that shape the decision-making processes quality in the context of team decision-making. A quantitative survey was conducted among 461 employees in Germany who regularly participate in team decision-making. Structural equation modeling was used to analyze the impact of a supportive organizational culture and the perceived relevance of the team decision on decision process quality, and subsequently the impact of this quality on the perceived success. Results show that both factors significantly enhance process quality, which in turn strongly predicts the perceived success. Additionally, the study explores how artificial intelligence (AI) as decision support influences process quality. A group comparison between employees with and without experience in AI-supported team decision-making and regression analyses reveal that actual use of AI is associated with higher trust in intelligent systems and a more favorable assessment of process quality. Trust in AI significantly predicts process quality across both groups. These findings contribute to the understanding of the determinants of decision-making quality and the emerging role of AI in organizational decision contexts. From a practical perspective, organizations can improve decision-making processes by providing sufficient resources and communicating the relevance of decisions. AI should be explored by users beforehand and fears addressed at an early stage to enhance trust and thus process quality.
