Summary

Purpose: This study assesses the perceived quality of the outcomes in decision-making phases by using the conversational ai approach.
Design/Method: The research adopts an experimental design to explore the impact of conversational artificial intelligence (AI) in the separate phases of a decision-making making process. This investigation is conducted through a team-level “Shark Tank” game, which serves as a dynamic platform.
Findings: The data indicated a discernible pattern across all five steps of the decision-making process. The integration of AI, particularly Conversational AI, consistently improves the perceived quality of decisions, with varying degrees of impact at various stages.
Originality/Value: This study contributes by particularly focusing on the conversational AI approach, to discern its efficacy in enhancing decision making processes. It is critical in contributing to the rapidly growing field of AI in decision making, providing a deeper understanding of AI's role in improving decision making quality.