AI-Augmented Decision-Making in Dynamic Business Environments: A Qualitative Perspective

Abstract

This study aims to explore the opportunities, challenges, and organizational impacts of AI-augmented decision-making in dynamic business environments. A qualitative research design was adopted, utilizing semi-structured interviews with 17 participants from various industries, including finance, healthcare, and retail. The participants were selected using purposive sampling, and data collection was conducted via online interviews. Theoretical saturation was achieved, and data analysis was performed using NVivo software, employing thematic analysis to identify key themes and subthemes related to AI adoption in decision-making. The study identified several key opportunities of AI in decision-making, including improved efficiency, enhanced decision accuracy, innovation enablement, scalability, and collaborative decision-making. However, challenges such as trust and transparency issues, skill gaps, resistance to change, technical limitations, and cost concerns were also highlighted. Additionally, the impact of AI on organizational dynamics was evident, with significant shifts in organizational culture, employee roles, and decision-making hierarchies. Ethical considerations and the need for accountability frameworks were also emphasized. AI offers substantial opportunities for improving decision-making processes; however, organizations must address challenges related to trust, transparency, and skill gaps. The integration of AI requires a cultural shift within organizations, with an emphasis on collaboration, innovation, and ethics. To fully harness the potential of AI, organizations should invest in training, ensure data quality, and implement robust governance mechanisms.