This research explores the use of AI in organizations’ decision-making by adopting an Action Design Research (ADR) method to reveal the means, potential, and best practices. Indeed, there has been a signification of AI in decision-making, and these features accompany the technology with the potential to improve the efficiency, accuracy, and predictability of decision-making. However, significant problems, including transparency, ethical questions, and users’ resistance, prevent its smooth implementation. Focus groups, interviews, and document reviews form the basis of this research, which aims at properly examining these dynamics in detail. The findings are categorized into five themes: mixed concerns like implementing complexities and challenges, shared opportunities, knowledge of ethics for clinical interoperability, the concept of governance and regulation, and examining the best practices for integration processes. The findings highlight that ethical and organizational challenges persist while AI application means a democratized decision-making opportunity and virile analytical support. Consumers also stressed the need for transparency, engagement with customers, and regulations befitting the sector’s requirements. The study ends with design principles to be followed by organizations that intend to implement AI solutions with positive outcomes and minimal harm.
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