Adopting AI in Organizational Decision Making: A qualitative study

Organizational decision making is a challenging task that tends to be impactful. Decisionmakers have for more than 50 years been using different types of computational support to enable for more accurate and faster decision. In today’s business context, there is an increasing volume of data available for the decision-maker. However, humans are limited in their capacity to consume and manage data and information. In addition, humans possess biases and can be considered as unreliable decision makers. Hence, AI-enabled systems have intelligence capabilities that require some sort of such as problem solving or communicating, assisting organizations to overcome potential biases that could affect the decision. However, there is a lacking understanding of what factors influences the organizational adoption of AI-enabled system in decision making. Therefore, a qualitative investigation using six semi-structured interviews with organizational decision makers were conducted through the lens of an adapted TOE-framework. The conclusion shows that amount of data, perceived direct and indirect benefits, perceived technical competence, top management support and competitive pressure were factors perceived to be influential in the adoption. These initial insights may serve as further guidance for more research of this phenomenon