Building Trust in Decision‐Support Artificial Intelligence: A Boundary Spanning Perspective

ABSTRACT Decision‐support artificial intelligence (AI) has become an essential technology for firms aiming to increase their business development by optimising strategic decisions. However, unlike other information technologies, decision‐support AI often operates as a ‘black box’, which can erode trust. The current understanding of information technology trust faces challenges when attempting to explain the role of trust in decision‐support AI when formulating business strategies. This study explores how firms can develop trust in decision‐support AI for the formulation of business strategies. By adopting a boundary‐spanning perspective, the research introduces a three‐stage model that outlines specific strategies, processes, and outcomes at each stage to nurture trust in decision‐support AI. This study contributes to the existing literature on AI trust by proposing an approach for building organisational trust in decision‐support AI and to technology trust theory by emphasising the iterative and concurrent dynamics of trust and usage within the realm of decision‐support AI, as well as the interactive capability of organisations with decision‐support AI. Additionally, it enriches the boundary‐spanning literature by offering a planned view on decision‐support AI trust development.