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Abstract
This study investigates how artificial intelligence (AI) reshapes buyer–supplier negotiations for non-critical items through the lens of transaction cost economics, with a focus on mundane transaction costs (MTC). Drawing on a comparative case study of four firms adopting diverse AI technologies, we show that distinct bundles of AI capabilities reduce different sub-categories of MTC. We develop a classification of four buying situations where AI is adopted in negotiations for non-critical items, highlighting how even routine categories exhibit significant heterogeneity. The findings elaborates on MTC theory by specifying its sub-dimensions and showing how AI capabilities impact the structure and magnitude of MTC in negotiations. From a managerial perspective, the study offers guidance on how to leverage AI to tailor negotiation processes for non-critical purchases, contingent on supplier characteristics and the extent of adoption.
