Artificial intelligence maturity in buyer–seller exchange

Artificial intelligence (AI) is rapidly reshaping business-to-business (B2B) buying and selling, yet research has largely examined AI as a unilateral process enabler. While this perspective has generated important insights regarding AI adoption and performance, it overlooks a fundamental characteristic of B2B selling: exchange outcomes depend on the compatibility of buyer–seller decision processes at the exchange interface. To address this gap, the authors advance the concept of AI exchange maturity (i.e. extent to which decision authority within buyer–seller exchange is delegated to AI systems) and theorize its organizational antecedents. Building on this construct, the authors develop a bilateral theory of buyer–seller AI exchange in which value co-creation depends on the configuration of AI exchange maturity across exchange partners. The framework identifies four configurations (buyer AI-maturity advantage, seller AI-maturity advantage, agentic-AI maturity alignment, and pre-AI maturity alignment) and theorizes how each configuration shapes value co-creation through information-processing fit and buyer–seller trust. The authors further identify strategies for selling organizations to manage each configuration to enhance value co-creation. In doing so, the framework shifts the theoretical focus from whether individual firms adopt AI to the distribution of decision authority between humans and AI systems across exchange partners.