GenAI in industrial B2B sales – for which types of industrial goods and where along the sales process to apply?

Purpose This study aims to classify the current applicability of generative artificial intelligence (GenAI) along the business-to-business (B2B) sales process regarding different types of industrial B2B goods. Previous artificial intelligence (AI) studies in B2B sales have not considered the special characteristics of different types of industrial goods and the respective sales process regarding the applicability of GenAI. Design/methodology/approach To close this gap, this study combines a systematic literature review on strengths and weaknesses of GenAI with 20 expert interviews from B2B companies, covering 31 types of B2B goods. Expert assessments were structured using a scoring model that maps GenAI capabilities to sales tasks across the B2B sales process and different types of B2B goods, and were subsequently analyzed using hypothesis-testing. Findings The results show that GenAI creates the greatest value in standardized product-businesses and in analytically intensive early sales phases such as prospecting across all types of B2B goods. Its effectiveness gradually declines along the sales process, particularly in later negotiation- and trust-intensive phases of project-, system- and integration-businesses, where customization, relational investment and interpersonal trust are critical. Following an initial purchase, GenAI strengths increase sharply again during the follow-up phase for all business types, especially for those with a transaction bond. Originality/value This study advances B2B sales and AI research by introducing a context-sensitive perspective that links classic industrial goods typologies with GenAI-enabled sales processes. Rather than viewing GenAI as universally beneficial, the findings highlight its role as a conditional sales enablement tool whose value depends on task structure, relational requirements and business-type characteristics.