The “Dark Side” of AI in B2B Consulting: Conceptual Foundations, Empirical Cases, Managerial Insights

This chapter of the monograph is focused on the “dark side” of AI integration into the activities of entrepreneurship infrastructure organizations (EIOs) and consulting companies operating in the B2B segment. In the study, AI is interpreted as an epistemic intermediary within the framework of the Knowledge-Based View (KBV) theory. Despite analyzed numerous scientific publications proving the increase in the efficiency of organizations from the implementation of generative AI, its use also creates epistemic, cognitive, and organizational vulnerabilities. Based on semi-structured interviews with specialists in German EIOs engaged in expert and consulting activities, we identified recurring themes of algorithmic opacity, loss of expert qualifications, and management failures that threaten the reliability of AI-influenced consulting services. Using Gioia’s methodology, a structural model of unsuccessful AI implementation has been developed, outlining three interrelated failure mechanisms: technological dysfunction, cognitive degradation, and institutional unpreparedness. Each of these dimensions corresponds to specific knowledge-related risks that threaten the integrity of expert knowledge production in consulting environments. The study also proposes multi-level mechanisms to mitigate the manifestations of the “dark side” of AI, including explainable AI techniques, critical thinking support programs, and formalized governance frameworks. This research contributes to a more balanced understanding of AI’s role in professional services, emphasizing that technological innovation must be accompanied by institutional safeguards and epistemic responsibility. By addressing the conditions under which AI implementation fails, the chapter outlines a pathway for more sustainable and ethically grounded integration of AI in knowledge-intensive B2B contexts.