ABSTRACT This study extends absorptive capacity research by showing how corporate venture capital (CVC) investments enable corporate artificial intelligence (AI) adoption through collaboration pathways, delineated in four adoption archetypes that explain how heterogeneous AI knowledge is absorbed. Firms face increasing pressure to embed AI into their core operations to maintain competitiveness. Despite the growing wave of CVC investments in AI, existing research offers little insight into how corporations actually absorb and apply acquired AI knowledge, treating the transferred knowledge as homogenous. Building on organizational learning theory, this study examines how CVC programs enable corporates to learn from AI‐driven portfolio startups as a pathway to corporate AI adoption. Using a multiple case study design, we analyzed 14 CVC‐organized collaborations and conducted 36 interviews and one site visit with CVC, startup, and corporate executives across Europe. We complemented the cases with secondary data and 12 additional interviews for triangulation. From this analysis, we synthesized our findings into a three‐layer framework that introduces five principal dimensions shaping corporate AI adoption. Moreover, we determined archetypical patterns across these dimensions and derived four distinct adoption archetypes: (1) internal adoption, (2) customer‐facing adoption, (3) product integration, and (4) co‐creation. From a theoretical perspective, we contribute to absorptive capacity and CVC research by conceptualizing AI‐driven learning not as an isolated firm‐level activity, but as a relational capability emerging from the triangular interplay of CVC program, AI startup, and corporate. Practically, the study provides guidance on collaboration to achieve effective AI knowledge absorption, balancing explorative with exploitative corporate AI adoption outcomes.
Müller et al. (Fri,) studied this question.