Artificial intelligence (AI) is increasingly positioned as a key driver of digital transformation, enabling organizations to enhance performance, decision-making, innovation and stakeholder engagement. However, for public, hybrid, and mission-driven organizations, the critical issue is not only how AI improves efficiency, but how it contributes to value creation beyond profit (Moore, 1995; 2013; Battilana and Lee, 2014). This paper investigates how AI-driven academic spin-offs enact public value within digital knowledge ecosystems.
Drawing on public value theory (Moore, 1995; 2013), the sociology of valuation (Stark, 2009; Dussauge et al., 2015; Kornberger et al., 2015), knowledge management literature (Davenport and Prusak, 1998; Zack, 1999), and research on AI and entrepreneurship (Shepherd and Majchrzak, 2022; Fossen et al., 2024), the study conceptualizes public value as a dynamic process of (dis)aggregation, where multiple and conflicting value regimes coexist and are negotiated through evaluative practices. This allows us to explain not only the multiplicity of value generated by such organizations, but also the tensions, asymmetries, and exclusions through which that value comes into being.
The paper is based on an exploratory qualitative case study of Kebula S.r.l., an academic spin-off operating in data engineering and AI. Adopting a valuographic approach (Dussauge et al., 2015), the analysis examines how value is constructed, justified, and governed through everyday practices. Findings show that AI systems act as infrastructures of valuation that reorganize what counts as legitimate impact, redistributing visibility across economic, social, and knowledge domains. Public value emerges as a contested and relational accomplishment rather than a stable outcome. The paper contributes to knowledge management, public value theory, and AI-entrepreneurship literature by showing that intelligent transformation shapes not only how value is created, but also how it is made visible, accountable, and legitimate. Empirically, the case highlights how digital knowledge systems mediate innovation, learning, failure, and infrastructural flexibility in a hybrid university-based organization over time and across organizational contexts.