This study proposes an integrative framework to explain how generative AI firms organize and adapt governance architectures to temporarily contain the conflicting logics of ethics, profit, stakeholder inclusion and technological autonomy.
Drawing on paradox theory, the study employs a multiple-case design analyzing ten frontier GenAI firms: OpenAI, Anthropic, Google DeepMind, Mistral AI, xAI, Inflection AI, Aleph Alpha, DeepSeek, Meta and Stability AI. A novel three-dimensional analytical framework operationalizes governance tensions through systematic documentary coding and comparative analysis.
The results identify five governance archetypes in GenAI firms: Contested Equilibrium, Institutionalized Ambiguity, Amoral Drift, Gilded Cage and the Founder’s Paradox. These archetypes demonstrate how attempts to incorporate ethics and accountability can create new forms of opacity, dependency and concentration of power. We interpret this recurring pattern as a form of “institutional paradoxification”, namely a theory-building construct that captures how governance mechanisms may, under certain conditions, amplify rather than resolve the tensions they are intended to contain.
This study extends paradox theory into the governance of frontier GenAI firms by showing that the “dark side” of AI governance is not reducible to isolated ethical failures but emerges as an institutional outcome of competing governance logics. In doing so, it shifts attention from technical risks alone to the organizational architectures through which responsibility, control and legitimacy are continuously negotiated.
