AIgemony
AIgemony extends Gramsci and Mouffe's concept of hegemony into the specific domain of AI governance. It names the process by which AI's development and deployment concentrate decision-making authority, infrastructure control, and economic returns in a small number of corporations and geographies, while the concentration itself is presented as the natural outcome of market competition and technical innovation rather than as a contestable political arrangement. The power is real; its presentation as neutral is the hegemonic operation. 'Inadequate public awareness, combined with regulatory and legal framework lags, and the exploitation of such vulnerability by influential actors, could intensify inequalities to unprecedented levels' — a formulation that echoes Mouffe's analysis of how hegemonic operations succeed precisely because they are not recognized as political.
In the AI Story
The concept illuminates specific structural features of the contemporary AI landscape that the stewardship framework obscures. The concentration of frontier model training in a handful of American corporations. The concentration of compute infrastructure in a small number of hyperscale cloud providers. The concentration of training-data ownership among platforms that acquired data before the political significance of that ownership was widely understood. Each of these concentrations can be defended on efficiency grounds. None of them was democratically chosen. The defense on efficiency grounds is the characteristic hegemonic move — converting a political arrangement into a technical necessity.
The Buyl et al. study provides empirical grounding: different LLMs from different regions reflect systematically different ideological positions, yet the emerging regulatory discourse often treats ideological neutrality as the goal. The pursuit of neutrality is itself an AIgemonic operation — it conceals the choices embedded in every model behind the appearance of technical objectivity.
The concept does not propose that AI development should stop. It proposes that the concentrations embedded in current AI development should be recognized as political arrangements subject to democratic contestation — through antitrust enforcement, data governance reform, infrastructure diversification, and the creation of institutional mechanisms through which affected populations can influence the terms of their participation in AI-mediated economic and social life.
Critics of the concept argue that it overstates the coherence of AI-industry interests and understates the genuine technical difficulties that constrain alternative development trajectories. The Mouffean response: the recognition of genuine constraints does not eliminate the political character of choices made within them. Every constraint leaves a space of alternatives; the question is who decides which alternative prevails.
Origin
Introduced in scholarly literature applying the Laclau-Mouffe hegemony framework to AI governance, with particular development in work connecting algorithmic systems to democratic theory. The specific coinage builds on Mouffe's conceptual vocabulary while naming the novel AI-specific manifestation.
Key Ideas
Concentration presented as neutrality. The signature AIgemonic move is framing technical arrangements as beyond political contest.
Regulatory lag is politically productive. The gap between capability and governance benefits those whose interests the current arrangement serves.
Neutrality is hegemonic. The pursuit of ideological neutrality in AI systems is itself a political operation.
Contestation, not abolition. The response is democratic challenge to specific arrangements, not rejection of AI development.
Appears in the Orange Pill Cycle
Further reading
- Ernesto Laclau and Chantal Mouffe, Hegemony and Socialist Strategy (Verso, 1985)
- Kate Crawford, Atlas of AI (Yale, 2021)
- Maarten Buyl et al., 'Large Language Models Reflect the Ideology of their Creators' (Nature Machine Intelligence, 2025)