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Paper short abstract

This paper examines Hugging Face's evolution to show that as AI development becomes increasingly industrialised, infrastructural intermediaries play an increasingly crucial role in shaping the governance, economics, and politics of AI.

Paper long abstract

This paper examines Hugging Face’s (HF) evolution from a machine-learning library into an infrastructural intermediary within the contemporary AI ecosystem. Originally launched as a chatbot application and natural language processing library, it now operates as a "hub": a repository, infrastructure provider, standard-setter, marketplace operator, and participant in AI governance and ethics. Rather than presenting this trajectory as a linear story of growth, the paper interrogates the political-economic forces that have shaped HF’s development and the tensions that emerge from its dual positioning as both an advocate of “open and ethical AI” and a commercially embedded platform.

Employing a mixed-methods approach rooted in critical data and AI studies, the research analyses a longitudinal corpus of HF’s archival webpages, terms of service and pricing (2016–2026), alongside a systematic review of its organisational partnerships and infrastructural integrations with cloud hyperscalers and hardware manufacturers. This approach enables a decade-long analysis of the platform’s shifting roles and ecosystem position.

We argue that in this trajectory, the model functions as a central organising unit through which AI is built, circulated, and governed, and this centrality is inseparable from an ongoing assetization (Birch & Muniesa 2020) of machine learning models. The case of Hugging Face thus also shows how as AI development becomes increasingly industrialised, infrastructural intermediaries play an increasingly crucial role in shaping the governance, economics, and politics of AI.