Open source has repeatedly reshaped technology markets by lowering barriers to entry, reducing rent extraction, and enabling innovation beyond what proprietary licensing allows. But open source code alone doesn’t guarantee competition, “sovereingnty,” or decentralization. A project can also be open while the surrounding market remains concentrated in cloud, compute, distribution, data, or complementary services, having little ultimate impact on the incentives of the actors in the market or the competitive dynamics. These tensions are especially visible in AI, where “open weights” are often treated as synonymous with open source even when other ingredients needed to study, reproduce, or operate the system remain unavailable. This panel examines open source as a market-shaping tool, asking what complementary conditions (architecture, protocols, procurement, governance) make it effective, and what outcomes are actually feasible in AI markets.

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