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As the AI economy accelerates, experts warn that open research infrastructures face increasing strains from automation and data monopolisation, urging a shift towards commons-based governance to ensure sustainable and equitable access.<\/p>\n<\/div>\n
Invest in Open Infrastructure says the accelerating AI economy is putting fresh pressure on the open collections that underpin research, public knowledge and digital access. In a new landscape scan released through its BRIDGE project, the organisation argues that archives, journals, repositories, preprint servers and knowledge graphs have become part of a shared digital commons that is increasingly valuable to machine learning systems, even as the institutions that maintain it struggle with rising costs and operational strain.<\/p>\n
The group\u2019s assessment comes at a moment when open science is widely framed as a route to broader participation and fairer access to knowledge. UNESCO\u2019s Recommendation on Open Science describes the model as an international standard for making research more accessible, inclusive and sustainable, while recent academic work has also noted that open access can expand reuse, replication and collaboration. Yet scholars and commentators have warned that openness can carry its own paradoxes, including the risk of new dependencies and deeper inequalities when powerful actors are better placed to extract value from shared resources.<\/p>\n
According to Invest in Open Infrastructure, the pressure is already visible in traffic patterns and submission workflows. Automated bots can overwhelm servers, drive up bandwidth bills and even cause outages, while AI-generated material can swamp curation systems built on limited staff time and community labour. The report also questions whether current defences are sufficient. Technical barriers, legal remedies and market-based licensing all have limits, and stricter access controls may simply push data consolidation further towards the largest companies.<\/p>\n
The organisation says a more durable answer may lie in commons-based governance, built on reciprocal norms and a clearer sense of shared interest between AI developers and the stewards of open collections. It argues that companies have practical reasons to help preserve reliable open sources, from training data quality to legal and reputational risk. The harder question is whether that enlightened self-interest can outperform the more adversarial approaches already tried. Invest in Open Infrastructure says the next step is to treat curators and users of open collections as co-stewards of the system, and to develop partnership models that align commercial demand with the long-term health of the digital commons.<\/p>\n
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