
Toward AI Governance That Works: Examining the Building Blocks of AI and the Impacts
As governments and international bodies race to establish guardrails for AI, most of the global agenda still focuses on managing what AI systems produce—their outputs. This article argues that such an approach is incomplete. The real foundations of safe, rights-respecting, and equitable AI lie upstream in how data is collected, governed, shared, and stewarded. Without integrating mature data governance practices, such as data stewardship and data commons, into AI governance, countries will struggle to protect fundamental rights or ensure that AI’s economic and social benefits are distributed fairly. A future-ready AI governance framework must therefore unite input and output governance into a single, coherent system.













