A policy analysis using India’s experience — processing ~20 billion transactions monthly — argues that institutional readiness, not just model quality, determines whether AI drives productivity at scale. The piece emphasizes that institutions and organizations must change rules, incentives and workflows to absorb AI, citing Aadhaar and other national systems as enablers of wide adoption. For universities, the takeaway is practical: building or licensing AI models is only the start. Successful campus deployments require updated governance, workforce reskilling, procurement policies that define accountability, and metrics tied to learning outcomes. The analysis recommends investment in data infrastructure, legal frameworks for cross-border datasets, and internal incentives to align faculty and administrative stakeholders around adoption.