INTEGRATION IS KEY
When it comes to AI, the hard part is not experimentation. It is integration.
That means addressing less glamorous constraints – fragmented data systems, limited interoperability, unclear procurement pathways and uncertainty around governance. Common architecture is what will turn AI from a collection of promising pilots into systemic innovation.
Prime Minister Lawrence Wong acknowledged that end-to-end AI transformation demands shared foundations, not piecemeal initiatives. That logic is central to proposals such as the Networks for Humanity Research Institute at the National University of Singapore (NUS), which seeks to establish open standards so financial institutions can modernise collectively, rather than in costly and incompatible silos.
In finance, in particular, the integration challenge is becoming structural. As AI evolves from analytics tools into autonomous agents allocating capital, executing compliance and interacting with markets, the underlying infrastructure must adapt. In this case, programmable, quantum-secure and interoperable systems will be prerequisites for stability in AI-driven markets.
TURNING AI ACCESS INTO PRODUCTIVITY GROWTH
The Budget also includes measures to spur adoption, including six months of free access to premium AI tools for Singaporeans who take up selected courses, alongside productivity support for firms.
These are sensible entry points that reduce friction and encourage experimentation, but access to tools does not automatically translate into productivity. The real gains come when organisations rethink workflows, redesign processes and integrate AI into core operations.
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