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Singapore faces AI’s challenge early, and it’s about the data you can prove

Governance that lives only in policy documents fails in production; it must be embedded in how data is collected, shared and used

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    • The questions that stall AI roll-outs are practical, not philosophical: Where did this data come from? What rights apply? Can we trace an output back to its inputs when something goes wrong?
    • The questions that stall AI roll-outs are practical, not philosophical: Where did this data come from? What rights apply? Can we trace an output back to its inputs when something goes wrong? IMAGE: PIXABAY

    Zac Cheah

    Published Thu, Apr 2, 2026 · 07:00 AM

    DATA trust is not a new issue – companies have been grappling with it for years. What’s new is the urgency: as generative artificial intelligence (AI) moves into production, knowing where your data came from, whether you are allowed to use it, and whether you can explain your AI’s outputs are no longer negotiable.

    President Tharman Shanmugaratnam recently said Singapore will face AI’s challenge sooner than many economies, and that the deeper test is ensuring AI’s productivity gains are distributed “up and down the workforce”.

    That urgency is reinforced by Budget 2026’s push to scale AI nationally, including a new National AI Council chaired by Prime Minister Lawrence Wong, with missions spanning manufacturing, connectivity, finance and healthcare.

    Artificial IntelligenceData governanceAI governanceSingapore economyAsean

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