These two episodes point to the same rupture. The question is no longer whether AI will reshape work. It will, and in many sectors already has. The question is whether the institutions driving that change have earned the right to be trusted with it — and whether the leaders responsible understand what trust actually requires.
The gaps — credibility, values
The anger at those graduation ceremonies was not irrational. It reflected something that survey data has since confirmed. Gallup’s research on Generation Z shows that negative sentiment about AI is rising even as usage remains consistent. They are not rejecting the technology. They are rejecting the terms on which it is being offered.
At the heart of that rejection is a credibility problem. When corporate leaders announce job cuts and attribute them to AI, they invite scrutiny of whether the explanation holds. In many cases, it does not. The six largest Wall Street banks cut 10,600 jobs in 2025, the most since 2016, yet few were candid about the relationship between those cuts and their simultaneous AI investments. Singapore’s three major banks shed nearly 2,800 jobs in the same period. None attributed this directly to AI.
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The more honest assessment came not from a regulator or a critic, but from Jensen Huang, CEO of Nvidia, whose chips power much of the world’s AI infrastructure. Speaking to CNA this month, Huang was blunt: “I think the narrative that connects AI to job loss for many of the CEOs that are doing it, it is just too lazy.” Earlier this year at Nvidia’s GTC conference, he described companies using AI to justify headcount reductions as “out of imagination”, i.e. organisations that, lacking the vision to grow, settle instead for a cheaper present.
Huang is right, but only partly. The reality is less about imagination than about pressure and arithmetic. Leaders know that meaningful AI investment requires significant capital. That capital has to come from somewhere, and workforce reduction is the most straightforward case to make to a board or to shareholders. It is a budgeting decision presented as a strategic vision. The efficiency argument — doing more with less — is easy to sell. The broader costs to people, to social cohesion, and to the longer-term talent pipeline are harder to quantify and easier to defer.
This matters because the values gap is at least as damaging as the credibility gap. How leaders speak about their people in moments of disruption reflects what they actually believe. Standard Chartered’s “lower-value human capital” and Prime Minister Lawrence Wong’s pledge at the May Day Rally earlier this month — “We may not be able to protect every job, but we will protect every worker” — sit at opposite ends of that spectrum. One treats people as a cost to be optimised. The other recognises an obligation that predates any technology.
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That obligation has a name: Governance. And at present, it is not keeping pace.
Getting AI governance right
Governance is failing at different levels and for different reasons, and it is worth being precise about where.
Regulators are making a genuine effort. Singapore’s National AI Strategy 2.0, the PDPC’s Model AI Governance Framework, and MAS sector guidance represent a serious attempt to build coherent oversight. The difficulty is structural: AI innovation moves faster than regulatory processes can reasonably follow. That places greater responsibility on organisations themselves.
Inside organisations, a related problem has taken hold: Shadow AI — the use of AI tools by employees outside sanctioned systems and without IT oversight. Surveys consistently put the proportion of employees doing this at between 49% and 80%, and recent research suggests senior decision-makers are among the heaviest users. The problem is not simply one of rogue behaviour at the margins. It reflects a deeper absence of organisation-wide AI governance where clear policies, consistent application, and leadership that models the conduct it expects. Where AI governance is weak, deployment runs ahead of control. The Diligent Institute’s APAC Governance Outlook 2026, published in partnership with the Singapore Institute of Directors, found that 57% of Asian organisations are already deploying AI. For many, the technology has arrived well ahead of the structures needed to govern it.
At board level, the challenge is of a different character. Many boards are managing competing demands of geopolitical risk, regulatory pressure, shareholder expectations and so on. AI governance does not yet command the attention it warrants. Directors whose formation and experience predate the digital era may find the pace and iterative nature of AI difficult to assess with confidence. The result, in many organisations, is that consequential technology decisions are being made below board level with limited oversight.
Leading from the top
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What changes this is leadership that treats governance as a cultural commitment rather than a compliance requirement. Some organisations are beginning to demonstrate what that looks like in practice. At the “Trust and AI: Navigating a World in Transition” Leaders Dialogue earlier this month, DBS Group CEO Tan Su Shan offered one practical guidance: Make sure your data is in order; create a safe space for learning; and bring your people with you. “As you incorporate AI into your operations, bring people — your customers and colleagues — with you because culture starts from the top,” she said. The bank has also maintained its graduate intake, with plans to hire more than 500 young Singaporean recruits in 2026.
This is one example. The broader picture remains uneven. Asia-Pacific AI spend is projected to reach US$370 billion ($473.54 billion) by 2029, from US$73 billion in 2024. At that scale, the gap between policy and practice is not merely an organisational problem. It is where public trust is won or lost.
Rebuilding the human compact
Not everyone who spoke about AI at a graduation ceremony this month was booed. Steve Wozniak, co-founder of Apple, drew applause with a simple observation: “You all have AI — Actual Intelligence.” He described AI as engineers’ unfinished attempt to imitate the human brain. The crowd’s response was not coincidental. Wozniak earned it by placing the human above the technology, rather than subordinating people to machines.
Pope Leo XIV made a similar argument at greater length and with greater authority in his encyclical Magnifica Humanitas, released this week. AI systems, he wrote, merely imitate certain functions of human intelligence, often surpassing it in speed and computation, but their power remains entirely tied to data processing. “So-called artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships and do not know from within what love, work, friendship or responsibility mean,” he reminded. The Pope drew a deliberate parallel to Rerum Novarum, Leo XIII’s 1891 encyclical on workers’ rights and the social consequences of industrialisation. The questions of dignity, labour and the common good that preoccupied the Church in 1891 have not been resolved. They have been renewed.
Singapore’s compact
Singapore’s position in this debate is significant. The country’s brand has been built on integrity and efficiency. Both are now being tested simultaneously. The integrity test is whether Singapore’s commitment, that AI must benefit people and deliver prosperity broadly, holds when the economics of adoption push in a different direction. The efficiency test is whether the governance architecture being built is capable of keeping pace with the technology it is meant to oversee.
Those two tests are connected. Efficiency without integrity produces the kind of governance failure that erodes public trust. Integrity without efficiency produces frameworks that look good on paper but struggle in practice. Singapore has navigated this balance at various junctures in its nation-building history. The challenge now is to do so again, at a speed and scale that neither policymakers nor businesses have previously encountered.
The graduates who booed were registering something real, as was the backlash when a global bank’s CEO reduced his workforce to an accounting entry. Trust is lost when people feel they are not valued by the organisations they work for, or by the leaders who speak on their behalf.
The human compact that AI is now testing is not a sentimental idea. It is a practical foundation. The organisations and societies that understand this and govern accordingly will do right for our children and future generations.
Kay Pang is a Singapore board director and business lawyer specialising in technology law and AI governance. She has advised boards and senior management on AI adoption and governance, contributed to World Economic Forum white papers on the responsible use of technology, and speaks regularly on AI law and ethics
