When corporate efficiency becomes an economic risk

MY CAREER in business transformation and sustainability has taught me that what makes sense for one company may not benefit the wider economy.

Environmental sustainability offers a lesson: Businesses could profit while society bore environmental costs till the accumulated risks demanded attention from governments, investors and boards.

Artificial intelligence is creating a different version of this dilemma. Beyond disappearing jobs lies a deeper risk: What happens if AI-enabled capitalism excels at creating wealth but not at distributing economic opportunity?

A “slow-moving tsunami”

For a company, AI promises automation, lower costs and greater productivity. Imagine many companies pursuing this simultaneously.

If workforce displacement outpaces new opportunities, what happens to household incomes, consumer spending and the markets that businesses depend upon? After all, employees are also consumers.

Herein lies the paradox: What is rational for individual companies may become problematic when pursued collectively.

Technology has created industries, lowered prices and generated jobs. AI could do the same, but new job opportunities may require different skills or arise elsewhere.

In a widely reported statement in 2025, DBS said AI could reduce the need to renew about 4,000 temporary and contract roles across its 19 markets over three years. The bank added that around 1,000 AI-related roles would be created.

Since then, DBS has introduced new measures to help its workforce navigate these changes.

Beyond the finance industry, the wider economic risk is a prolonged transition in which productivity grows faster than broad-based economic participation.

At the recent International Monetary Fund (IMF)-World Bank meetings in Thailand, IMF managing director Kristalina Georgieva described AI’s impact on jobs and public finance as a “slow-moving tsunami”.

More “socialism” in an AI-driven economy?

Capitalism creates innovation and wealth, yet depends on people having the means to participate in the economy.

If AI concentrates returns among owners of technology and capital, and those best equipped to harness it, while weakening opportunities for others, inequality could become an economic vulnerability.

Could capitalism’s greatest productivity engine eventually require stronger mechanisms for sharing its gains?

Governments are already confronting this question, albeit through different approaches.

In its April 2026 response to a parliamentary AI inquiry, the Australian government recognised that workers should share AI gains through wages, equity, skills and employment security.

Cited research estimated that 4 per cent of workers were in occupations with high near-term automation exposure. This was not a job-loss forecast, but it reinforced the case for early preparation.

China offers another example. The authorities in the socialist market economy have reportedly cautioned major employers against AI-driven job cuts. In May 2026, The Guardian reported on a Chinese court ruling against an AI-related dismissal where the employer failed to meet its legal obligations.

Different economic systems are recognising a common concern: Productivity gains must sustain economic participation, or the markets that businesses depend on could become less resilient.

Singapore’s opportunity to lead an “AI-just transition”

Singapore has long combined openness to investment and competition with a strong emphasis on human capital and tripartite cooperation. The Skills and Workforce Development Agency, integrating skills and employment functions, provides a useful foundation.

But AI presents a challenge beyond reskilling: We could become increasingly effective at training people for an economy that needs fewer of them in traditional structures of employment.

Training matters, but so do opportunities to apply new skills. Businesses must redesign work, create jobs and new forms of value, rather than relying solely on the government to improve workers’ employability.

Amid concerns that AI is removing the “first rung” of the career ladder, banks such as DBS and UOB announced plans in 2026 to recruit 500 and 1,000 young people, respectively. These decisions signal the importance of developing the future workforce, not just meeting current staffing needs.

Returning to the environmental sustainability example, climate transition risk asks businesses to consider the broader economic consequences of moving towards a lower-carbon economy.

A “climate-just transition” considers how people and communities share these costs and benefits.

The move towards an AI-intensive economy warrants a similar, yet distinct, governance lens.

Companies may capture automation’s benefits while workers, communities and governments bear some costs of displacement, retraining and income insecurity.

AI can also lower prices and improve services, but the issue is how benefits and transition costs are distributed.

We need an “AI-just transition” – one that proactively manages who gains, who bears the costs and whether displaced capabilities find new productive uses. The AI transition risk is that poorly managed workforce change creates vulnerabilities beyond any single company’s balance sheet.

Corporate governance questions

Boards are skilled at assessing returns on invested capital.

But do they examine returns from sustaining human capital? Are AI investments creating new services, markets and higher-value roles, or mainly removing labour costs?

Are gains being reinvested in workforce adaptability alongside shareholder returns?

Australia’s Commonwealth Bank offers a telling example. In 2025, it reversed 45 AI-related call-centre redundancies after acknowledging flaws in its assessment of staffing needs.

In 2026, it committed about A$90 million (US$63.1 million) over three years to skills development and career-transition support.

Ahead of its initial public offering, Anthropic recently pledged 5 per cent of its shares to a new public-benefit fund aimed at supporting the broader public good, including addressing AI-driven worker displacement.

This follows the technology company’s June 2026 commitment of US$200 million to research into managing AI’s economic and labour-market disruption.

While these moves may be dismissed by sceptics as an IPO publicity exercise, they may also signal emerging recognition that companies benefiting from AI-driven wealth creation have a responsibility to help manage its wider social and economic consequences – an early step towards an AI-just transition.

These separate decisions illustrate the challenge for boards: balancing immediate efficiency with investment in future human capabilities.

No company can solve economy-wide inequality, and none should retain redundant jobs for its own sake. But eliminating work that no longer creates value is different from failing to explore how people might create value differently across the new economy.

Beyond productivity

Environmental sustainability challenged the assumption that growth could disregard the natural resources on which it depends. AI may challenge the assumption that productivity gains will translate to widely shared prosperity.

Sustainable human economic participation deserves a place in how boards think about long-term resilience and value creation.

An economy can become extraordinarily efficient at creating wealth yet increasingly fragile if too few people have the means to participate in it. That may be AI’s greatest capitalism paradox – and a governance question worth confronting now.

The writer is the founder of Human Meridian Advisory, a committee member of National Council of Social Service and former group vice-president of corporate sustainability at Singtel. He is currently based in Sydney. AI tools were used in structuring and trimming the article before submission. The writer remains fully accountable for the commentary’s accuracy, originality and final form.