Greater collaboration required to realise the full potential of technology, says US Under Secretary
By Hanna Kum
At the ATxSummit on May 21, Jacob Helberg highlighted Southeast Asia’s secure supply chains, manufacturing capabilities, and large youth population as key assets for mutually-beneficial collaboration with the US.
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Photo of conversation between US Under Secretary Jacob Helberg and Singapore's Ministry of Digital Development and Information's Permanent Secretary, Chng Kai Fong, taken at ATxSummit 2026. Image: Infocomm Media Development Authority.
In its race for supremacy in artificial intelligence (AI), the US is betting its strategy on a private sector-led charge to unlock the entire AI supply chain, from large language models (LLMs), to chips, energy and associated products.
Noting that this approach was very different from one which favoured large state-run megaprojects, the US’ Under Secretary Jacob Helberg said this would bind US partners like Singapore, the Philippines, Vietnam, and Malaysia into a shared, positive‑sum tech and security ecosystem.
Speaking at a fireside chat with Singapore’s Ministry of Digital Development and Information (MDDI)’s Permanent Secretary, Chng Kai Fong, at ATxSummit 2026, on May 21, Helberg rejected the “doom-laden” narratives of mass job losses due to AI adoption.
He pointed to the growth of AI as comparable to the First Industrial Revolution. In this context, he praised Singapore as proof that automation and low unemployment can coexist.
Leaning on one’s comparative advantage
Helberg said that the US was leaning into its comparative advantage: private‑sector companies that built platforms others wanted to use.
Southeast Asian nations face a strategic choice when it comes to AI development.
They could attempt to build their own complete AI ecosystems from the ground up — covering everything from chips to frontier models — under the claim of “digital sovereignty”.
But this risks wasting limited resources on fragmented efforts.
Alternatively, they could focus on channeling their resources into what sits above that base layer, while treating American and allied AI platforms as common infrastructure.
What sits above that base layer could include harnessing local data, developing homegrown applications, and cultivating industries that leverage these foundations.
He noted that that trying to replicate everything in-house amounted to “competing for the last technology, not the next one.”
Leveraging other countries’ expertise to benefit mutually
With reference to President Trump’s speech on the US winning the global AI race, Helberg outlined three pillars the country must secure to achieve that goal: resilient supply chains, dominant market share, and technological innovation.
“None of these matters if we don’t secure our supply chains, because our supply chains are the bedrock of production of intelligence production,” he noted, referencing Southeast Asia as a testbed for supply chain efforts.
He cited the Philippines, Vietnam and Malaysia’s possession of “deep manufacturing ecosystems” and “unique manufacturing capabilities” which the US could leverage on.
Singapore was also mentioned as having “one of the most impressive port logistics infrastructures in the world” and being responsible for the production of 10 per cent of the world’s semiconductors — a country well-positioned to complement the US.
Helberg stressed that in this partnership, Southeast Asian countries would not merely be low-cost factories, but co-creators of value.
For example, the US and the Philippines had recently agreed on a designated Economic Security Zone in the Philippines to lock in the production of inputs vital to US and global supply chains.
Southeast Asia's large young population positions the region as fertile ground for AI adoption, driving strong uptake of new digital tools and platforms.
“We think that making sure that they have access to those tools will actually allow them to build the next wave of companies and businesses in order to build up their own economies,” he said, arguing for the mutually beneficial effects of this collaboration.
A product-centric approach to foreign policy
In response to Chng’s question about what success for the US strategy looks like, Helberg shared about his product-centric approach to foreign policy.
This referred to prioritising the roll out of concrete products that their partners could adopt and use, rather than just generally announcing policies for collaboration.
It could include the exporting of AI stacks, or securing supply chains in other countries, as mentioned above.
“Products are a lot more measurable, so when you roll out products, you can actually measure the results and the impact and KPIs for that product,” he explained.
It was his hope that in a year’s time, there would be a visible movement shown from the data on the adoption of these products.
These partnerships would see countries contributing their unique capabilities to complement each other in this AI race, ultimately reinforcing “positive-sum thinking” that was the core feature of this system.
Seeing the possibility of economic growth in AI development
Helberg also urged the shifting of mindset regarding AI, framing it as a growth-accelerating technology that was comparable to the effect of the First Industrial Revolution.
Past technological shifts had resulted in economies moving from a GDP growth rate of zero to one per cent in agrarian societies, to one to three per cent when industrialisation was integrated into the economy.
“And now I think with the AI revolution, there's a very good chance that we're starting to see an acceleration in AI-led economies,” Helberg said.
He said that this reflected what was ultimately “at stake in this race” — not a battle for the next technology, but a shift in economic growth.
Chng then asked him to elaborate on the role of governments to harness AI for productivity gains, noting that Helberg seemed “more optimistic about AI and jobs than most”.
Helberg referred to the unemployment argument where AI would generate immense productivity, and this productivity would lead to mass jobs dislocation.
“Unemployment today in the US is still around 4 per cent... still really, really low,” he said.
In fact, Helberg continued, Singapore was an example of integrating AI extensively into everyday life while maintaining low unemployment rate.
“I think it's such a great example that shows how those two things can actually coexist incredibly well, and actually reinforce each other.”