Everyone can build with AI now. Almost nobody can see what’s coming

In just one week, Singapore's central bank allocated SG$220 million over three years to fintech and AI infrastructure, while Southeast Asian native AI startups raised a combined US$4.1 billion in the same period. This showcases a rapid rise in AI technology adoption, but it also reveals a significant disparity in information access and trust.

One startup, Kling AI, absorbed 68% of the total funding, leaving the rest of the region with only US$1.3 billion spread across 23 deals. Meanwhile, no dedicated Southeast Asia private equity fund closed any deals in the first half of 2026, marking the worst performance on record. On the other hand, three pan-Asian mega-funds raised a combined US$39.2 billion, with no requirement to invest specifically in this region.

With AI coding tools becoming more accessible, 84% of users have no technical background. Lovable, a company founded by a non-technical individual, achieved US$400 million in annualized revenue within a year, four times its revenue from eight months prior. The author, who also has no technical background, built their first product using AI during their ambulance shifts.

While the accessibility of AI tools is undeniably empowering, the timing gap between information access and trust remains significant. Institutional investors enjoy a substantial lead time, while consumers struggle to determine the trustworthiness of AI systems. Despite 65% of US consumers trusting AI to compare prices, only 14% trust it to place orders.

The author emphasizes the importance of evidence and timestamped claims when building AI-driven products. While AI has made building software more accessible, it has also uncovered critical security vulnerabilities. The real gap lies in building auditable infrastructure that provides meaningful advantages to ordinary users, rather than merely developing flashy features. The future belongs to those who can deliver reliable, trustworthy AI solutions.