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Chairman Sohn Projects $9 Trillion Investment to Reach Artificial Superintelligence in a Decade
On 15 June 2026, Chairman Sohn of a leading South Korean conglomerate announced that artificial general intelligence (AGI) will soon outstrip human brains, and that the next frontier will be artificial superintelligence (ASI). He estimated that building an ASI system would require about $9 trillion—roughly five percent of global GDP—and could be achieved within ten years.
Sohn’s remarks arrive as a wave of high‑profile AI funding pours into the sector. He noted that AGI, defined as a system capable of self‑learning and reasoning across diverse tasks, is expected to materialise in two to three years at the current pace of development. “At the ASI level, human intelligence will look almost like a goldfish,” he said, underscoring the vast gulf between human and superhuman cognition.
Unlike the narrow AI that powers today’s chatbots, image generators, and recommendation engines, AGI would generalise knowledge, transfer skills between domains, and solve novel problems without task‑specific re‑programming. While analysts have long debated the timeline, the rapid progress of large language models and multimodal systems has led many to believe a generalist system could emerge soon.
ASI is defined as an intelligence that far exceeds the best human minds in virtually all domains. According to Sohn, an ASI system would be about 10 000 times smarter than an average human, rendering human cognition comparable to a goldfish. He also pointed out that the combined intelligence of all humans is tens of thousands of times greater than that of a single human, illustrating the scale of the challenge.
The $9 trillion figure reflects the computing power and data required for an ASI system. Current AI hardware investments by companies such as Nvidia, Google, Meta, and Amazon have already reached multi‑billion‑dollar levels, and the industry is expanding its focus to include specialised neural‑processing units and custom ASICs. Sohn added that the investment could be recovered in a single year if an ASI system were realised, suggesting a substantial economic upside.
The prospect of ASI raises questions about alignment, safety and regulation. While the article does not detail specific policy responses, it echoes broader concerns raised by researchers and policymakers about the potential risks of superintelligent systems. The translation of the original Korean article by GripLabs Mingo AI indicates that the comments were reported in a mainstream Korean outlet.
At present, no company has announced a concrete roadmap to ASI, and the timeline remains speculative. However, the combination of aggressive capital deployment, advances in model scaling and the growing availability of high‑performance hardware suggests that the industry is preparing for a future in which AGI and, eventually, ASI could become operational.
In summary, Chairman Sohn’s statements highlight a belief that AGI will arrive within a few years and that ASI could follow within a decade, requiring a $9 trillion investment. The claim underscores the scale of resources needed and the potential economic impact, while leaving open questions about safety, governance and the pace of technological progress.
Sohn’s remarks arrive as a wave of high‑profile AI funding pours into the sector. He noted that AGI, defined as a system capable of self‑learning and reasoning across diverse tasks, is expected to materialise in two to three years at the current pace of development. “At the ASI level, human intelligence will look almost like a goldfish,” he said, underscoring the vast gulf between human and superhuman cognition.
Unlike the narrow AI that powers today’s chatbots, image generators, and recommendation engines, AGI would generalise knowledge, transfer skills between domains, and solve novel problems without task‑specific re‑programming. While analysts have long debated the timeline, the rapid progress of large language models and multimodal systems has led many to believe a generalist system could emerge soon.
ASI is defined as an intelligence that far exceeds the best human minds in virtually all domains. According to Sohn, an ASI system would be about 10 000 times smarter than an average human, rendering human cognition comparable to a goldfish. He also pointed out that the combined intelligence of all humans is tens of thousands of times greater than that of a single human, illustrating the scale of the challenge.
The $9 trillion figure reflects the computing power and data required for an ASI system. Current AI hardware investments by companies such as Nvidia, Google, Meta, and Amazon have already reached multi‑billion‑dollar levels, and the industry is expanding its focus to include specialised neural‑processing units and custom ASICs. Sohn added that the investment could be recovered in a single year if an ASI system were realised, suggesting a substantial economic upside.
The prospect of ASI raises questions about alignment, safety and regulation. While the article does not detail specific policy responses, it echoes broader concerns raised by researchers and policymakers about the potential risks of superintelligent systems. The translation of the original Korean article by GripLabs Mingo AI indicates that the comments were reported in a mainstream Korean outlet.
At present, no company has announced a concrete roadmap to ASI, and the timeline remains speculative. However, the combination of aggressive capital deployment, advances in model scaling and the growing availability of high‑performance hardware suggests that the industry is preparing for a future in which AGI and, eventually, ASI could become operational.
In summary, Chairman Sohn’s statements highlight a belief that AGI will arrive within a few years and that ASI could follow within a decade, requiring a $9 trillion investment. The claim underscores the scale of resources needed and the potential economic impact, while leaving open questions about safety, governance and the pace of technological progress.
