When China’s State Council issued its “AI Plus” guideline on August 26, 2025, it set a target no other major economy has dared to publish: a 90 percent penetration rate for new-generation intelligent terminals and AI agents by 2030, with 70 percent already by 2027. The document framed AI as the next general-purpose technology, comparable to electricity, and identified six sectors where it must dominate: science and technology, industry, consumption, public well-being, governance, and global cooperation.
By 2030, China expects AI to be a primary growth engine; by 2035, an “intelligent economy and society” sufficient to underpin what Xi Jinping calls socialist modernization. Trivium China’s analysis noted that no Chinese policy, including the 2025 guideline, defined a unit of measurement for AI’s contribution to GDP, but the political signal is clear: AI is now in the same tier as the 2015 “Internet Plus” initiative that produced Meituan, DiDi, and the cashless economy. Beijing is willing to legislate AI adoption, not just subsidize it.
The implication for Europe, which is still debating compliance, is unflattering. And China is not the only Asian country powering up to embrace AI.
South Korea has gone furthest in formalizing its approach. The Framework Act on the Development of Artificial Intelligence, known as the AI Basic Act, took effect on January 22, 2026, making South Korea the first country to have a comprehensive AI statute that combines governance, industrial policy, and risk management into a single law.
The 2026 national budget tripled AI spending to 10.1 trillion won (about $6.94 billion), and President Lee Jae-myung has pledged to make South Korea an “AI G3” power by 2030. Nvidia’s Jensen Huang announced in October 2025 that 260,000 Blackwell GPUs will be deployed across Samsung, SK, Hyundai, Naver, and government infrastructure. South Korea has chosen a path that the EU recognizes (regulate first) but paired it with capital deployment that the EU has not matched.
Japan presents the most interesting contrast. Generative AI usage among the Japanese public stood at 26.7 percent in 2024, compared with 68.8 percent in the United States and 81.2 percent in China, according to the Ministry of Internal Affairs and Communications’ 2025 White Paper. The Japan Times reported in December 2025 that Tokyo’s draft basic AI program targets a public utilization rate of 50 percent, eventually 80 percent, alongside roughly 1 trillion yen (about $6.4 billion) in private R&D investment. NTT alone is committing $59 billion through 2027, and SoftBank has tied itself to OpenAI’s Stargate project with over $40 billion in commitments. Japan is late and knows it – now Tokyo is buying its way back.
India is running a different play: compute as a public utility. The IndiaAI Mission, approved in March 2024 with an outlay of over 103.7 million rupees ($1.24 billion) outlay, has already deployed over 38,000 GPUs (including 1,050 Google Trillium TPUs), well over the initial target of 10,000. Startups and academics can access H100-class compute at 65 rupees (about $0.72) per hour, the cheapest subsidized rate in the world.
Minister Ashwini Vaishnaw said in February 2026 that committed AI-related investment in India already stands at $90 billion, with projections that it will exceed $400 billion across the AI stack within two years. The Indian government projects AI will add $1.7 trillion to GDP by 2035.
Singapore is the precision case. Its National AI Strategy 2.0 (launched 2023, with a refreshed 10-priority Update in May 2026) tripled the AI talent pool target to 15,000 from 4,500 and anchored over 70 corporate AI Centers of Excellence on the island. According to the IMDA’s Singapore Digital Economy Report, AI adoption in small and medium-sized enterprises (SME) jumped from 4.2 percent in 2023 to 14.5 percent in 2024, and non-SME adoption from 44 percent to 62.5 percent in the same year. The new National AI Impact Program aims to onboard 10,000 enterprises over three years.
Singapore is small enough to measure what it deploys, which is precisely why it is outpacing larger economies in per-capita adoption. The table below summarizes how the six countries stack up on targets, current adoption, and capital commitments.
Set against this, the EU’s Digital Decade looks tepid. The headline target is 75 percent of EU enterprises using cloud, AI, or big data by 2030. Eurostat’s 2025 data put cloud adoption at 39 percent, data analytics at 33.3 percent, and AI at 13.5 percent across EU enterprises. Basic digital skills are at 55.6 percent among adults, against an 80 percent target.
The Commission’s own June 2025 State of the Digital Decade report conceded that at the current pace, the bloc will not hit the 2030 goals until around 2040. An AWS-commissioned analysis by Public First found that the EU is on track to unlock only 1.3 trillion euros of the projected digital value by 2030, leaving up to 1.5 trillion euros on the table. The EU is regulating an economy it has not yet built.
The EU has world-class regulation (the AI Act), serious chip ambitions (20 percent of global production value by 2030, up from 10.5 percent in 2024), and almost nothing on the demand side that compares with what Asian governments are pushing through their economies. China publicly set a 90 percent penetration target and history suggests Beijing will use industrial policy to hit it. South Korea legislated a national AI architecture and tripled its budget in a single year. India is treating GPUs like public roads. Singapore measures adoption by enterprise and acts on the result. Japan, embarrassingly behind on usage rates, is throwing tens of billions at the gap.
Brussels is mistaking the rulebook for the game. If the Digital Decade ends in 2030 with EU AI adoption at 30 to 40 percent while China sits at 90 percent, no amount of well-drafted compliance will close that gap, and the productivity dividend will accrue elsewhere.
