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Policy, Infrastructure, Ecosystem: The Three-Layer Framework Behind Fast AI Growth

  • Aug 11
  • 3 min read

There's a moment in every fast-moving industry when everyone asks the same question: how did some players get so far ahead, so fast? At GoTech World 2025, Clas Neumann, SVP and Head of the Global SAP Labs Network, offered an answer that had nothing to do with luck. It came down to something almost unfashionable in a hype-driven industry: a plan.


The country he was describing is China and the numbers back up the scale of the ambition. Back in 2017, China's State Council set a target of turning AI into a trillion-yuan (roughly $150 billion) domestic industry by 2030, with related industries worth ten times that, according to OECD.AI's policy tracker (2025). Stanford's DigiChina project, which translated the original plan in full, notes it was structured in three explicit steps: competitive with the world by 2020, world-leading in select fields by 2025, the planet's primary AI innovation center by 2030.


The Plan Before the Sprint


The starting point Neumann pointed to was that same 2017 plan. What stood out in his account wasn't just that it existed, but that most of its 2025 milestones were reportedly hit a year or two early. 



The discipline behind that plan shows up in current data too. Per Stanford HAI's 2026 AI Index, China now leads the world in AI research out, even though U.S. private investment ($285.9B in 2025) still outpaces China's ($12.4B) by more than 23 times. Two structurally different playbooks, both producing global relevance, just measured on different axes: America is buying speed with capital, China is compounding output through sustained, coordinated policy.


Champions and the Ecosystem Around Them


A plan on paper doesn't move an industry alone. The second layer is where strategy becomes infrastructure: naming specific companies to lead specific domains, then deliberately building the smaller players, such as startups, suppliers, research labs, around them.



It's the same logic China used to fast-track its electric vehicle industry a decade earlier, and it doesn't stop at the anchor companies. Clusters of startups grow up around them geographically and that's borne out in outside data too. Tortoise Media's Global AI Index (2025) ranks China second worldwide overall, and cities like Hangzhou (home to Alibaba and DeepSeek) now function as genuine innovation hubs in their own right. Fortune's coverage of Stanford's most recent index adds another layer to that: nearly all of the researchers behind DeepSeek's foundational papers were trained inside China, including many who returned home after studying in the U.S.


The Lesson Beneath the Strategy


None of this is really about which country "wins" because that framing misses what's useful here. The harder, more transferable question is structural: what does it take for a plan to survive nine, ten, thirteen years across shifting political and economic cycles, without collapsing into bureaucracy or short-term reaction?


The ecosystem piece is the more portable lesson for anyone outside government. You don't need a national mandate to apply the logic. Ecosystems don't self-assemble; someone has to build them on purpose, before the payoff is obvious.


So here's the question worth sitting with: does your organization have a plan that would survive being read back to you in five years or a strategy slide that gets quietly rewritten every time the market shifts?


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