AI requires massive capital:Big tech alone is spending hundreds of billions annually; with global AI infrastructure needs projected to reach USD 6.7 trillion by 2030.
Private funding can’t cover it all:Venture capital and corporate investment fall short, making government support and sovereign wealth funds crucial.
Winner-takes-all dynamics are intensifying:Big tech incumbents dominate the market, with major implications for economic and strategic power.
Governments must act strategically:National AI strategies, targeted investments, and global collaboration are essential to safeguard competitiveness and sustainable growth.
Big tech spent USD 155 billion on AI in FY 2025 and is set to invest hundreds of billions more. In total, 4 tech companies (Microsoft, Meta, Alphabet, and Amazon) will spend USD 369+ billion on capex (USD 400+ billion, by most accounts) in the coming year.
The bottom line is, to sustain frontier AI efforts, huge financial backing is needed. Where do AI companies go?
AI funding sources: VC, big tech, and government investments
Global AI venture capital (VC) funding exceeded USD 100 billion in 2024 – a 62% YoY growth, still not enough to satisfy AI companies’ demand. For billions-scale infusions, they might turn to:
1. Private sector
Corporate AI investment reached USD 252.3 billion in 2024, hitting a record high with 26% growth.
Governments provide AI leaders with grants, equity investments, subsidies and tax incentives, compute and infrastructure access, loans and accelerators.
Though governments worldwide are increasingly channeling resources into AI, with China and the US at the forefront (USD 62 and 52 billion respectively), their commitments remain limited. Reasons may vary: shifting political priorities, risk considerations, skepticism or underestimation of AI’s future demand, or strategic reliance on the private sector.
4. Sovereign Wealth Funds (SWFs) (government-affiliated)
Since VC and private investments will not be sufficient, SWFs might become AI companies’ last resort. In 2024, SWFs’ total assets under management reached $12 trillion globally. GCC funds collectively manage USD 5 trillion (USD 7 trillion by 2027), among other large investors are China-, Norway- and Singapore-based SWFs.
That said,AI firms’ sources of financing are tight. Then the question is, whether there is enough capital in the world to sustain AI development.
If there is, those who deliver on promises could reap enormous rewards. But if capital does not prove sufficient, consequences might include systematic breakdowns, supply chain bottlenecks, regulatory backlash and, eventually, a surge of consolidations.
On top of that, many emerging AI companies build on existing models, ensuring incumbents’ recurring revenue, so, if funding dries up, integrators, not tech giants, are at risk.
AI industry outlook: winner-takes-all market risks
High costs, along with compute shortages, data monopolies, and capital intensity, drive strategic M&A (2025 total deal volume is expected to exceed that of the prior year by 33%), reducing diversity and shifting to state / incumbent control .
Concentration of computing power and services
The US accounts for one third of the top 500 supercomputers and more than a half of overall computational performance.
The market of AI services providers is dominated by the US- and China-based companies (Amazon, Alphabet, IBM, Microsoft, OpenAI in the US and Baidu, Tencent in China).
Given that just 100 companies account for over 40% of global business R&D investment, large players locking up their technology can significantly hinder open innovation.
All together, these strains centralize resources and create a ‘winner-takes-all’ gap. As a result, AI is dominated by incumbents, raising concerns over economic dependence, limited innovation diversity, strategic vulnerabilities, and national competitiveness – forcing governments to take decisive steps.
Closing the AI funding gap: government playbook
While private enterprises, investors, and civil society play vital roles in responsible AI deployment, the greatest responsibility falls on governments due to the scale of investment needed and associated risks. That’s why, regardless of capital availability in the industry, governments should know how to act. Here are the steps we suggest they take:
Determine AI direction and positioning:Decide whether to develop domestic capabilities, rely on international platforms, or combine both, guiding all policies and investments.
Build a national AI strategy: Outline economic, technological, and geopolitical goals.
Conduct supply-demand analysis across the AI value chain: Identify market needs, investment gaps, and sectors for targeted resource allocation.
Align investment and funding mechanisms with strategic goals:Deploy capital through investments and partnerships that support prioritized areas, while balancing domestic innovation with dependence on global players.
Advance international collaboration, workforce development, and regulation: Engage internationally on governance and ethics, while building workforce skills to sustain AI growth.
What approach do you think governments should take?