The global race for technological leadership has reached a critical inflection point, revealing a widening AI transformation execution gap between the world’s major economic blocs. The latest report from Natixis CIB, led by Alicia García Herrero, paints a clear yet troubling picture of the current landscape. While the United States holds a significant lead in AI and quantum computing, China is rapidly accelerating its capabilities in semiconductor production. Meanwhile, the European Union appears to be struggling to keep pace, risking a permanent technology divide that could define the next decade of economic power.
Defining the AI Transformation Execution Gap in a Polarized World
Technological dominance is decided in the granular details of innovation: who registers the most critical patents, who adopts them the fastest, and who successfully turns innovation into marketable products. Currently, the U.S. and China are exchanging and replicating innovations at a surprising speed, even amid increasing trade restrictions. This fluid flow of “radical innovations” between the two giants suggests that global leadership is increasingly becoming a two-horse race, leaving other regions to navigate the fallout of structural inertia and limited scalability.
One figure from the report should sound every alarm for Western policymakers: in 2023, the EU produced only 804 critical innovations. In contrast, both the U.S. and China generated nearly 3,000 each during the same period. This disparity highlights a growing identity crisis in AI transformation where European efforts remain fragmented while global competitors achieve massive scale. This lack of traction between academia and industry prevents breakthroughs from reaching the global market with the necessary velocity to compete effectively.
The United States: Consolidating Dominance in AI and Quantum Computing
In the field of artificial intelligence, the United States continues to outpace China in most critical subfields. This is particularly evident in generative AI—the backbone of language models like GPT and Claude—and quantum computing, where American labs maintain several years of advantage. This dominance rests on a “virtuous triangle” of vast private capital, a tightly connected academic-industrial ecosystem, and a consistent ability to attract global talent to innovation hubs like Silicon Valley and Austin.
To maintain this edge, American organizations are focusing on drivers for true AI transformation that prioritize infrastructure over mere hype. By focusing on practical application and infrastructure, the U.S. ensures that its theoretical leads translate into tangible economic value. The fluid movement of knowledge between universities, startups, and corporations creates a real-time exchange that remains difficult for more regulated or centralized economies to replicate at the same intensity or speed.
Furthermore, American firms are demonstrating how to scale AI innovation in enterprise by integrating advanced models into existing business workflows. This ability to bridge the AI transformation execution gap allows US-based companies to pivot quickly as new technologies emerge. By leveraging deep pools of venture capital and flexible labor markets, they turn experimental software into industry standards before international competitors can establish a foothold in the same market segments.
China: Mastering Semiconductor Production and Rapid Scaling
China holds significant control over the semiconductor production chain, which serves as the critical pillar of the modern digital economy. While it still depends on certain advanced technologies from abroad, the country dominates the mass manufacturing of the mid- and low-range chips essential to global industry. This specialization, combined with a coordinated state strategy, allows China to excel in computer vision and intelligent aerial vehicles where data volume is the primary driver of progress.
The contrast with the West is striking, as China operates under a unified national industrial strategy while Europe remains fragmented across 27 different innovation policies. This centralized approach enables China to pursue technological leadership by rapidly scaling technologies that require massive data sets and infrastructure. Their ability to turn state mandates into industrial reality provides a level of execution speed that currently challenges the traditional Western model of decentralized innovation and private-sector lead times.
The European Technology Gap: A Crisis of Execution
Europe faces the significant risk of becoming trapped in a state of technological dependence. While the continent possesses world-class universities and cutting-edge labs, it lacks the critical mass and funding to scale its startups effectively. The result is a cycle where Europe innovates but fails to capture the long-term value, leading to a widening EU vs US AI investment gap for business. Great ideas are often born in Europe only to be turned into products and jobs in the U.S. or China.
For the EU to reclaim its position, the focus must shift from pure investment to execution speed and strategic coherence. Decision-makers must understand that B2B marketing and content changes are just the tip of the iceberg in a broader digital shift. Success will depend on whether CEOs and CIOs can jointly lead AI transformation by linking supercomputing hubs to real industrial projects that drive market demand and close the AI transformation execution gap across the continent.
The Final Race Against Time: Mitigating Technological Dependence Risks
The technological gap is not static; it widens with every year that Europe delays the execution of its strategic goals. The U.S. and China are not waiting for consensus, advancing instead with aggressive funding and agile policy frameworks. For Europe, the only viable strategy for mitigating technological dependence risks is to concentrate resources, reduce fragmentation, and focus on measurable outcomes. The AI transformation execution gap cannot be closed through regulation alone; it requires a fundamental shift in how innovation is commercialized.
In the modern era of global technological leadership, those who arrive late do not merely lose the race—they become entirely dependent on the platforms and standards of others. Closing the AI transformation execution gap is no longer just a business objective; it is a matter of economic sovereignty. Organizations that fail to adapt their infrastructure and leadership styles to this new reality will find themselves increasingly marginalized in a world defined by algorithmic power and quantum processing speed.
Based on the report “Radical Innovations in Critical Technologies and Spillover Effects: Where Do China, the U.S., and the EU Stand?” published by Natixis CIB.