NetApp® (NASDAQ: NTAP), the intelligent data infrastructure company, today released its new report, The AI Space Race, examining which countries are leading the fierce global competition to become the world leader in AI innovation. While some countries are further ahead than others, this survey of CEOs and IT executives in the U.S., China, the U.K., and India found that every player has the potential to thrive in the global race for AI dominance.
AI is no longer optional for business, and the region that leads the world in AI innovation will be well-positioned to be a technological superpower, and drive potential benefits like economic growth, improved quality of life, and global political influence in the years to come. Successfully fueling AI innovation requires organizations to prepare their data to make it accessible, secure, and scalable—wherever it lives—to produce trusted and valuable outcomes.
“In the ‘Space Race’ of the 1960’s, world powers rushed to accelerate scientific innovation for the sake of national pride. The outcomes of the ‘AI Space Race’ will shape the world for decades to come,” said Gabie Boko, CMO at NetApp. “The companies and regions that can get their data ready for AI will be able to generate differentiating business insights and unlock operational efficiencies that launch them ahead of their rivals. Intelligent, scalable, secure data infrastructure is a decisive factor as the global competition drives businesses to solidify their AI ambitions and understand how they translate into a true, lasting advantage.”
The AI Space Race is Still Anyone’s Game
When asked what region is best positioned to lead AI innovation in the long term, respondents from every country overwhelmingly pointed to the U.S. (43 percent).
However, everyone sees themselves as AI ready, and every region views themselves as competitive in the global AI innovation race. The report shows that 81 percent of global respondents are currently piloting or scaling AI, while 88 percent view their organization as mostly or completely ready to sustain AI transformation. The massive investment in AI innovation around the globe shows that everyone is working to become the world leader in AI innovation. However, some countries are working harder than others, with respondents from India (29%) and UK (32%) reporting that they feel extra pressure to compete as China and US are seen as clear leaders. With all this fierce rivalry and active investment, the field is wide open for any country to achieve that goal.
Driving the global differences in the state of AI innovation are diverging priorities in how it is implemented. Respondents in China put a much greater focus on scalability with 35 percent ranking it as a top capability—11 percent higher than the global average—suggesting a focus on rapid deployment to make an early impact. By contrast, leaders in the U.S., U.K., and India put a greater emphasis on integration with existing systems. This long-term strategy to enable sustained AI growth may result in greater business value in the future, though the short-term approach may drive more immediate results.
Aligning Business Ambitions and Technology Reality
While organizations are focused on turbocharging AI innovation, CEOs and IT leaders need to be aligned on the state of their technology environments and plans to drive long term success and leadership.
In China, the survey indicates there is a critical misalignment between Chinese CEOs and IT leaders on both AI readiness and actual deployment, which could hinder its long-term leadership potential: 92 percent of Chinese CEOs report active AI projects, compared to just 74 percent of Chinese IT leaders. In the United States, alignment is stronger—77 percent of CEOs and 86 percent of IT leaders say the same. Perceptions of AI readiness are also misaligned. While 68 percent of Chinese CEOs consider their organizations AI-ready (versus 62 percent globally), only 58 percent of their IT counterparts agree (versus 72 percent globally). In the United States, CEO and IT readiness is more closely aligned at 60 percent and 61 percent, respectively. These differences suggest that internal alignment—not just ambition—may shape how AI strategies are executed, depending on region and role.
However, concerns about the quality of results from AI projects have the potential to slow down innovation if they are not addressed. Globally, 79 percent of respondents reported a fear of broken models and biased insights resulting from poor data and cloud strategies. Businesses that want to tap into the opportunity of AI innovation will need strong data governance strategies to serve as the foundation for their digital transformation.
“One of the most significant success factors in the AI Space Race will be data infrastructure and data management, supported by cloud solutions that are agile, secure and scalable,” said Russell Fishman, Senior Director, Product Management at NetApp. “Winning organizations will be those that recognize that they require an intelligent data infrastructure in place to ensure unfettered AI innovation. This is critical no matter the company size, industry or geography. As organizations around the world embrace AI at scale, NetApp is there to help them extract maximum value from their data by creating an AI ready data infrastructure that unifies, manages and harnesses their data for optimal AI outcomes.”
The AI Space Race is just getting started, but the organizations that can move the fastest will lead in AI innovation. The fierce competition highlighted by this report shows that businesses need to find an edge that will help them leverage AI securely and efficiently to stay a step ahead of their peers, no matter how fast the race evolves. Adopting an intelligent data infrastructure offers organizations unparalleled flexibility and agility to move into the cloud when needed, scale AI workloads seamlessly, reduce costs, and quickly adapt to evolving business needs. As AI increasingly moves from generating content to taking action, businesses need security that starts with the data itself. Only an intelligent data infrastructure delivers a full chain of trust, empowering enterprises to move fast, without compromising control.
To learn more, read the report brief and the infographic:
- Report brief: https://www.netapp.com/pdf.html?item=/media/136511-na-1180-ai-space-race.pdf
- Infographic: https://www.netapp.com/pdf.html?item=/media/136510-na-1179-the-ai-space-race-infographic.pdf
Join NetApp and Steve McDowell of NAND Research for a LinkedIn Live event on Wednesday, June 25 at 11am ET: https://www.linkedin.com/events/7340492842705821697/about/
Methodology
NetApp partnered with Wakefield Research to conduct a quantitative research study during May 2025, among 400 IT Executives and 400 CEOs in 4 countries (US, China, UK and India).
Additional Resources
- NetApp AI Solutions: Data Fuels AI, NetApp Fuels Data
- NetApp Intelligence: Thought Leadership Insights for Better Decisions
- NetApp’s 2024 Data Complexity Report Reveals AI’s Make or Break Year Ahead
- NetApp’s 2024 Cloud Complexity Report Reveals AI Disrupt or Die Era Unfolding Globally
About NetApp
NetApp is the intelligent data infrastructure company, combining unified data storage, integrated data, operational and workload services to turn a world of disruption into opportunity for every customer. NetApp creates silo-free infrastructure, harnessing observability and AI to enable the industry’s best data management. As the only enterprise-grade storage service natively embedded in the world’s biggest clouds, our data storage delivers seamless flexibility. In addition, our data services create a data advantage through superior cyber resilience, governance, and application agility. Our operational and workload services provide continuous optimization of performance and efficiency for infrastructure and workloads through observability and AI. No matter the data type, workload, or environment, with NetApp you can transform your data infrastructure to realize your business possibilities. Learn more at www.netapp.com or follow us on X, LinkedIn, Facebook, and Instagram.
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