The “AI Cold War” refers to a geopolitical narrative describing the technological and strategic rivalry between major powers, primarily the United States and the People’s Republic of China (PRC), in the field of artificial intelligence. This concept draws parallels to the historical Cold War between the US and the Soviet Union, but with AI as the central battleground for global dominance1
The term “AI Cold War” emerged after the PRC published its AI Development Plan in 2017, which aimed to make it the global leader in AI by 2030. This narrative has since been reinforced by policymakers, tech industry leaders, and media outlets. This Cold War centers around four key “accelerator technologies”: artificial intelligence, semiconductor chips, quantum computing, and biotechnology.
It has faced criticism as an oversimplified or potentially dangerous narrative in describing US-PRC competition in artificial intelligence development. However, for those of us working in digital development in low and middle-income countries (LMICs), this framing provides a useful lens for understanding the strategic dynamics and power struggles that increasingly shape our work.
AI Cold War Narrative for Government
Richard Heeks and Yujia He’s analysis of the “AI Cold War” narrative shows that its parallels with the First Cold War are particularly instructive.
Just as newly independent nations in the 1950s and 60s found themselves navigating between competing superpowers, today’s developing nations face mounting pressure to align their AI and digital infrastructure development with either US or PRC technological ecosystems.
Both powers are actively seeking to expand their spheres of technological influence, offering funding, technology transfers, and capacity building support – but often with strings attached. This dynamic is evident in several key ways:
1. Aggressive AI Promotion
Both the US and the People’s Republic of China are aggressively promoting their respective AI technology stacks and standards in developing markets. Chinese firms like Huawei and Alibaba Cloud are offering comprehensive AI solutions to LMIC governments, often bundled with Belt and Road Initiative infrastructure projects. Meanwhile, US tech giants backed by government initiatives are pushing their own AI platforms and cloud services, frequently emphasizing values like data privacy and algorithmic transparency.
2. Exclusive Choices
There’s increasing pressure on LMIC governments to make exclusive choices between US and PRC AI ecosystems. When a country adopts PRC surveillance systems or facial recognition technology, it often faces scrutiny or warnings from Western partners about security risks. Conversely, choosing Western AI solutions may mean missing out on attractive PRC financing packages or technology transfer arrangements.
3. Focused Investment
Third, both powers are investing heavily in artificial intelligence talent development in LMICs, but with clear strategic aims. PRC’s AI training programs for government officials and technologists from developing countries mirror similar US initiatives. Both seek to create networks of influence and shape how the next generation of LMIC tech leaders think about AI governance and implementation.
4. National Sovereignty
The Cold War analogy is particularly apt when considering data governance and digital sovereignty. Just as the First Cold War involved competing models of economic and political organization, today’s AI competition presents developing nations with divergent approaches to data control and algorithmic governance. The PRC model emphasizes state sovereignty over data flows and AI development, while the US model promotes private sector innovation within certain ethical bounds.
AI Cold War Narrative for Digital Development
For digital development practitioners, understanding this as a “Cold War” dynamic offers several advantages. The concept can help us highlight the realities around:
- Strategic thinking about technological dependency. Just as Non-Aligned Movement countries sought to maintain autonomy during the First Cold War, LMICs today must carefully consider how their AI choices might lock them into particular technological trajectories.
- Ideological dimensions of AI adoption. Different AI systems embed different values and assumptions about privacy, individual rights, and the role of the state. These choices have long-term implications for how digital development unfolds in LMICs.
- Importance of building local capacity. The First Cold War spurred many developing nations to invest in indigenous technological capabilities to reduce dependence on superpower patronage. Similarly, LMIC governments today need to develop domestic AI expertise to make informed choices between competing offerings.
- Opportunities for strategic leveraging. Just as Cold War competition led to increased aid and investment in developing countries, today’s AI rivalry creates opportunities for LMICs to negotiate better terms and conditions for technology transfer and capacity building.
Critics might argue that the Cold War framing oversimplifies complex technological relationships or risks becoming a self-fulfilling prophecy of conflict. However, for those working in digital development, this framework helps illuminate the very real power dynamics and strategic choices that shape our work.
A New Non-Aligned AI Movement?
The Cold War analogy suggests possible paths forward. Just as some developing nations successfully played both superpowers off each other during the First Cold War while building indigenous capabilities, today’s LMICs might pursue similar strategies. This could involve selectively adopting AI technologies from both PRC and US ecosystems while investing in local AI research and development.
The rise of regional tech hubs in places like India, Kenya, and Brazil suggests that a new “Non-Aligned Movement” in AI development is possible. These countries are increasingly able to develop their own AI applications and platforms, adapted to local needs and values, while selectively engaging with both US and PRC technologies.
For digital development practitioners, embracing rather than rejecting the Cold War framing can lead to more strategic and nuanced approaches to AI adoption in LMICs. It reminds us that technological choices are never purely technical but always embedded in larger geopolitical dynamics. Understanding these dynamics is crucial for helping partner countries navigate the complex landscape of AI development.
We should recognize this analogy as a useful tool for understanding the constraints and opportunities in our work. It highlights the need to build resilient, locally-appropriate AI ecosystems that can withstand geopolitical pressures while serving local development needs. In this way, the Cold War framing doesn’t trap us in binary choices but rather illuminates the path toward greater technological autonomy for developing nations.
