The risks of AI dependence for developing nations

As Artificial Intelligence (AI) reshapes technology worldwide, developing countries must carefully navigate its adoption, especially generative AI. While these AI-driven tools enhance efficiency and foster innovation, they also raise serious concerns about data sovereignty and national security.

The rise of generative AI models like ChatGPT has made advanced AI accessible to people in developing nations, unlocking new opportunities in education, business, and governance. However, this rapid and widespread adoption is like a virus - once it spreads, it becomes nearly impossible to regulate. The challenge is not just about access but control: How can a country restrict the use of AI models when their ownership, governance, and data processing are controlled by developed nations? This dependency raises serious concerns about data sovereignty, national security, and economic stability. If developing nations rely on foreign AI infrastructure, they risk losing control over critical information flows, making them vulnerable to external influence. The ability of AI providers to dictate terms, restrict access, or shape information ecosystems could deepen inequalities, effectively placing developing nations in a position of digital dependence. Critics argue that this dependency could evolve into a new form of digital colonialism, where developing nations become increasingly reliant on AI infrastructure, they neither own nor control.

The integration of AI into daily life marks an irreversible shift in human behavior and societal function. As AI tools become embedded in everyday decision-making, from personal choices to government operations, this dependence becomes neurologically and structurally hardwired, much like how smartphones transformed from luxury to necessity. For developing nations, this behavioral lock-in poses an unprecedented sovereignty challenge. When a population’s cognitive patterns and daily operations become dependent on foreign-controlled AI systems, national autonomy is compromised at its most fundamental level. The sovereignty threat extends beyond data and infrastructure. It reaches into the collective thinking and decision-making capabilities of entire populations, making traditional notions of national independence increasingly fragile.

To navigate these challenges, developing nations must weigh the risks against the opportunities. On one hand, restricting foreign AI usage can help protect national data and reduce reliance on external entities. However, this approach risks stifling innovation and falling behind in the global AI race. On the other hand, investing in domestic AI capabilities offers greater sovereignty and control but requires significant resources such as advanced infrastructure, skilled talent, and sustained research. Several countries have already begun initiatives to build local AI research centers and develop indigenous models, though the gap with leading AI nations remains substantial.

The real challenge lies in striking a balance: leveraging foreign AI for immediate gains while steadily building the foundations for long-term technological independence. Building domestic AI capabilities is not just about technological independence but it is about ensuring long-term economic competitiveness. The initial investment may be significant, but the alternative is perpetual technological dependence.

In an AI-driven future, technological self-reliance is becoming as crucial to national sovereignty as traditional measures of self-determination. The cost of investing in domestic AI capabilities is high, but the cost of dependence could be even greater, potentially restricting economic and strategic autonomy for decades to come. Developing nations must act now, striking a careful balance between adoption and self-sufficiency to secure their place in the global AI landscape. (The writer is assistant professor of cybersecurity and software engineering at The University of Adelaide, Australia)