Why Google and OpenAI’s Dominance Risks AI Poverty Traps

As AI accelerates and AI companies prosper, what are the consequences for the rest of the world?

According to new research from University of Auckland and University of Otago economists, AI now threatens to deepen global inequality as 60% of developing nations lack the digital infrastructure required to deploy AI systems at scale.

Dr Asha Sundaram, Associate Professor at the University of Auckland Business School and Dr Dennis Wesselbaum, Associate Professor at the University of Otago, argue that developing countries risk falling into “AI poverty traps” that could lock entire economies into technological dependence on developed nations.

The research, published in Economic Development Reloaded: The AI Revolution in Developing Nations, highlights how the concentration of AI technology in the hands of US corporations Google and OpenAI could exacerbate existing global disparities.

Google, which develops AI systems including Gemini, controls significant AI infrastructure alongside cloud computing services. Whilst OpenAI, the company behind ChatGPT and GPT-4 language models (LM), has emerged as a dominant force in Gen AI technology.

“Much of the technology is controlled by firms like Google and OpenAI, raising the risk of over-reliance on foreign tech, potentially stifling local innovation,” Asha explains.

Telecoms infrastructure emerging as critical solution

The fundamental barrier preventing developing nations from harnessing AI lies in inadequate digital infrastructure.

Low internet and mobile phone penetration rates, combined with limited access to high-speed networks and cloud-based services, create insurmountable obstacles for AI deployment.

Considering cloud-based services refer to computing resources delivered over the internet, allowing users to access software and storage without owning physical hardware, these services form the backbone of modern AI systems, which require substantial computational power to process data and run algorithms.

“The downside is that there isn’t a lot of capacity in some countries in terms of digital infrastructure, internet and mobile phone penetration,” Asha adds.

The research suggests telecommunications providers hold the key to addressing these infrastructure gaps, as building robust networks in emerging markets is both a commercial opportunity and a prerequisite for equitable global progress.

AI deployment showing promise despite infrastructure challenges

The potential for AI to transform developing economies remains substantial when proper foundations exist.

Dennis says: “For developing countries, AI could be a game-changer, boosting productivity, expanding access to essential services and fostering local innovation if the right infrastructure and skills are in place.”

For example, Ethiopia is emerging as successful with AI implementation through telecommunications partnerships, as the country’s largest telecom provider has collaborated with the government to deploy algorithms that analyse mobile money transactions for creditworthiness assessment.

This AI-powered credit scoring system enables small businesses without traditional collateral to access short-term financing.

The need for regulatory frameworks and international coordination

Without proper regulatory alignment and international cooperation, AI development risks repeating historical mistakes in foreign aid policy.

“We also need robust legal and regulatory frameworks to support responsible AI by addressing data privacy, ethics and transparency concerns,” Asha says.

The research also warns against creating dependency relationships similar to those seen in traditional development aid programmes.

“Aid has often failed to spur lasting growth in developing countries,” Asha adds, “partly because it can create dependency, reducing self-reliance and domestic initiatives.”

Investment needed for inclusive AI growth

For inclusive AI growth, the economists propose targeted investment strategies including grant funding, concessional loans and global AI tax regimes to ensure countries capture value from AI-driven economic activity within their borders.

Grant funding would be non-repayable financial assistance that can support initial infrastructure development without creating debt burdens for recipient countries.

A global AI tax regime would establish international frameworks for taxing AI-generated revenue, ensuring that economic benefits reach the countries where AI systems operate.

The research concludes that telecommunications partnerships will prove essential for realising AI’s potential in developing markets.

Beyond infrastructure investment, AI training programmes and talent development initiatives must address the digital skills gap that currently limits local capacity.

“AI holds the power to transform development trajectories,” Dennis says, “but without targeted investments and inclusive policies, it risks deepening the digital divide and entrenching global inequality.” 

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