• AI adoption varies widely between countries, creating a growing capability overhang
• Advanced users rely on AI for multi-step, complex tasks instead of prompts
• OpenAI claims some lower-income countries use advanced AI more than wealthier nations

Artificial intelligence systems are improving quickly, yet adoption across countries remains uneven, new research has claimed.

The findings from OpenAI argue a growing capability overhang exists between what current AI systems can do and how much of that capability is actually used by people, companies, and governments.

The company warns this gap risks allowing a small group of countries to move faster economically and technologically, while others struggle to keep pace.

Evidence of uneven adoption across countries

OpenAI frames this as a problem of usage rather than access, suggesting that uneven skills, infrastructure, and institutional readiness matter as much as model availability.

Data cited by OpenAI indicates that advanced usage differs sharply between users and countries.

Power users depend on stronger reasoning skills, using AI tools for complicated, multi-step tasks instead of single-step prompts.

Country-level differences show similar variation, with some nations using far more advanced capabilities per person than others.

OpenAI notes that this gap does not align neatly with income levels, because some countries with lower income levels are using advanced AI tools more than some wealthier countries.

OpenAI’s response to this gap is its Education for Countries program, which aims to integrate AI into national education systems.

The initiative focuses on building AI skills among students while providing educators with training and tools to guide responsible use, with early partners include countries across Europe, the Middle East, Central Asia, and the Caribbean.

OpenAI describes the program as a way to treat AI as essential education infrastructure and will support research while expanding access to advanced systems.

OpenAI links education efforts to broader national strategies that include workplace adoption, infrastructure development, and workforce training.

The company argues productivity gains depend on scaling enterprise use and improving institutional fluency with AI systems.

New initiatives announced alongside the World Economic Forum extend this approach into areas such as health, disaster preparedness, cybersecurity, and start-up support.

These programs are described as flexible frameworks shaped through discussions with partner governments rather than standardized deployments.

In its own framing, OpenAI positions adoption, skills, and infrastructure as necessary complements to advancing model capability.

The company’s interpretation is that early action could allow more countries to translate AI progress into tangible economic benefits.

It remains uncertain whether partnerships and wider AI access can reduce structural differences, given varying governance, funding, and policy execution.

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Efosa has been writing about technology for over 7 years, initially driven by curiosity but now fueled by a strong passion for the field. He holds both a Master’s and a PhD in sciences, which provided him with a solid foundation in analytical thinking.