Microsoft Warns of Widening AI Divide Despite Fastest Tech Adoption in History

AI adoption races ahead—leaving everyone else in the dust.

The Great AI Split

Microsoft's latest research reveals a troubling paradox: artificial intelligence is spreading faster than any technology we've seen, yet the gap between AI haves and have-nots is turning into a chasm. Companies racing ahead with AI implementation are pulling further away from competitors still stuck in analog thinking.

Adoption rates that make the internet revolution look slow—but benefits concentrating in fewer hands. The usual corporate suspects hoard the AI advantage while traditional businesses play catch-up. Another case of technology democratizing access while centralizing power—Wall Street must be thrilled.

Welcome to the AI gold rush where the picks and shovels cost more than the mine.

Language barriers worsen the global inequality in AI

While Microsoft acknowledges that AI tech is fast growing and spreading like no other tech before, there are fears this AI wave will not be experienced by everyone in the world therefore “deepen global inequality.”

According to the Microsoft report, most AI models are trained in English, which means billions across the world cannot access the technology in their native languages. According to Microsoft, AI speaks English.

The report indicates that while English and other high-resource languages are used to train AI, the majority of the world’s 7,000 languages are effectively excluded from AI systems, therefore limiting access for billions of people.

According to Microsoft, low-resource languages like Hausa, Bengali, and Chichewa are under-represented in major AI developments, therefore limiting access to users in those regions who cannot interact with tools that cannot understand them.

The tech giant opines that unless digital infrastructure and education catch up, “this gap will define who benefits from AI for decades to come” and could cement a new technological divide.

Microsoft cites the stark infrastructure gap as problematic

In this report, Microsoft indicated that over 1.2 billion people now use AI tools, which the tech giant admitted the adoption rate far outpaced electricity, computers and the internet. However, despite this rapid adoption and spread of the technology, Microsoft maintains that the diffusion is not even.

In the report, Microsoft highlights the widening gap between the “haves” and the “have-nots” citing countries with power, data, and skills to use AI, and those that still lack the basics.

Countries like UAE, with 59.4% adoption, Singapore at 58.6%, and Norway with 51.9% are leading the world in AI use.

According to Microsoft, these countries have vast electricity, near-universal internet access, and while their populations are digitally fluent. Yet in some parts of Sub-Sahara Africa, South Asia, and Latin America, fewer than 10% of the populations use AI due to factors like low internet penetration, unreliable power, and limited access to the devices as well as the basic education to needed to use new technologies.

In Africa, Microsoft recently highlighted the vast opportunities for AI developments. It however demands coordinated, inclusive effort involving governments, education systems, industry and civil society, according to Microsoft.

“The challenge is not only scale, but also coordination. Fragmented efforts and a lack of unified strategy continue to slow momentum and dilute impact,” said Microsoft.

“To fully realize AI’s potential for job creation, Africa must build a coordinated, inclusive skilling ecosystem, where government, education, industry, and civil society work together to shape the AI economy,” added Microsoft.

The report also highlights the infrastructure gap that exists between countries, which has an impact on AI adoption.

In terms of energy, the US leads with 53.7 gigawatts (GW) of data center capacity followed by China with 31.9GW, then Germany with 8.5GW, and the United Kingdom with 7.4GW.

According to the report the AI diffusion is dependent on electricity and computing capacity as much as on algorithms or data, and that over 700 million people still lack reliable power.

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