AI’s Promise for Developing Economies Faces Infrastructure and Literacy Hurdles

AI’s Rapid Adoption in Emerging Markets

Artificial intelligence tools are seeing remarkable uptake across developing economies, with sources indicating approximately 800 million people now use AI chatbots weekly. According to reports, countries with lower human-development scores demonstrate particularly high confidence in AI technologies, with Ghana and Nigeria emerging among the most enthusiastic adopters globally. The technology‘s accessibility via affordable smartphones positions it as a potential equalizer for knowledge access in regions historically underserved by traditional infrastructure.

AI’s Rapid Adoption in Emerging Markets
Early Success Stories in Education and Healthcare
Connectivity Remains Critical Barrier
Digital Literacy and Language Gaps
Institutional Integration Challenges
Productivity Transformation Required
The Path Forward

Early Success Stories in Education and Healthcare

Multiple pilot programs across Africa demonstrate AI’s transformative potential. In Nigeria, analysts report a six-week after-school program using Microsoft’s Copilot AI assistant produced English test score improvements equivalent to nearly two years of additional schooling. Meanwhile, healthcare applications show similar promise – a randomized trial covering 40,000 patient visits across Nairobi clinics found that AI-assisted doctors reduced diagnostic errors by 16% and treatment mistakes by 13%, according to the study findings.

Connectivity Remains Critical Barrier

Despite AI’s potential, the digital divide presents significant challenges. Reports indicate only about 25% of people in poor countries were online in 2024, compared to 90% in wealthy nations. While approximately 85% of Africans live within mobile-broadband coverage areas, data costs frequently remain prohibitive. The report states that mobile operators’ substantial markups on data services continue to limit access for the poorest populations, potentially excluding them from the AI revolution entirely.

Digital Literacy and Language Gaps

Beyond connectivity, skill disparities create additional hurdles. World Bank estimates suggest 70% of ten-year-olds in low and middle-income countries cannot read simple texts, complicating their ability to interact effectively with text-based AI systems. Research from UC Berkeley indicates that outcomes vary significantly by user capability – skilled Kenyan entrepreneurs saw profit increases exceeding 15% with AI assistance, while less experienced business owners experienced declines after following generic AI advice. Language representation compounds these challenges, as most AI systems primarily train on English and other wealthy-nation languages, leaving hundreds of African languages underrepresented.

Institutional Integration Challenges

Experts caution that technology alone cannot drive transformation without proper institutional support. According to analysts at the Abdul Latif Jameel Poverty Action Lab, previous “silver-bullet” technologies like massive open online courses failed to significantly improve educational outcomes in developing countries because they operated outside existing educational structures. Similar integration challenges appear in governance applications – researchers found that while AI successfully identified thousands of fake companies in one Indian state, enforcement failed to improve because officials lacked incentives to act on the findings.

Productivity Transformation Required

Ultimately, sources suggest AI’s economic impact will depend on whether it can drive broad productivity gains rather than merely improving individual services. Historical analysis of 25 general-purpose technologies over two centuries indicates that while newer inventions reach developing countries faster, their implementation often remains shallow. Even in advanced economies like the United States, reports indicate only about 10% of firms currently use AI in production processes, suggesting the technology‘s full economic potential remains largely untapped worldwide.

The Path Forward

Despite these challenges, several initiatives show promise for making AI more accessible. Community-led projects like Masakhane are developing open datasets for African languages, while voice-based interfaces could eventually enable users to interact with AI in their native tongues. As connectivity improves and digital literacy grows, analysts suggest AI could follow the trajectory of mobile phones in Africa – bypassing traditional infrastructure limitations to deliver services directly to populations that previously lacked access to essential knowledge resources.