World Bank urges investment in local AI tools to drive economic growth

The World Bank has called on developing nations to invest in affordable, locally tailored AI tools to stimulate job creation, enhance public services and broaden economic prospects. This recommendation was issued during the World Bank Group Meetings on October 18, 2026, where world leaders and tech specialists deliberated on the role of AI in boosting productivity and enabling entrepreneurial ventures.

Tharman Shanmugaratnam, a senior figure from Singapore, highlighted how the increasing accessibility of AI is blurring the distinction between employees and entrepreneurs. Discussions at the meeting, which featured World Bank President Ajay Banga and International Monetary Fund Managing Director Kristalina Georgieva, centered on "Small AI"—cost-effective tools designed for specific functions, even on rudimentary devices and in regions with restricted internet access.

Experts emphasized AI's potential to aid agriculture, healthcare, education, skills enhancement, and small enterprises. They also advocated for investment in digital infrastructure, training, local data, and responsible governance to transition from experimental projects to practical applications. The push is prompted by the World Bank’s Africa Economic Update: Building AI Readiness, released in October 2026, which raises concerns about the underrepresentation of African countries, languages, and economic activities in global AI training datasets.

The report notes that Africa boasts over 2,000 languages, yet nearly 56% of open-source training data is exclusively in English, a disparity that could hinder the effectiveness of AI systems in understanding and catering to African users' needs. The report cites InkubaLM, a small language model created by the African firm Lelapa AI, as a compelling example.

Trained on widely spoken African languages like isiZulu, Yoruba, Hausa, Swahili, and isiXhosa, InkubaLM outperforms larger models on these languages, demonstrating the potential of locally focused AI solutions. However, creating effective local systems necessitates overcoming challenges such as insufficient digital infrastructure, a shortage of technical skills, and limited access to computing resources.

The World Bank also stresses the importance of establishing clear guidelines on data ownership, privacy, consent, and benefit-sharing when communities contribute language resources for AI system training. Regional collaboration could facilitate knowledge sharing and alleviate the financial burden of developing tools for languages with smaller digital markets.

The report contends that evaluating success should focus on how accurately and affordably AI can be utilized in everyday life, rather than on the sheer number of languages a system claims to support. To fully leverage AI for improving services, fostering businesses, and expanding economic opportunities, developing countries must invest in locally relevant tools, infrastructure, and skills.