Artificial intelligence (AI) is rapidly emerging as one of the most transformative economic forces of the era, with its global market projected by UN Trade and Development (UNCTAD) to expand roughly 25-fold to around $4.8tn by 2033.
For advanced economies, the technology promises substantial productivity gains. For emerging markets, however, the implications are more complex and double-edged. AI offers a powerful means to accelerate development, improve public services, increase industrial know-how and leapfrog outdated infrastructure.
Yet it also threatens to erode long-standing sources of competitive advantage and widen the gap between richer and poorer nations, particularly in countries with large services sectors that depend on low-cost manual and repetitive tasks. The stakes are therefore especially high for the developing world, QNB stated in its latest economic commentary.
The ultimate impact of AI on any economy will depend not only on the technology itself but also on a country’s capacity to adopt and adapt it. Emerging markets enter this transition with a distinct mix of advantages and vulnerabilities relative to advanced economies.
QNB examined both dimensions of AI’s impact on emerging markets: the opportunity to raise productivity and growth, contrasted by the potential disruption to the value propositions of entire industries built over decades.
“On one hand, AI represents a significant opportunity to lift productivity and accelerate development. In economies long constrained by shortages of skilled labour and uneven institutional capacity, AI-enabled tools can extend the reach of scarce expertise. In education, AI translation models can support regional dialects and low-resource languages, reducing structural barriers to communication,” QNB stated.
Personalised tutors can improve access to quality education while tailoring lessons to individual students’ skill levels. In healthcare, AI-assisted diagnostics can extend services to rural areas while improving the quality of initial diagnosis, with potentially meaningful effects on infant mortality and average life expectancy.
In finance, AI-assisted credit scoring using unstructured and behavioural data can help increase the availability of credit in micro-finance to small producers and entrepreneurs while reducing related credit risks, QNB pointed out.
Much as mobile technology allowed many developing countries to bypass fixed-line and internet broadband networks, AI offers the potential to leapfrog historical constraints on growth.
Emerging markets have already become meaningful participants in the digital economy, exporting more than $1tn in digitally deliverable services in 2024. Harnessed effectively, AI could reinforce this momentum and help create entirely new industries, QNB stated.
“On the other hand, however, AI poses a significant disruption to labour markets and to the development model that has long served emerging economies. It is shifting the economic advantage of repetitive remote tasks away from labour arbitrage, which relies on low-cost human workers, towards algorithm arbitrage, which relies on lower-cost AI agents. The IMF estimates that around 40% of jobs in emerging markets are exposed to AI, particularly in industries and services with high levels of manual and routine work,” stated QNB.
Generative AI and AI agents can now handle simple cognitive tasks, data processing, and basic billing at a lower cost than employing overseas staff. This impact is already being felt across India’s $300bn IT outsourcing industry.
Routine junior developer and business process outsourcing roles are heavily exposed, causing sharp drops in campus recruitment across Indian technology hubs. The Nifty IT index, which tracks India’s biggest software companies, is down by around 15% this year, compared with a 20% gain in the broader MSCI Emerging Markets Index, QNB stated.
“All in all, AI presents emerging markets with both a defining opportunity and a serious risk. Realising the opportunity will require avoiding relegation to the margins of the future global AI-enabled economy. This will depend on decisive action across three fronts: building digital infrastructure, developing data ecosystems, and investing in skills.
“Economies that move early to strengthen these foundations stand to convert AI into a powerful engine of catch-up growth. Those that do not may find the gap with the technological frontier widening further, making AI one of the central determinants of economic divergence in the years ahead,” QNB stated.
