Artificial Intelligence: A New Engine of Economic Growth and Technological Development in Emerging Countries

From African farms to Asian semiconductor factories, artificial intelligence is opening new pathways for productivity, innovation and economic opportunity. But turning technological progress into lasting prosperity will depend on investment, education, infrastructure and local ownership.

AI TV INFO | Global Technology & Economic Development Desk

Artificial intelligence is rapidly emerging as a strategic force in the economic transformation of developing countries. Across Africa, Asia and Latin America, governments, entrepreneurs and local communities are exploring how AI can improve productivity, modernize public services, strengthen industries and create new opportunities for millions of people.

While advanced economies continue to command significant financial resources and research capabilities, emerging markets are increasingly finding ways to use AI to overcome traditional development barriers. From mobile-based agricultural advice to intelligent manufacturing systems, new applications are helping countries address local challenges while strengthening their participation in the global digital economy.

For many developing nations, the opportunity is particularly significant: rather than following the same industrial development path as wealthier countries, they can selectively adopt modern technologies to accelerate progress in agriculture, healthcare, education, finance and infrastructure.

However, experts caution that access to AI alone will not guarantee economic transformation. Reliable electricity, affordable internet, skilled workers, investment and effective governance remain essential to ensuring that technological advances translate into measurable improvements in living standards.

AI AND AGRICULTURE: TECHNOLOGY REACHES THE SMALLHOLDER FARMER

Agriculture remains a major source of employment and income across much of the developing world. Yet millions of smallholder farmers continue to face unpredictable weather, crop diseases, limited access to financing and difficulties reaching profitable markets.

AI-powered agricultural tools are beginning to offer practical responses to these challenges.

Computer vision systems can analyze photographs of damaged leaves to help identify possible plant diseases and nutrient deficiencies. Weather forecasting and satellite imagery can support decisions about planting schedules, irrigation and crop management. Digital advisory services can also help farmers access relevant information without travelling long distances to agricultural extension offices.

Several initiatives illustrate how these technologies can be applied.

Plantix and digital crop diagnostics: Plantix uses image-based crop diagnostics to help users identify potential plant health problems and access treatment guidance. Such tools can support earlier intervention, although recommendations must be adapted to local conditions and verified where necessary.

ACRE Africa and climate-related insurance: ACRE Africa works with agricultural insurance partners to help smallholder farmers manage climate-related risks. Satellite observations, weather information and index-based insurance approaches can reduce dependence on costly field inspections. The availability and timing of payouts depend on the insurance product and its terms.

Hello Tractor and shared mechanization: Operating in African markets, Hello Tractor connects farmers who need mechanized services with tractor owners and operators through digital booking and fleet-management systems. Better coordination can improve equipment access, reduce idle time and help farmers complete time-sensitive agricultural operations.

Farmerline and local-language advisory services: Ghana-based Farmerline has developed digital agricultural services that connect farmers with information and support. Voice-based and multilingual tools can help address literacy, language and connectivity barriers that limit access to conventional digital platforms.

These examples demonstrate the potential of combining AI, mobile technology, agricultural expertise and local knowledge.

The next challenge is to expand these services affordably, verify their impact and ensure that farmers can use them even where smartphones, electricity and broadband connectivity remain limited.

HEALTHCARE, EDUCATION AND FINANCIAL INCLUSION

Beyond agriculture, AI could help emerging economies improve access to essential services while making better use of scarce resources.

In healthcare, image-analysis systems can assist trained professionals in interpreting medical scans and identifying potential signs of disease. AI can also support appointment management, medicine supply forecasting and the analysis of public-health information.

Such technologies are particularly relevant in rural areas where medical specialists are scarce. Nevertheless, AI systems require clinical validation, appropriate oversight and strong protections for sensitive patient data. They should support qualified healthcare workers rather than replace essential medical judgment.

Education represents another promising field. AI-assisted learning platforms can provide students with personalized explanations, practice exercises and language support. Teachers can use these tools to prepare lessons, adapt learning materials and reduce administrative workloads.

For countries with large young populations, the combination of AI education tools and vocational training could help develop the skills required in software development, engineering, manufacturing and digital services.

Financial technology offers a further opportunity. Digital payment histories and other permitted data sources may help financial institutions assess customers who lack conventional credit records. Properly designed systems could expand access to small-business loans, microinsurance and other financial services.

However, alternative credit scoring also creates risks involving privacy, biased decisions and financial exclusion. Transparent methods, secure data practices and accessible appeals procedures are essential.

EMERGING ASIA: STRENGTHENING THE GLOBAL TECHNOLOGY SUPPLY CHAIN

In Asia, AI development is closely connected to electronics manufacturing, semiconductor supply chains, software services and digital infrastructure.

Countries such as Malaysia, Vietnam and Thailand have opportunities to strengthen their roles in electronics production, semiconductor assembly and testing, industrial automation and advanced manufacturing. India, meanwhile, has substantial capabilities in software services, digital public infrastructure and technology entrepreneurship.

AI can help manufacturers improve quality control, forecast equipment failures, optimize production schedules and reduce waste. These applications may increase competitiveness and encourage the development of higher-value industrial activities.

The wider AI boom is also stimulating demand for data centres, cloud computing and electricity infrastructure. For emerging economies, these investments can create opportunities in construction, engineering, telecommunications and renewable energy.

Yet the benefits are not automatic. Data centres can place significant demands on electricity and water resources, while highly automated factories may reduce demand for certain routine jobs. Governments must therefore assess the broader economic value of major investments, including local employment, skills transfer, energy requirements and domestic supplier participation.

The strategic objective should be to move beyond hosting foreign production facilities towards building local technical expertise, research capacity and competitive companies.

AFRICA: MOBILE TECHNOLOGY AS A DEVELOPMENT ADVANTAGE

Across Sub-Saharan Africa, mobile connectivity provides an important foundation for AI adoption.

In countries such as Kenya, Nigeria, Ghana and Rwanda, entrepreneurs and institutions are exploring applications in mobile finance, agriculture, logistics, education and digital public services.

The region’s experience with mobile money demonstrates how technologies can expand access to services without requiring every user to rely on traditional physical infrastructure.

AI could build on this foundation through voice interfaces, messaging platforms and lightweight applications that work under limited connectivity. Local-language systems are particularly important because many communities cannot benefit fully from tools designed primarily for major international languages.

Agriculture is one immediate area of opportunity. Digital advisory services can help farmers interpret weather information, understand crop-management recommendations and connect with suppliers and markets. In financial services, AI may support fraud detection and more efficient customer support.

But Africa’s digital transformation continues to face major constraints, including unreliable electricity, uneven internet access, limited computing resources and shortages of specialized technical skills.

Addressing these constraints requires coordinated investment in energy, telecommunications, education and locally relevant digital services. It also requires African institutions and businesses to have a meaningful role in developing, governing and benefiting from the technologies they use.

LATIN AMERICA: AGRICULTURE, FINTECH AND INDUSTRIAL MODERNIZATION

Latin America has its own combination of strengths and development priorities.

Brazil offers opportunities in precision agriculture, environmental monitoring, renewable energy and industrial applications. Mexico can build on its manufacturing base and proximity to North American markets, while regional fintech companies are exploring ways to improve payments and access to financial services.

AI-enabled agricultural systems can help optimize fertilizer use, monitor crops and improve logistics. In manufacturing, predictive maintenance and automated quality control can increase productivity and strengthen participation in international supply chains.

Nearshoring—the relocation of production closer to major consumer markets—may create additional opportunities for countries able to combine competitive manufacturing with skilled workers and reliable infrastructure.

To capture these benefits, regional economies will need continued investment in broadband, research, technical education and regulatory cooperation. Supporting domestic suppliers and startups will also be important if higher productivity is to generate broad-based economic development.

THE ECONOMIC OPPORTUNITY: FROM TECHNOLOGY CONSUMERS TO TECHNOLOGY CREATORS

One of the most important questions facing emerging economies is how to ensure that AI investment builds domestic capabilities rather than simply increasing dependence on imported technology.

Adopting existing AI tools can deliver immediate benefits. However, long-term economic resilience requires countries to develop their own software businesses, technical specialists, research institutions and intellectual property.

This transition involves several priorities.

First, invest in people. Digital literacy, mathematics, science, engineering and vocational training should be accessible to a broad section of the population. Workers affected by automation need realistic opportunities to acquire new skills.

Second, strengthen local entrepreneurship. Startups and small businesses need access to finance, reliable digital infrastructure, research partnerships and markets in which they can test and expand their products.

Third, improve essential infrastructure. Electricity, broadband, computing capacity and secure data systems are fundamental requirements for productive AI adoption.

Fourth, encourage responsible investment. Foreign technology companies can contribute capital, expertise and access to global markets. Partnerships should also promote local employment, technical training and opportunities for domestic suppliers.

Fifth, support locally relevant innovation. AI systems adapted to local languages, agricultural conditions, health priorities and administrative needs can address challenges that general-purpose international products may overlook.

Together, these measures could help emerging countries increase productivity, diversify their economies and move into higher-value industries.

THE CHALLENGES: JOBS, INEQUALITY AND DIGITAL DEPENDENCE

Despite its promise, AI also presents significant risks.

Automation may reduce demand for some routine administrative, customer-service and entry-level digital tasks. The scale of the effect will vary by industry, country and occupation, but governments and businesses should prepare workers for changing employment requirements.

Unequal access to technology could widen existing income disparities. Larger companies may have the capital and expertise to benefit quickly from AI, while informal businesses and rural communities risk falling behind.

Dependence on foreign technology providers presents another challenge. Countries that rely entirely on external platforms may face rising costs, limited control over sensitive data and difficulties developing independent technical capabilities.

Environmental pressures also deserve attention. Data centres and computing infrastructure require electricity, cooling and, in some cases, substantial water resources. Responsible development must consider these costs alongside the economic benefits.

Finally, weak data protection, inadequate cybersecurity and poorly governed automated decisions can undermine public trust.

The solution is not to reject AI, but to develop policies that make its adoption more inclusive, accountable and economically sustainable.

A FIVE-YEAR ROADMAP FOR POSITIVE AI DEVELOPMENT

Emerging economies can translate ambition into practical action through a phased development programme.

Year 1 — Establish the foundations. Identify national priorities, assess digital infrastructure gaps, strengthen data protection and launch targeted skills programmes.

Year 2 — Test practical applications. Pilot AI projects in agriculture, education, healthcare and small businesses. Establish clear performance measures and evaluate results independently.

Year 3 — Expand local innovation. Increase support for startups, universities, vocational institutions and research partnerships. Improve access to finance and computing resources.

Year 4 — Scale successful solutions. Expand applications that demonstrate measurable benefits, develop regional markets and strengthen links between domestic suppliers and international companies.

Year 5 — Build competitive industries. Focus on higher-value production, locally developed technology, research capacity, exports and sustainable employment.

Success should be measured by improvements in productivity, household incomes, job quality, business growth and access to essential services—not simply by the number of AI systems introduced.

CONCLUSION: PUTTING PEOPLE AT THE CENTRE OF THE AI REVOLUTION

Artificial intelligence presents emerging countries with an important opportunity to accelerate economic and technological development.

From improving agricultural resilience in Africa to modernizing manufacturing in Asia and strengthening fintech in Latin America, practical AI applications can help address persistent development challenges and open new economic pathways.

But technology alone cannot deliver prosperity. The decisive factors will be investment in people, reliable infrastructure, responsible governance, local entrepreneurship and the ability to retain more economic value within domestic economies.

For developing nations, the objective should not simply be to adopt AI faster. It should be to use AI more effectively to create productive businesses, expand opportunity, improve public services and build stronger, more resilient economies.

The future of AI in emerging markets will ultimately be measured not by the sophistication of the technology, but by the quality of life it helps create.

AI TV INFO — TECHNOLOGY • ECONOMY • INNOVATION

Reporting focus: Artificial intelligence, inclusive economic development, emerging-market innovation and the future of work.