AI in Developing Economies: A Growth Tool or a Barrier to Equity?

By: Aditi Sharma & Sanket Ghodeswar

Introduction

Artificial intelligence (AI) is revolutionizing economies across the globe, remodeling industries, and redefining the future of work. Developed countries are exploiting AI to foster innovation and productivity, while its effects on developing economies are multifaceted. On the one hand, AI brings many opportunities for economic growth, efficiency, and enhanced service delivery. It can help solve age-old problems like poverty, illiteracy, and poor healthcare.

Nevertheless, most developing nations do not possess the required infrastructure, human resources, and regulation to effectively tap into AI. AI-powered automation can replace human labor in industry sectors that rely heavily on it, exacerbating socio-economic imbalances. Also, dependence on AI systems built by the Global North can entrench biases, curtailing developing economies’ agency in determining their technological destiny.

The key question remains: Does AI serve as a tool for inclusive growth, or does it act as a barrier to equity? This article explores AI’s potential to drive economic growth in developing economies while also highlighting the risks it poses to equity and inclusion.

AI as a Tool for Economic Growth in Developing Economies

AI has great potential to stimulate economic development in developing countries through enhanced productivity, innovation, and service sector transformation. Most nations in the Global South are already employing AI-based solutions to address major challenges, enhance livelihoods, and promote industries.

One of the most exciting uses of AI is in agriculture, where it is assisting farmers with data-driven insights. In India, CropIn, an AI-based platform, employs predictive analytics to deliver real-time advisory services. Using satellite imagery and weather data, CropIn assists farmers in minimizing crop loss and boosting productivity. This technology is especially beneficial to small-scale farmers who do not have access to advanced farming practices.

AI is also making governance more robust by enhancing transparency and effectiveness in public services. In Brazil, the government employs AI to identify fraud in social welfare programs, allowing for more effective resource allocation and less corruption. In Indonesia, startup eFishery has created an AI-based smart feeding system that assists fish farmers in maximizing feeding schedules, reducing cost and improving yield. This has greatly increased the productivity and revenue of small-scale fish farmers.

The financial sector is also where AI is shaping economic change. In Nigeria, fintech services such as Paystack and Flutterwave, powered by AI, are increasing financial inclusion by making digital payment services accessible to small businesses. The platforms have simplified it for entrepreneurs to participate in e-commerce, which has led to the expansion of local economies.

In medicine, AI is assisting developing countries in addressing issues of accessibility and affordability. Sophia Genetics, an AI platform, is improving medical diagnostics in Kenya, especially in diseases such as cancer. Also, Rwanda has incorporated AI-based diagnostic tools to enhance healthcare outcomes in rural areas. Also, Zipline, a drone-based system for the delivery of medical supplies, ensures remote locations get necessary medication in a timely manner.

These examples highlight AI’s ability to solve real-world problems, enhance efficiency, and contribute to economic growth. However, despite these advancements, AI also presents significant risks that could hinder equity and inclusive development.

AI in Developing Economies: A Barrier to Equity and Inclusive Development

Although AI can be a great economic development tool, its fast take-up in developing economies is worrying in terms of inequality, bias, and exclusion. AI, if not properly implemented, can increase socio-economic gaps instead of closing them.

Algorithmic Bias and Discrimination

One of the largest fears associated with AI is algorithmic bias. Because AI programs are trained on past data, they tend to mirror and even enhance preexistent social biases. If the data for training AI algorithms are biased, then the results will be biased as well.

For instance, in 2018, Amazon abandoned its AI recruitment tool after it discovered the tool was biased against women. The algorithm learned from previous hiring data that preferred men and consistently dismissed resumes of women, perpetuating gender-based discrimination in hiring. Likewise, AI-based tenant screening software has disproportionately given lower ratings to Black and Hispanic renters, causing housing discrimination.

These examples show how AI, if poorly constructed, can feed into social injustice instead of driving it out. Developing economies, which do not generally have strict AI regulations, are especially open to these biases.

Economic Disparity and Job Loss

AI-based automation threatens jobs immensely, particularly in labor-driven sectors. A 2023 McKinsey report shows that AI could automate 14 million jobs globally by 2030, with developing economies hit the hardest.

For example, in the hotel industry, AI-based self-check-in machines and virtual assistants have resulted in the loss of jobs for hotel employees. Valerie Gills, a U.S. hotel receptionist, lost her job when her company substituted human personnel with automated systems. The same dynamics are unfolding in emerging economies, where lower-skilled workers are most exposed to job loss due to AI.

In Latin America, research shows that nearly 25% of the positions occupied by Latino workers, especially in agriculture and construction, may be displaced through automation by 2030. Without adequate reskilling efforts, AI will increase unemployment levels and expand the economic gap.

Omission of Persons with Disabilities

AI technologies do not consider the requirements of individuals with disabilities, hence causing digital exclusion. The Royal Society for Blind Children (RSBC) released a report, which established that most AI-enabled applications are greatly dependent on visual recognition, which makes them impossible for visually impaired people to access.

Tom Pey, president of RSBC, accused the hasty deployment of AI-based services without disabled users in mind, saying it has shut them out of vital digital services. Unless AI is designed with inclusion in mind, disabled communities in emerging countries could be further marginalized.

AI and Financial Exclusion

As AI transforms financial services, it also threatens financial exclusion. In the UK, the Financial Conduct Authority (FCA) cautioned that AI-powered “hyper-personalization” in banking may render some people uninsurable based on their financial or health record. FCA Chief Nikhil Rathi warned that this might disproportionately impact low-income people, perpetuating economic inequality.

Likewise, in poor countries, AI-based credit scoring algorithms frequently reject loans to those with sparse financial records, limiting their access to funds and business expansion. If not protected against, AI may further exacerbate financial inequalities instead of minimizing them.

Global AI Disparities

The majority of AI technologies are created in the Global North, with minimal regard for the specific challenges of developing economies. As AI researcher Chinasa T. Okolo has argued, this has resulted in a technological gap, where developing countries are unable to implement AI solutions that were originally intended for richer nations.

For example, many AI-enabled farm tools are designed for large farms in the West and thus may not work for small farmers in Africa and South Asia. Without AI solutions specific to local environments, developing economies will be left behind during the digital revolution.

Balancing Growth and Equity: The Way Forward

The challenge is not AI itself, but how it is implemented. AI must be developed and deployed in ways that promote inclusivity rather than deepen inequalities.

Governments must prioritize ethical AI regulations, ensuring that AI systems are transparent, accountable, and free from bias. AI developers should actively work to make algorithms fair and representative of diverse populations.

Equilibrating the development potential of AI with equity needs strategic deployment. Governments need to place ethics-first regulations for AI so that AI systems remain transparent, accountable, and unbiased. Lacking strict policy, AI has the potential to reinforce discrimination and exclusion. The European Union’s AI Act sets a good precedent for AI regulation, imposing strict tests for high-risk applications. Developing countries may implement similar frameworks adapted to their socio-economic contexts. India’s NITI Aayog has recommended responsible AI principles focusing on fairness, transparency, and accountability in AI-based decision-making. Likewise, Brazil’s AI Strategy (EBIA) seeks to foster ethical AI by mitigating bias, promoting inclusivity, and facilitating local innovation. Developing economies can learn from such policies and develop AI regulations that avoid exploitation and ensure fairness.

Investment in digital education and infrastructure is the other key step. Most marginalized populations do not have access to the internet and the skills needed to engage in the AI-enabled economy. Governments and the private sector must come together to extend digital literacy training and prepare workers with AI-relevant skills. For example, Google’s “Grow with Google” program has trained tens of millions globally in digital skills, and such programs could be scaled up to developing nations. In Rwanda, the government has joined forces with global tech firms to establish coding boot camps and AI training courses so that the labor force is equipped for an AI-led future.

AI also needs to be localized for the needs of developing economies. Most AI solutions developed in the Global North fail to address regional challenges, and hence, domestic AI innovations need to come to the forefront. In Kenya, the Sophie Bot, a health chatbot with AI, has been created to offer medical advice in under-served populations. In contrast to other global AI healthcare systems, which are expensive and demand expensive infrastructure, Sophie Bot functions using simple mobile phones, thereby making it accessible to more people. In India, AI translation aids are overcoming the language barrier by providing access to information in a variety of local languages. Support for local AI innovation is important to ensure technology is designed with cultural and economic realities.

Public-private collaborations are important to make AI more inclusive. Governments, technology firms, and universities must collaborate to create AI innovations and policies that are equitable. In South Africa, cooperation between universities and AI startups has resulted in the development of smart agriculture solutions for the country’s local farming conditions. Such partnerships in Latin America have facilitated AI-powered microfinance platforms that evaluate creditworthiness outside of conventional banking information, enabling farmers and small businesses to receive loans.

Making AI-powered solutions inclusive also involves developing them with accessibility in mind. AI tools tend to neglect the needs of disabled people, excluding them from basic digital services. The Royal Society for Blind Children has been concerned with AI-based applications using a lot of visual recognition and leaving out the visually impaired user. In order to correct this, Microsoft’s AI for Accessibility initiative is currently developing solutions like Seeing AI, an app that describes the world to the blind user. Building similar accessibility components in AI programs utilized in the developing world has the potential to close digital gaps.

Ultimately, AI can be a driver of inclusive growth, but only if created and implemented with equity as its foundation. Governments, businesses, and communities need to collaborate to create AI solutions that are equitable, ethical, and specific to the requirements of the varied populations. By focusing on fairness, accessibility, and people-driven development, AI has the opportunity to close healthcare gaps, bring education closer, and increase financial inclusion, leading to an equitable and prosperous future for all.

Conclusion

Artificial intelligence brings with it tremendous opportunities as well as enormous challenges for the developing world. AI can be a catalyst for economic growth, enhance efficiency, and raise the standard of service delivery in agriculture, healthcare, finance, and governance. AI can also widen socio-economic disparities, displace workers, and entrench biases unless there is proper regulation and pro-inclusive policies.

The path forward is ensuring that the development and use of AI is equity- and inclusion-focused. Private and public stakeholders need to collaborate to make ethical AI policies, invest in digital literacy, and develop technology suited to local requirements. Increasing domestic AI innovation can assist developing countries in bridging the technological divide and owning their own digital transformation.

AI is not inherently an instrument of growth or a stumbling block to equity—it is contingent on how it is embraced and regulated. With sound policies and a commitment to equity, AI can be an effective force for inclusive economic growth, enabling developing economies to unleash new opportunities while protecting their social and economic cohesion.

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