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