From Silicon Valley to Nairobi: What the Global South’s AI leapfrogging teaches tech leaders
When I write about the cognitive migration now underway, brought about by the rapid advance of gen AI, I do so from the perspective of someone who has spent four decades in the technology industry. My own journey runs from coding business applications in Fortran and COBOL to systems analysis and design, IT project management, enterprise systems consulting, computing hardware sales and technology industry communications. All of it has been centered in the U.S., although I have collaborated with colleagues and clients across Europe and Asia.My writing carries an American, tech-industry vantage point, although I make attempts to see a broader perspective. Perhaps that is fitting, since much of the frontier development of AI remains clustered in Silicon Valley, Seattle, Boston and a handful of other Western hubs. But how does this migration look beyond America’s borders? For millions in the Global South, cognitive migration is less about the loss of white-collar prestige and more about the chance to leapfrog into new opportunities.This divide is visible in the data. The 2025 Edelman Trust Barometer found that fewer than one in three Americans feel comfortable with businesses using AI, while in India, Indonesia and Nigeria nearly two-thirds express comfort. In the West, AI may be perceived to threaten job loss and displacement, and this view may be warranted. A study by the International Monetary Fund (IMF) found that 60% of jobs in advanced economies are exposed to the impact of AI due to the prevalence of cognitive-task-oriented jobs. The Wall Street Journal quoted Ford CEO Jim Farley: “AI will leave a lot of white-collar people behind.”In the Global South, however, AI is often perceived as an opportunity to improve education, strengthen healthcare, modernize agriculture and drive development. One analysis argues that for the Global South, “AI holds tangible promise for nations historically excluded from the benefits of previous industrial revolutions.” Perhaps this explains the findings reported by Academia.edu that Global North newspapers publish more negative AI headlines, while Global South outlets emphasize opportunity. Yet the story is not so simple. Even where the potential for advancement is emphasized, there is often also worry about loss of work, ethics, algorithmic bias, access and technical capacity. As with earlier waves of globalization, gains and risks will be distributed unevenly.AI as opportunityThere is a strong positive narrative around AI in the Global South, with many hopeful stories and promising results. In Nigeria, a World Bank-funded after-school tutoring program that used AI to tailor lessons to individual students produced striking results with nearly two years of learning gains in just six weeks. For communities with few qualified teachers, such gains are not incremental improvements. They can transform futures. Healthcare applications provide comparable stories. In India, Boston Consulting Group reports that AI diagnostic tools are being deployed in rural clinics with few doctors, offering screenings for conditions such as breast cancer or tuberculosis that might otherwise go undetected. These tools extend the reach of limited health resources and help detect conditions before it is too late.The use of AI in agriculture also shows promise. In Kenya, the PlantVillage Nuru app developed with Penn State University uses AI to detect crop diseases through farmers’ smartphones, equipping them to spot and treat threats to their harvests early. For households that depend on subsistence farming, such tools can mean the difference between security and scarcity.Yet many of these breakthroughs rely on Northern institutions, creating benefits but also exposing a fragile dependency. When outside funding or partnerships end, local efforts can stall. In this sense, leapfrogging risks being built on borrowed foundations.Taken together, these examples illustrate why many in the Global South see AI as a chance to transform trajectories rather than repeat old patterns. Yet optimism tells only part of the story. Alongside these gains are deep structural challenges that complicate the journey, reminding us that this migration, like all others, carries benefits that include hidden costs.Barriers to progressResearch also shows that AI adoption across the Global South is hindered by persistent gaps in infrastructure, data, skills and governance. Availability of reliable electricity and broadband remains uneven, local datasets are often scarce or biased and many countries face shortages of trained professionals to develop and oversee AI systems. Without strong regulatory frameworks, societies are also more exposed to privacy risks, exploitative labor practices and algorithmic bias. These realities mean that while AI holds promise as a development pathway, it can also deepen inequality if its benefits concentrate in urban centers and among elites, while leaving rural communities behind.So why do surveys of trust show higher comfort with AI in the Global South than in the West? One explanation lies in expectations. In the U.S. and Europe, AI is often perceived as a threat to stable jobs and established professions. In Nigeria, India or Indonesia, by contrast, it is more likely to be framed as a tool for closing persistent gaps. Media narratives often reinforce the divergence in expectations. In the West, headlines emphasize automation anxiety, while in the Global South, AI is more often described as a development pathway. Add to this the fact that many people in the Global South report higher levels of trust in institutions overall, and the disparity begins to make sense. The same technology intersects with different baselines, diverse needs, distinct cultures and different stories, which shape whether AI is welcomed with suspicion or with hope. Yet beyond these perceptual differences lie material realities that complicate the optimistic narrative, particularly in how global AI development distributes both its benefits and its burdens.Hidden costsEvery migration carries costs alongside gains, and the story of AI in the Global South is no different. While the overall AI narrative in the Global South leans positive, many celebrated breakthroughs depend on large workforces doing essential yet hidden tasks. Data annotation and content review are indispensable to the global AI economy, but the work is repetitive, emotionally taxing and poorly paid relative to the value it creates.Other sectors face pressure from a different direction. In India and the Philippines, business process outsourcing and call centers employ millions of workers who support global clients. These roles depend on language, routine cognitive tasks and customer service, the very areas where AI chatbots and automated platforms are advancing fastest.The shift is not immediate, but workers in these industries are already questioning whether the migration now underway will carry them forward or leave them behind. Is cognitive migration a single global phenomenon, or are we witnessing multiple migrations that only appear connected?Many routes, shared destinationIs this the same cognitive migration unfolding everywhere, or are there separate journeys? On the surface, the story looks divided. In the U.S. and Europe, professionals worry about displacement from stable careers and a risk to their lifestyles. In India, Nigeria and Indonesia, AI is often presented as a chance to accelerate development and fill long-standing gaps. These appear to be distinct migrations.Yet, the reality is more entangled. The story of AI in the Global South is not simply one of catching up, just as the story in the West is not simply one of decline. Migration is never only progress or only loss. It is both, with something gained and something given up. For teachers in Nigeria, the gain may be students advancing at unprecedented speed. For call center workers in India, the loss may be jobs once thought secure. For farmers in Kenya, the gain may be healthier crops and steadier harvests. For professionals in Europe or the United States, the loss may be careers reshaped or diminished by automation.This variability in experience is not because AI technology is somehow different in one area or another, but because the lived experiences are diverse. The same systems can seem empowering in one place and threatening in another. An uneven passageWhat lies ahead is still uncertain. But if migration teaches anything, it is that adaptation requires not only resilience but imagination. The task is not to deny what is lost or to celebrate only what is gained, but to recognize both and design wisely for what comes next.This migration is not unfolding along a single path. It is fractured and revealing. The starting points differ, the routes are uneven, and the burdens are not equally shared. In the Global South, AI is often seen as a lever for progress, not a threat to status. But beneath the promise lie the same risks we face everywhere, including extraction without investment, automation without inclusion, innovation without safeguards and deployment without trust. These are not side effects. They are signals. If we ignore them, the cognitive future will be one more story written by the few for the few. As Indonesian policy advisor Tuhu Nugraha has argued in Modern Diplomacy: “As concerns rise globally about AI’s unchecked development potentially destabilizing economies or social cohesion, models from the Global South that emphasize inclusion, trust and reflection can help mitigate those risks before they explode into global backlash.” His warning reinforces the point that inclusion and trust must be part of the design of AI advancement and not assumed.If we pay attention, the Global South may offer not just caution but clarity. The choice is not only whether to design wisely, but whose experience we treat as essential when we do. Because in the end, cognitive migration is not regional. It is a worldwide passage, and how we navigate it together will shape not just the future of AI, but the future of being human.Gary Grossman is EVP of technology practice at Edelman.
