In 2026, the India AI Impact Summit highlighted that artificial intelligence is no longer just a buzzword used by business leaders and tech professionals. It's increasingly seen as a tool for development that should address real-world problems rather than theoretical or technological goals.
Prime Minister Narendra Modi's guiding motto, "Sarvajan Hitay, Sarvajan Sukhaye" (welfare and happiness for all), underscored the need for India to anchor its AI ambitions not just on Silicon Valley benchmarks, but on the realities of its 700,000 villages and nearly half a billion rural citizens.
During this February, world leaders, business executives, and technologists gathered in Delhi, amidst a strong push for inclusion. Their presence demonstrated the importance of technology as a public good and India's growing influence in shaping the global AI agenda. The summit's focus on "People, Planet, and Progress" at its core reflected a shift towards impact-oriented strategies.
However, ambitious plans are only effective if they address the deep-rooted divisions within Indian society. A stark contrast exists between the rural hinterlands, characterized by patchy connectivity, low digital literacy, and limited economic opportunities, and the urban centers brimming with digital infrastructure. India's technology policies are often drafted from the perspective of major cities, but their true efficacy is tested in the villages where the benefits of digital transformation have not yet materialized.
This divide is not merely a matter of geography. Data-driven services in healthcare, education, and business are already benefiting urban India. Rural India, on the other hand, struggles with inconsistent broadband, a workforce that is both precarious and underqualified for modern jobs, and limited institutional capacity. The goal is to leverage technology to create real gains in livelihoods, resilience, and citizenship, rather than simply having access to gadgets.
The key question is whether AI can be used to democratize opportunities instead of perpetuating inequality. This is reflected in the India AI Impact Summit's emphasis on "All-Inclusive Intelligence," a term frequently used by Union ministers. AI should be evaluated based on its ability to improve lives and reduce disparities in care delivery, rather than just its complexity.
This is a systemic and structural challenge. Urban areas benefit from network effects, economies of scale, and concentrated human capital, which enhances the value of AI. Rural areas, however, require technology that is reasonably priced, culturally appropriate, and sensitive to local context. AI interventions must accommodate diverse languages, educational levels, and economic settings.
Consider how AI might be used in agriculture, which employs almost half of India's workforce. If AI-powered market recommendations, soil health prediction models, and precision agricultural technologies are available in local languages and distributed through reliable intermediaries like panchayats or cooperative organizations, they can increase productivity and incomes. While cloud infrastructure investments are significant, a pilot project in personalized, AI-based agricultural extension services could have a much larger multiplier effect on rural incomes.
Another area where AI's inclusion could revolutionize is education. Personalized learning systems, adaptive tutoring in vernacular languages, and mentorship networks mediated through AI could address the disadvantages faced by schoolchildren in remote districts. However, these tools risk being aspirational rather than practical if there isn't concurrent investment in local data infrastructure, reliable electricity, and teacher training.
Studies suggest that AI should be viewed as a complement to human labor, particularly in resource-constrained environments.
The summit focused on how AI might help scale public health surveillance and diagnosis. This makes sense: AI can be a force multiplier for screening, early detection, and resource allocation in states with low doctor-to-patient ratios. Again, the true challenge is to integrate these technologies into the public health system, where they are most needed, in community outreach initiatives and rural primary health centers.
These reflections highlight two interrelated topics. AI integration must be deliberate, not accidental. Market forces alone will concentrate the benefits of AI in urban clusters with higher revenues and richer infrastructure, absent tailored policy design and fiscal incentives. This would widen the gap rather than close it. Second, inclusive AI must reflect India's story, influenced by its linguistic diversity, democratic values, and development goals. It cannot be a one-size-fits-all solution.
This calls for a fundamental shift in mindset. Policymakers and practitioners need to focus on equity issues, such as who gains, who loses, and how the marginalized can exercise agency in an AI-mediated future, rather than simply viewing AI as either disruptive or stable. Local languages, interoperability with rural service delivery, and grassroots capacity building must be prioritized in India's AI governance frameworks. This is reflected in the Summit's characterization of AI for "social empowerment" and "democratizing resources," but the true test will be its application.
Addressing the skills frontier is also critically important. India's demographic dividend has the potential to either promote prosperity or increase inequality. Attendees were warned by Chief Economic Advisor V. Anantha Nageswaran that India risks underutilizing the potential of its youthful labor in the AI era if it does not implement strong upskilling programs. The gap between urban and rural areas will widen if AI develops more quickly than human capital, making young people in rural areas more susceptible to marginalization and displacement.
Ultimately, an ecological strategy that integrates technology, institutions, and human agency is what holds the potential of inclusive AI in India. Making decisions that enable every child in a village school, every farmer in a rain-shadowed area, and every small business owner to take part in and profit from the intelligence revolution is more important than simply providing algorithms.
Although the India AI Impact Summit was a positive step, summits are just the beginning, not the end. Whether India's AI trajectory fills in the gaps that have long limited its promise will be the true test. AI will have failed not only in rural India but also in its own purpose if it only serves to perpetuate already-existing disparities. The improvement of life will be used to gauge AI's value more so than model output.
(Mayank Chandra is a social development leader with over two decades of on-ground experience)