The Union Budget 2025-26 has put artificial intelligence in focus, with Finance Minister Nirmala Sitharaman announcing the establishment of a Centre of Excellence for AI in education with an outlay of Rs 500 crore. This follows the three CoEs announced in 2023 for AI in agriculture, health, and sustainable cities. Additionally, five National Centres of Excellence for Skilling, set up in collaboration with global partners, aim to equip India’s workforce for an AI-driven future. But the question remains—are these steps enough to position India as a global leader in AI, or do they merely scratch the surface of what’s needed?
The government’s commitment to skilling is evident in the Budget’s emphasis on Centres of Excellence for AI training. Given the rapid integration of AI in various industries, skilling initiatives are essential to mitigate job displacement risks. The Economic Survey 2024-25 underscores this concern, stating that India’s workforce, particularly in low-value-added services, is vulnerable to automation. To address this, it calls for the creation of “stewarding institutions” that can guide workers into medium- and high-skilled jobs where AI complements rather than replaces human effort.
READ | Rural economy: Policy levers for agricultural prosperity
While skilling initiatives are a crucial step, they are not enough. The Economic Survey points out that a holistic approach requires not just education and training but also robust institutional frameworks to balance innovation with societal costs. Without a well-thought-out AI adoption strategy, India risks falling into the trap of technological unemployment rather than reaping the benefits of AI-driven productivity gains.
Funding AI: A Drop in the Ocean?
A Rs 500 crore outlay for an AI Centre of Excellence in education is a welcome move, but it pales in comparison to the scale of investments made by AI leaders like the US and China. India’s AI funding remains fragmented, with limited allocation towards foundational AI research. As highlighted in a recent report by the Australian Strategic Policy Institute (ASPI), China has not only outpaced India in research volume but also in the quality of AI publications. The gap in high-impact AI research suggests that India needs a much larger and sustained investment in AI infrastructure, research grants, and talent retention.
Moreover, while the budget proposes subsidized cloud computing infrastructure for AI startups, the effectiveness of this initiative hinges on efficient execution. The current plan of having bureaucrats vet applications raises concerns about the agility and fairness of access. Instead, a dynamic AI innovation ecosystem driven by industry-academia collaboration is needed.
India’s AI Research: The Missing Piece
AI leadership is not built on skilling initiatives alone—it requires cutting-edge research. China’s AI dominance is driven by high research output in critical technologies, with significant government backing for universities and research institutions. The ASPI report underscores India’s lag in AI research, where quantity does not match quality. Without a strong research ecosystem, India’s AI ambitions will remain dependent on global players rather than fostering homegrown innovations.
India’s policymakers must rethink their approach to AI research. Rather than focusing solely on applied skills, universities should be encouraged to push the frontiers of knowledge. Unfortunately, as the ASPI report suggests, Indian universities are increasingly being reduced to “skill imparting centres” rather than hubs of groundbreaking research. Without strong foundational research, India’s AI sector will struggle to compete globally.
Balancing AI’s Promise and Pitfalls
The Economic Survey 2024-25 rightly warns that AI-driven automation could lead to significant labour displacement, especially in the lower wage quartiles. Historical precedents suggest that technological revolutions have often led to economic hardship before benefits are fully realized. India, with its vast labour force and relatively low per capita income, is particularly susceptible to such disruptions.
To navigate this transition, the Economic Survey proposes a tripartite compact between the government, private sector, and academia. This approach aims to ensure that AI adoption is inclusive and aligned with national economic goals. However, implementing such a framework requires strong governance, clear policy roadmaps, and accountability mechanisms—none of which were explicitly detailed in the Budget 2025-26.
The Road Ahead: AI Leadership Beyond Rhetoric
India’s AI aspirations need more than budgetary allocations—they demand structural reforms, institutional support, and a long-term vision. Key priorities should include:
Substantial R&D Investment: AI leadership requires massive funding in research, akin to what China and the US are doing. India needs dedicated AI research funds, tax incentives for R&D, and public-private partnerships to develop homegrown AI technologies.
Industry-Academia Collaboration: Instead of bureaucratic control over AI infrastructure, industry and academia should jointly drive AI innovation. A robust AI research ecosystem, supported by leading universities, is essential to enhance India’s competitiveness.
Responsible AI Governance: The Economic Survey’s call for stewarding institutions is critical. India must establish regulatory frameworks that promote ethical AI development while avoiding overregulation that stifles innovation.
A Nationwide AI Adoption Strategy: Beyond isolated initiatives, India needs a national AI mission with a clear roadmap—one that integrates AI into public services, manufacturing, and critical sectors while ensuring workforce adaptability.
Conclusion: A Promising Start, But Not Enough
The Union Budget 2025-26 has set the stage for AI expansion, but it falls short of positioning India as a global AI leader. The initiatives announced—though positive—are fragmented and insufficient compared to the scale of the challenge. Without a deeper commitment to AI research, stronger institutional frameworks, and significant investments, India risks being a participant in the AI revolution rather than a leader.
As the saying goes, learning to kick a ball straight is just the beginning; it does not make one Lionel Messi. Likewise, India’s AI ambitions require more than budgetary allocations—they need a long-term, strategic vision that transcends annual policy announcements and fosters a truly transformative AI ecosystem.