Whalesbook
Developing India's own artificial intelligence capabilities is crucial, not just for technological advancement, but for capturing the economic benefits. As India aims for global AI leadership, a key concern is becoming a 'follower' rather than a 'leader' in setting AI standards. This could mean forfeiting substantial economic gains from owning the AI development process. This echoes past industrial shifts where major value creation often benefited dominant global companies. The current AI era requires proactive, strategic development to ensure India profits from its growing digital economy.
Building India's Own AI
Industry leaders warn that India's ambition to become an AI powerhouse depends on building its own core AI capabilities, trusted infrastructure, and globally competitive products, rather than just relying on foreign technology. This drive for 'domestic AI' stems from recognizing that AI will be fundamental to future economic growth across all industries. The urgency is heightened by AI's rapid development, which could outpace policy and workforce readiness. Major investments are flowing into data center expansion. Projections show capacity could increase fivefold by 2030, reaching over 8 GW. Companies like Yotta Data Services are investing over $2 billion to build AI superclusters. They plan to deploy thousands of Nvidia Blackwell GPUs by August 2026, placing India among a few locations capable of large-scale AI infrastructure. This expansion is vital for training complex AI models. Sarvam AI, for example, is reportedly working to train a trillion-parameter model. The IndiaAI Mission also supports this by encouraging domestic AI development and providing access to computing power.
Turning Data into Economic Gain
Beyond infrastructure, a key challenge is India's difficulty in translating its vast data into proportional economic value. India generates significant digital content and data, but much of its value currently benefits global platforms. This imbalance highlights the need for domestic AI models and systems capable of processing and profiting from local data. Sarvam AI, founded by Pratyush Kumar and Vivek Raghavan, is a key player. They are developing large language models (LLMs) designed for Indian languages and specific uses. The company is reportedly close to a significant funding round, valuing it between $1.5 to $1.6 billion, showing strong investor interest in India's domestic AI initiatives. The overall Indian AI market is projected to grow substantially, reaching an estimated $27.7 billion by 2032, with a compound annual growth rate (CAGR) of 19.2%. Focusing on domestic capabilities is considered essential to avoid repeating past mistakes from industrial eras, where India was mainly a user and missed out on key value creation.
AI's Impact on Jobs and Skills
AI's rapid evolution presents both opportunities and significant challenges for India's workforce. While AI is expected to create millions of new jobs, estimates suggest significant job losses could occur in sectors like manufacturing and retail. Projections show AI could create 40 million new jobs by 2030, but also displace millions through automation. This necessitates large-scale reskilling and upskilling programs. The uncertainty around future job markets and value creation points to the pervasive influence of AI. India's AI strategy success is tied to its ability to prepare its workforce for these transformative changes, aligning talent development with the fast-evolving AI-driven industries.
Facing Global Competition
Despite strong domestic progress and rising investment, India faces intense global competition. China, for instance, is rapidly advancing in AI applied to physical tasks and robotics, controlling key components like lidar sensors and leading in industrial robot installations. China's integrated approach, using its EV supply chain for robotics parts, provides a cost advantage and a clear strategy for dominating the future of AI in physical applications. This lead in AI for physical tasks, where machines operate autonomously in the real world, poses a significant challenge for India. Additionally, global AI computing power is concentrated among a few tech giants, creating reliance on foreign semiconductors and cloud services. While India is expanding its data center capacity, reliance on foreign-made chips and core AI models remains a critical vulnerability. Without a clear national AI strategy, execution could falter, further cementing India's role as a tech follower. For investors, the AI race is increasingly about capturing value. Any misstep in strategy or infrastructure could cede significant economic ground to competitors.
Next Steps for India's AI Future
Navigating this complex landscape requires a coordinated effort from private industry, government, and academia. Industry leaders emphasize substantial private investment in AI infrastructure and research and development to stay competitive against global tech firms. This includes not only computing power but also developing local talent and addressing the risks of AI adoption. Speakers agreed on building globally competitive tech firms, rather than focusing solely on restricting access to international AI companies. Robust local data center capacity, supported by companies like Yotta Data Services, is crucial, even though chip supply chains remain global. The way forward requires a coordinated strategy where developing domestic control at critical points fosters innovation and long-term competitiveness, rather than solely focusing on risk mitigation.