By synthesizing identity, inclusion, and innovation, India stands poised to transition from a digital powerhouse to a global artificial intelligence (AI) contender. But the race is far from over—and the next lap demands more than just momentum.
India’s digital transformation over the past decade is not merely a case study in technological adaptation—it’s a masterclass in scalable innovation. As Neha Sahni, Director and Global Market Strategist at HSBC Global Private Banking and Wealth, writes, “India’s tech innovations in the last 10 years have been nothing short of a tech alchemy – transforming the nation and pushing out its productivity frontier”¹. This transformation, underpinned by India’s Digital Public Infrastructure (DPI), known as the “India Stack,” has democratized access to finance, identity, and data at scale—laying the groundwork for a broader leap into artificial intelligence.
From JAM to GDP: The Rise of India's Digital Infrastructure
At the heart of India’s digital evolution lies the ‘JAM trinity’—Jan Dhan (financial inclusion), Aadhaar (identity), and Mobile connectivity. The JAM interlink has powered the DPI ecosystem, connecting over 1.3 billion Aadhaar users and nearly 500 million Jan Dhan accounts². Combined with the Unified Payments Interface (UPI) and Account Aggregators, these tools formed the foundation of a third-most-digitized economy—surpassing most developed markets in mobile-enabled transactions and e-governance.
Sahni emphasizes the significance of these developments, noting that “India’s digital economy is growing at twice the pace of the overall economy and projected to become one-fifth of the country’s economy by 2029”³. This leap was made possible by factors including ultra-low mobile data costs—the world’s lowest—and near-universal smartphone penetration⁴.
The AI Arms Race: Brains Over Brawn
But digital maturity alone is no longer sufficient. In what Sahni calls a “global AI arms race,” India must transition from consumer to creator. The traditional advantage of cheap labor and scalable services is no match for the current wave of AI, which rewards intellectual capital, data richness, and algorithmic refinement.
“In this AI race, brains will conquer the brawn,” Sahni asserts, citing the rise of models like DeepSeek that demonstrate the potential of lightweight, efficient architectures over mere computational horsepower⁵. India’s path forward hinges not on building the next ChatGPT but on creating indigenous AI suited to its own linguistic, economic, and cultural context.
India’s AI Readiness: Building Blocks and Gaps
India is not starting from zero. Its existing digital stack, combined with a thriving startup ecosystem already deploying AI tools, gives the nation a head start. Sahni identifies four strategic levers for indigenous AI development:
- Upskilling and retaining tech talent
- Creating public repositories of unleveraged data
- Enhancing AI R&D capabilities
- Deploying India’s unique “frugal innovation” mindset⁶
These priorities reflect both opportunity and necessity. India’s AI contribution to GDP is estimated to hit $1 trillion by 2027, potentially creating over 30 million jobs⁷. Yet, Sahni warns that standing still equates to falling behind, particularly when the U.S. and China are accelerating investment in sovereign AI stacks.
Spotlight on Language Tech and Bhashini
India’s unique multilingual landscape—home to 22 official languages and hundreds of dialects—poses a structural challenge to AI adoption, but also a competitive edge in Natural Language Processing (NLP). The government’s “Bhashini” initiative aims to build AI-driven, speech-to-speech translation systems and a Unified Language Interface (ULI) that can operate across India’s vast linguistic tapestry⁸.
“Through this Bhashini platform,” Sahni explains, “it facilitates voice-based access and supports content creation in 22 Indian languages”⁹. These efforts have already produced over 350 AI-based tools, from speech recognition to machine translation.
What India Still Needs: Data, Talent, R&D
Despite progress, Sahni argues that India “ranks only 1st in AI research and 16th in AI infrastructure among the G32 countries”¹⁰. To bridge this divide, the National AI Mission has laid out a seven-pronged strategy: computing infrastructure, data, talent, R\&D, capital, algorithms, and applications.
But in practice, the emphasis remains skewed toward hardware procurement (e.g., GPUs) and Indic language models. For India to lead, Sahni stresses the need to prioritize three enablers:
- Data Infrastructure: “India-specific data remains siloed, unstructured, and untapped… Building a ‘digital public repository’ of Indic language datasets… is the need of the hour”¹¹.
- Talent Pipeline: While India produces the world’s largest STEM graduate pool, “fixing its talent gap in AI… especially when it comes to the quality and job readiness of Indian engineering graduates is critical”¹². Brain drain remains a challenge, though programs like Microsoft’s ADVANTA(l)GE India and the YuvAI initiative are providing hope.
- Research Ecosystem: Sahni calls for a robust ecosystem that supports long-term innovation, emphasizing that India must “produce the next wave of AI innovations for the world”¹³.
Energy as a Strategic Asset
AI is energy-intensive. Recognizing this, India is simultaneously advancing its renewable capacity—solar, wind, and nuclear. “India’s renewable energy production has gone up from 26% to 46% of its energy mix,” Sahni notes¹⁴, adding that the country’s ambition includes 22,480 MW of nuclear energy capacity by 2032.
This commitment to energy security is not a side note—it is a strategic foundation for powering India’s future AI infrastructure at scale.
From DPI to AI: The Next 'Tech-tonic' Shift
India has already redefined what is possible through public digital infrastructure. Now it must turn that foundation into a launchpad for AI leadership. If successful, Sahni concludes, “AI will be able to turbocharge the benefits of its Digital Public Infrastructure and unleash enormous economic and social positives at scale”¹⁵.
With the pieces falling into place—talent, data, R\&D, infrastructure, and an innovation mindset—the next phase of India’s digital journey promises not just transformation, but global leadership.
Footnotes:
- Sahni, Neha. India’s Tech-tonic Shift: From DPI to AI. HSBC Global Private Banking and Wealth, Apr. 2025, p. 1.
- Ibid., p. 2.
- Ibid., p. 4.
- Ibid., p. 5.
- Ibid., p. 6.
- Ibid., p. 6.
- Ibid., p. 6.
- Ibid., p. 8.
- Ibid., p. 8.
- Ibid., p. 9.
- Ibid., p. 10.
- Ibid., p. 10.
- Ibid., p. 10.
- Ibid., p. 11.
- Ibid., p. 6.
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