Peripheral power of adoption and talent
By Javier Surasky
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India occupies a singular place on the artificial intelligence power map.
Its
relevance can be explained by the availability of human talent, installed
innovation potential, and adoption capacity, but the element that makes it
definitively different from other actors lies in its social scale, its digital
public infrastructure, and its capacity to use AI as a lever for development:
“India’s scale and opportunity landscape provides the ideal test-bed to ensure
sustainable and scalable solutions” (NITI Aayog, 2018, p. 18).
Unlike the
U.S. and Chinese models, India’s model lies in the possibility of deploying AI
across a massive population approaching 1.5 billion people: a gigantic digital
market within an economy projected to grow by around 6.5% in 2026
(International Monetary Fund [IMF], 2026).
The country
has turned its digital public infrastructure into an asset for administrative
modernization, financial inclusion, and international projection, especially
through systems such as Aadhaar and UPI, as well as the Digital Public
Infrastructure approach promoted within the framework of the G20 (Press
Information Bureau [PIB], 2024a, 2026).
Added to
this is the steady generation of human talent, an element I consider as
important as data, computing power, and infrastructure for the development of
AI. The country has a broad base of professionals in engineering and
programming, together with technology services companies and a large number of
connected users (Deloitte & NASSCOM, 2024; IndiaAI, 2024).
From an AI perspective, these conditions give India the opportunity to become
one of the world’s largest laboratories for the social, business, and state
application of digital technologies.
Along these
lines, the Indian government, led by Narendra Modi since 2014 and with a third
term that began in June 2024, has integrated digitalization into its national
strategy for development and administrative modernization (Reuters, 2024a; PIB,
2026), and has turned it into an asset of its foreign policy, using its
position within the BRICS to increase its weight as a leader of the Global
South.
This search
for international positioning was also visible at the AI Action Summit in
Paris, held on February 10 and 11, 2025, which India co-chaired with France.
The IndiaAI
Mission strategy stands out as a political node for connecting the mass
adoption of AI with technological sovereignty, making the country a power in
applied AI: adopted by the government on March 7, 2024, it has a budget
allocation of nearly USD 1.25 billion to develop the national AI ecosystem over
five years, under the slogan “Making AI in India and Making AI Work for India”
(PIB, 2024b, 2024; PIB, 2025).
However,
its objective is primarily political, not technical: to address the problem of
having scale, talent, and a market, but not controlling the critical layers of
AI, such as computing, chips, cloud, foundation models, quality datasets, and
alignment with technical standards (IMF, 2026; Deloitte & NASSCOM, 2024).
This becomes clear when looking at its seven pillars: IndiaAI Compute Capacity,
IndiaAI Innovation Centre, IndiaAI Datasets Platform, IndiaAI Application
Development Initiative, IndiaAI FutureSkills, IndiaAI Startup Financing, and
Safe and Trusted AI (PIB, 2024b; IndiaAI, n.d.).
This
reveals a key point for understanding India’s role within the AI ecosystem: the
country sees this technology as a layer capable of linking its digital public
infrastructure, state services, digital financial system, administration,
social policies, business services, and ambitions for leadership in the Global
South.
Three of the pillars on which the country supports its claims are:
- The presence of major Indian technology companies with global reach, such as Tata Consultancy Services, better known as TCS, Infosys, Wipro, and HCLTech.
- A network of universities, Indian Institutes of Technology, startups, and a technological diaspora that connects the Indian ecosystem with global centers of technological power.
- An existing digital architecture, India Stack, which links identity, payments, and data as population-scale services (Arner et al., 2025).
On this
basis, it can be argued that India occupies an intermediate position within the
global AI map: because of its assets, it cannot be understood simply as a
subordinate power, but neither is it a sovereign AI power, because it depends
on critical technological infrastructures that it does not control.
This
position leads India to cooperate with the United States, create programs to
attract Big Tech companies, maintain ties with foreign firms, and play a
leading role in the actions of global forums, while presenting itself as a
voice of the Global South, avoiding alignment with any one technological power
and instead pursuing strategic autonomy by negotiating with several centers of
power (Ministry of External Affairs [MEA], 2024a, 2024b).
Here, a structural tension in India’s position appears: the more it integrates into the global Big Tech ecosystem, the harder it will be to convert national AI
adoption into real technological sovereignty.
India also
faces a challenge that comes from AI itself: the concrete risk that its use
will displace part of the tasks that made the national outsourcing sector
strong, especially in back-office work, call centers, basic programming, and
repetitive services (Reuters, 2026a, 2026b).
Support for
startups can be read as a strategy to face that risk by creating new positions
in the development of sectoral and contextualized solutions, beginning by
responding to domestic demand itself, arising from the existence of local
languages, and in critical areas such as health, agriculture, mobility, and
financial inclusion (IndiaAI, n.d.; PIB, 2025). If the Indian entrepreneurial
ecosystem builds solutions adapted to these conditions, the country could
become an exporter of those solutions to countries facing similar difficulties.
Perhaps for
that reason, one of the main narratives of the Indian model is associated with
inclusive and multilingual AI.
Despite
that initiative, AI raises issues in India related to privacy, surveillance,
algorithmic discrimination, state opacity, platform control, freedom of
expression, and equitable access to services (GIGA, 2024; OECD, 2024),
presenting a narrative different from the one defended mainly by Indian and
international civil society organizations.
This narrative dispute is another crucial element for understanding the situation of
AI in India and leads us to argue that, for that country, its main strength
lies in its possibility of turning AI into social infrastructure for
development, its greatest vulnerability lies in its dependence on critical
technological layers controlled by external actors, and its main challenge lies
in transforming mass adoption into technological sovereignty without falling
into dependence on Big Tech or becoming a surveillance state.
Basic data
- India has an approximate population of 1.476 billion people, a massive digital market, an economy projected to grow by around 6.5% in 2026 (IMF, 2026), and a broad base of technical talent.
- India’s AI market could reach USD 17 billion in 2027, with an estimated annual growth rate of between 25% and 35% (Reuters, 2024b).
- Projected demand for AI talent in India exceeds 1.25 million people by 2027, compared with an estimated base of 600,000 to 650,000 between 2022 and 2023 (Deloitte & NASSCOM, 2024).
- Narendra Modi’s government is advancing an agenda of digitalization, technological development, digital public infrastructure, and international positioning.
- The IndiaAI Mission strategy functions as the central axis of the country’s state strategy to develop national AI capabilities. One of its pillars is the creation of national computing infrastructure for AI, with more than 10,000 GPUs planned to be available through public-private partnerships (PIB, 2025; IndiaAI, n.d.).
- The Indian ecosystem brings together major technology services companies such as TCS, Infosys, Wipro, and HCL with AI startups, universities, and scientific and technological research institutes.
- The main tension in the Indian model lies between technological sovereignty and external dependence.
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