When Narendra Modi opened the India AI Impact Summit 2026 at Bharat Mandapam, he framed artificial intelligence not as a luxury technology but as a developmental tool.
“AI must serve humanity. It must be inclusive, transparent, and rooted in public good,” he told a hall filled with world leaders and technology executives.
Over five days, New Delhi is hosting what could become one of the largest AI gatherings in the Global South: 250,000+ participants, over 800 exhibitors, 600 startups, and 3,000 speakers from more than 40 countries. But behind the spectacle lies a sharper ambition – to position India as a rule-maker, not a rule-taker, in the AI era.
A Guest List That Signals Geopolitics
The scale of attendance is strategic. Among the heads of government present were Emmanuel Macron, President of France; Luiz Inácio Lula da Silva, President of Brazil; Pedro Sánchez, Prime Minister of Spain; and Petteri Orpo, Prime Minister of Finland. Their presence elevated the summit beyond a technology fair into a diplomatic platform.
On the corporate side, the AI industry’s most influential figures were in attendance: Sam Altman of OpenAI, Sundar Pichai of Google, Demis Hassabis of DeepMind, along with leadership from Microsoft, Qualcomm, and Anthropic.
Altman noted during a public session that “India is one of our fastest-growing user bases globally,” highlighting that Indian developers and students are among the most active adopters of generative AI tools. India is not just a market; it is becoming a testbed.
More than 600 AI startups participated in the 2026 India AI Impact Summit in New Delhi, forming one of the largest startup showcases at any AI event globally this year.
These companies were featured at the India AI Impact Expo, where they demonstrated applications across healthcare diagnostics, agri-tech, climate modelling, language AI, fintech, robotics, and enterprise automation.
The scale of participation reflects the rapid expansion of India’s AI ecosystem, which has grown into one of the top three global startup hubs in terms of AI-focused ventures.
Notably, the summit spotlighted 12 indigenous foundation models developed under the IndiaAI Mission by homegrown startups and research consortia. These models are trained on Indian datasets and designed to support multiple Indian languages, addressing the country’s linguistic diversity.
The large startup presence signalled not just innovation density, but a deliberate policy push to position India as both a developer and deployer of AI at a population scale.
The IndiaAI Mission
Unlike previous tech summits heavy on rhetoric, Delhi came prepared with policy architecture. India’s $1.25 billion IndiaAI Mission, approved in 2024 and expanded in 2026, aims to build a national AI compute infrastructure, provide subsidised GPU access to startups and researchers, develop Indian-language foundation models, and fund AI innovation centres across universities.
Union IT Minister Ashwini Vaishnaw stated at the summit, “We are not outsourcing intelligence. We are building it here – with our own data, our own talent, our own infrastructure.”
Under the mission, India has committed to deploying more than 10,000 GPUs through public-private partnerships, making compute access significantly cheaper for domestic startups compared to global cloud rates.
The Investment Push
The economic announcements were concrete. Executives from Google, Microsoft, and Amazon reiterated cumulative infrastructure commitments estimated at $65 – $70 billion in India by 2030, largely focused on AI-ready data centres and cloud expansion.
India also used the summit to promote its Semiconductor Mission Phase 2.0, aimed at chip design and fabrication critical for AI sovereignty. Micron’s semiconductor facility in Gujarat was cited as an early example of strategic manufacturing investment.
Ashwini Vaishnaw, speaking on investment momentum, said, “AI investments may top $200 billion, with $90 billion already pledged.”
Economists estimate AI could add $450–500 billion to India’s GDP by 2030 – roughly a 10% boost to projected output – provided productivity gains materialise across sectors.
Altman, in his address, said, “India has all the ingredients: homegrown tech talent, a national strategy, and an infectious optimism about what AI can do for the country.”
Indian Startups At The Centre
The summit gave visibility to domestic AI innovators.
Among those showcased:
Sarvam AI, building multilingual foundation models tailored to Indian languages.
Krutrim, India’s first AI unicorn focused on large language models.
Mad Street Den, applying AI to retail and e-commerce.
Niramai, using AI-driven thermal imaging for early breast cancer detection.
Sarvam AI’s co-founder, Pratyush Kumar, argued during a panel discussion, “If AI speaks only English, it excludes most of India. Language inclusion is economic inclusion.”
This multilingual push directly addresses India’s 22 official languages and hundreds of dialects, a structural barrier to digital access.
Disruption Or Dividend?
Automation anxiety surfaced repeatedly. Industry leaders referenced global projections that 30–50% of repetitive tasks could be automated within the next decade. Yet the dominant narrative was transformation, not elimination.
Sundar Pichai emphasised, “AI will augment human potential. The key is preparing people for new roles we are only beginning to imagine.”
Anantha Nageswaran, Chief Economic Advisor, said, “India can lead the world by aligning AI-led transformation with mass employability.”
India’s demographic profile strengthens this argument. With a median age of 28 and nearly one million engineering graduates annually, the government announced expanded AI skilling initiatives through IITs, NITs, and Skill India programs.
The summit reiterated that if reskilling keeps pace, India could become the world’s largest AI talent reservoir.
AI For Public Systems
Beyond boardrooms, the summit focused on state capacity.
AI-assisted TB detection tools, crop-yield prediction systems, and adaptive learning software were demonstrated. These applications matter in a country where rural access to specialists remains limited.
A policy roundtable emphasised integration of AI with India’s digital public infrastructure – Aadhaar authentication, UPI payments, and digital health records – creating scalable deployment pathways unmatched in most developing economies.
The strategic idea is simple: combine population-scale digital rails with AI tools, and public service delivery could leapfrog traditional constraints.
Algorithmic Bias
Amid the optimism in Delhi’s exhibition halls, a question lingers: What happens when AI systems reproduce the world’s existing inequalities?
A January 2026 study by researchers at the Oxford Internet Institute found that leading large language models, including systems developed by OpenAI and other major firms, were significantly more likely to associate wealth, political stability, and technological advancement with Western, predominantly white-majority countries.
Conversely, queries about African and parts of South Asian regions often surfaced language connected to instability or poverty.
Professor Mark Graham of Oxford warned, “When AI systems consistently frame certain regions as innovative and others as problematic, they risk reinforcing global hierarchies rather than challenging them.”
The implications are not theoretical. If AI tools assist in credit scoring, recruitment filtering, development lending assessments, or even geopolitical analysis, these skewed representations could shape real-world decision-making. In a country like India, where AI adoption is accelerating in fintech, hiring platforms, and public administration, algorithmic bias could silently scale inequality.
India’s linguistic diversity poses a structural challenge. Nearly 90% of high-quality training data globally is in English, while a majority of Indians operate primarily in regional languages. If AI systems are optimised for English-speaking users, they risk embedding a digital caste system, privileging urban, English-speaking populations over rural and vernacular communities.
The summit’s push for multilingual foundation models through startups like Sarvam AI and Krutrim can therefore be read not merely as innovation policy, but as corrective justice in algorithmic form.
Yet questions remain: Who audits these systems? What transparency standards will apply? And can India realistically regulate global AI firms while competing for their investment?
Also Read: Is ChatGPT Biased Towards The Rich, The West, And White People?
The Climate Cost Of Computation
If bias exposes AI’s social risk, climate exposes its physical footprint.
Training a single advanced large language model can emit hundreds of tons of CO₂ equivalent, depending on the energy source. Data centres globally already account for approximately 1 – 1.5% of total electricity consumption, a figure projected to rise sharply with generative AI adoption.
Beyond carbon emissions, water usage is emerging as a major concern. Large-scale data centres require millions of litres of water annually for cooling systems.
As India expands AI-ready infrastructure under the IndiaAI Mission, including thousands of GPUs, questions about energy sourcing become urgent.
India remains heavily dependent on coal, which contributes roughly 70% of its electricity generation. Without a parallel expansion in renewable energy to power AI infrastructure, the climate trade-off becomes stark: can a country vulnerable to extreme heat, floods, and water stress afford compute-intensive growth without green safeguards?
Several summit panels acknowledged this tension. Discussions on “Green AI” focused on model efficiency, renewable-powered data centres, and hardware optimisation. But climate researchers argue that efficiency gains often lag behind demand growth, a phenomenon known as the rebound effect.
In simple terms, as AI becomes cheaper and more powerful, usage explodes, potentially increasing total emissions even if individual models become more efficient.
For India, which has committed to net-zero emissions by 2070, AI expansion must reconcile with its climate diplomacy. Technological leadership cannot come at the cost of environmental vulnerability.
Power, Responsibility, And The Road Ahead
The India AI Impact Summit 2026 marked a decisive moment.
India secured investment commitments, amplified its startups, advanced policy architecture, and positioned itself diplomatically in global AI governance. The economic upside, potentially half a trillion dollars in GDP contribution, is substantial.
But ambition carries responsibility.
Bias in algorithms, environmental costs, workforce disruption, and governance gaps are not peripheral issues; they are central to AI’s future legitimacy.
If India can convert summit energy into sustained policy execution, equitable innovation, and responsible infrastructure growth, this gathering may be remembered not as a spectacle but as the moment India stepped firmly into AI leadership.
Images: Google Images
Sources: The Times Of India, Indian Express, Hindustan Times
Find the blogger: Katyayani Joshi
This post is tagged under: India AI Summit, India AI Impact Summit 2026, AI governance India, Tech policy India, Digital India, Startup ecosystem India, Indian startups, Tech events India, Public infrastructure, Governance accountability, Tech conferences, AI policy, Innovation ecosystem, Startup founders, Journalism India, Ground reporting, Policy implementation, Government events, Bharat Mandapam, Delhi events, Technology and governance, AI India, Digital public infrastructure
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