🗞️ Why in News The India AI Impact Summit 2026 (February 16–21, Bharat Mandapam, New Delhi) — the fourth global AI summit after Bletchley Park (2023), Seoul (2024), and Paris (2025) — saw PM Modi unveil the MANAV framework for human-centric AI. Meanwhile, NITI Aayog warned that AI could wipe out 2.7 million tech jobs by 2031, and India’s plan to become a global data centre hub raises serious concerns about water, energy, and carbon emissions.

India AI Impact Summit 2026

  • Venue: Bharat Mandapam, New Delhi
  • Dates: February 16–21, 2026
  • Significance: First AI summit in the series hosted by a Global South nation
  • Previous summits: Bletchley Park AI Safety Summit (UK, 2023) → AI Seoul Summit (South Korea, 2024) → AI Action Summit (Paris, 2025; co-chaired by PM Modi and President Macron)
  • Key outcome: New Delhi Declaration on AI governance
  • Bill Gates pulled out as keynote speaker

The MANAV Framework

PM Modi unveiled MANAV (meaning “human” in Hindi) — India’s vision for AI governance:

Letter Pillar Meaning
M Moral and Ethical Systems AI must be rooted in fairness, transparency, and human oversight
A Accountable Governance Transparent rules and robust oversight mechanisms
N National Sovereignty Data sovereignty, algorithmic sovereignty, and digital infrastructure sovereignty
A Accessible and Inclusive AI must not be a monopoly but a multiplier — especially for the Global South
V Valid and Legitimate Trust, safety, legality — AI systems must be verifiable, lawful, and transparent (especially regarding deepfakes and synthetic media)
Key Principles
  • Transform AI from machine-centric to human-centric
  • AI must not reduce human beings to “mere data points or raw material”
  • Democratise AI as a medium of inclusion and empowerment
  • Ensure “the welfare of all, the happiness of all” (Sarve Bhavantu Sukhinah philosophy)

⊕ Supplementary UPSC Concepts (Additional Material)

The following sections provide supplementary explanatory material with key concepts for UPSC beyond the article.

UN “AI for Good” Initiative — Context for MANAV

  • Launched: 2017 by ITU (International Telecommunication Union) — the UN’s specialised agency for digital technologies
  • Partners: 53+ UN organisations, co-convened with Government of Switzerland
  • Goal: Identify practical AI applications to advance the UN Sustainable Development Goals (SDGs)
  • Scale: 37,000 contributors from 180+ countries
  • Annual summit: AI for Good Global Summit held in Geneva since 2017
  • Relevance: MANAV framework draws on similar principles but frames them as an Indian philosophical contribution — the article notes “not many here appear to be aware” of the UN’s existing initiative

IndiaAI Mission — India’s AI Infrastructure Push

  • Launched: March 2024
  • Budget: ₹10,371.92 crore (~$1.14 billion) over 5 years
  • Compute capacity: ₹4,563.36 crore allocated (44% of total budget — largest single component)
  • GPUs deployed: 38,000 (target was initially 10,000); 70% high-end NVIDIA H100, 30% older models
  • Subsidised rate: ₹65/hour for AI startups and researchers
  • Budget trajectory: FY 2024-25: ₹551.75 crore → FY 2025-26: ₹2,000 crore (1,056% increase in revised estimates)
  • 7 pillars: Compute infrastructure, AI innovation centres, datasets platform, application development, skilling, startup financing, responsible AI

Sarvam AI — India’s Sovereign LLM Effort

  • Selected by MeitY (April 2025) under IndiaAI Mission to develop an indigenous foundational AI model
  • Sarvam-30B: 30-billion parameter model (mixture-of-experts design), released February 18, 2026
  • Sarvam-105B (“Indus”): 105-billion parameter open-source LLM, released February 20, 2026
    • Trained from scratch under IndiaAI Mission
    • Supports all 22 official Indian languages (Eighth Schedule)
    • Hosted on Hugging Face under Apache License
  • The article notes Sarvam AI “failed to evoke any excitement” at the summit — reflecting the gap between announcements and ground-level AI capability

What is a Foundational/Large Language Model (LLM)?

  • LLM: A deep learning model trained on massive text datasets to understand and generate human language
  • “Foundational” means it serves as a base model that can be fine-tuned for specific applications
  • Parameters: The “weights” that the model learns during training — more parameters generally means more capability (GPT-4: ~1.8 trillion; Sarvam-105B: 105 billion)
  • Sovereign AI: The concept that nations should develop their own AI models and infrastructure to avoid dependence on foreign (primarily US) companies — a key concern for data privacy and national security

The Jobs Crisis — NITI Aayog Warning

The Report
  • Title: “Roadmap for Job Creation in the AI Economy”
  • Released: October 2025
  • Developed by: NITI Aayog’s Frontier Tech Hub with NASSCOM and BCG
Key Findings
  • AI could wipe out 2.7 million jobs in tech services by 2031
  • Tech services employ 13% of total workforce and over 30% of white-collar talent
  • Headcount could fall from 7.5–8 million to 6 million by 2031
  • Customer services sector: 2–2.5 million to 1.8 million
  • Centre of Advanced Study in India: Over 60% of formal sector jobs vulnerable to AI automation by 2030
  • India’s share of granted AI patents fell from 8–10% (2010) to under 5% (2023)
The Three Major Challenges
  1. Scale of jobs at risk — millions in the flagship tech sector
  2. Fundamental shortcomings in education and skills — curriculum and skilling cycles too slow
  3. Growing shortage of AI talent — paradox for a country with the world’s largest pool of young digital talent
Proposed Solution
  • India AI Talent Mission — nationally coordinated programme to equip the workforce for AI disruption
  • AI is “advancing faster than policy, curriculum, and skilling cycles can adapt to”
  • Risk: not just irreversible job losses, but “broader societal disruption, economic marginalisation, and weakening of global competitiveness”
  • The report also notes potential to create 4 million new jobs — but only with urgent reskilling

The Data Centre Gamble — Environmental Cost

The Plan
  • India pitching itself as a global hub for AI data centres
  • PM invited “all of world’s data to reside in India”
  • Expected investment: $200 billion — Google, Amazon, Microsoft have made commitments
  • Google: Setting up a 1 GW data centre in Visakhapatnam (243 hectares)
Why It Won’t Solve the AI Problem
  • AI behemoths do not share data or technology — hosting their data centres doesn’t transfer AI capability to India
  • Data centres are irrelevant to developing foundational LLMs — India needs its own models, not server farms for US companies
  • Employment generation will be minimal (data centres are largely automated)
The Environmental Cost
Resource Current (2024–25) Projected (2030)
Data centre capacity ~1.5 GW 4.5–17 GW
Electricity consumption ~0.5% of national grid 8% of national energy
Water consumption 150 billion litres/year 358 billion litres/year
  • A 100 MW data centre consumes over 2 million litres of water daily
  • 60–80% of India’s data centres will face high water stress (S&P Global)
  • Most centres in water-scarce cities: Mumbai, Chennai, Hyderabad, Bengaluru
  • India still relies on coal-based power — data centres add to carbon emissions
  • More than half of India’s districts face high risk from extreme heat → data centres in these areas need higher cooling loads
  • No carbon emissions framework specific to data centres exists in India
  • No mandatory EIA for data centres

Critical Evaluation for UPSC Mains

The Fundamental Contradiction
  • India simultaneously claims AI leadership (MANAV, sovereign AI) while lacking the basic infrastructure — specialised chips (GPUs are all imported), trained talent, and foundational models
  • The data centre strategy serves foreign AI companies, not Indian AI sovereignty
  • MANAV’s “national sovereignty” pillar is undermined by the data centre plan — India becomes a service provider (hosting data) rather than an AI power (creating models)
  • The jobs crisis timeline (5 years) is alarmingly short — reskilling 2.7 million workers requires institutional speed that India’s education system has not demonstrated
The Digital Divide Dimension
  • AI disruption will disproportionately affect lower-skilled tech workers — the very population that the IT boom lifted into the middle class
  • Rural India remains disconnected — 59% internet penetration (2024), significant urban-rural gap
  • MANAV’s “accessible and inclusive” pillar requires bridging this gap first
The Environmental Trade-off
  • Data centres consuming 358 billion litres by 2030 while India faces worsening water stress (Jal Jeevan Mission struggling to deliver)
  • Coal-powered data centres contradicting Net Zero 2070 target
  • The irony: hosting “green” AI infrastructure using coal-generated electricity

UPSC Angle

  • Prelims: MANAV framework (full form), India AI Impact Summit 2026 (venue, dates), IndiaAI Mission (budget: ₹10,372 crore), NITI Aayog AI jobs report, Sarvam AI, LLM, AI for Good (ITU, 2017), Bletchley Park/Seoul/Paris AI summits, NASSCOM, data centre water consumption, sovereign AI
  • Mains GS-2: Governance — AI governance frameworks, MANAV vs international frameworks (EU AI Act, UNESCO AI Ethics), digital sovereignty, government initiatives (IndiaAI Mission)
  • Mains GS-3: Economy — AI disruption of tech services, job losses vs job creation, India’s AI patent decline, data centre economics; Environment — data centre water/energy footprint, coal-based power for AI, carbon emissions; Science & Technology — LLMs, foundational models, GPU infrastructure, AI sovereignty
  • Essay: “India’s AI future cannot be built on other nations’ data — it must be built on its own talent and values”

📌 Facts Corner — Knowledgepedia

India AI Impact Summit 2026:

  • Dates: February 16–21, 2026; Venue: Bharat Mandapam, New Delhi
  • 4th global AI summit (after Bletchley Park 2023, Seoul 2024, Paris 2025)
  • First AI summit hosted by a Global South nation
  • New Delhi Declaration on AI governance adopted

MANAV Framework:

  • M: Moral and Ethical Systems
  • A: Accountable Governance
  • N: National Sovereignty
  • A: Accessible and Inclusive
  • V: Valid and Legitimate
  • Unveiled by PM Modi at the summit

NITI Aayog AI Jobs Report (October 2025):

  • Title: “Roadmap for Job Creation in the AI Economy”
  • Developed with NASSCOM and BCG
  • 2.7 million tech jobs at risk by 2031
  • Tech services: 7.5–8 million → 6 million (by 2031)
  • 60% of formal sector jobs vulnerable to AI automation by 2030
  • India’s AI patents: 8–10% (2010) → under 5% (2023)
  • Solution proposed: India AI Talent Mission

IndiaAI Mission:

  • Launched: March 2024; Budget: ₹10,371.92 crore over 5 years
  • Compute: ₹4,563.36 crore (44% of budget)
  • GPUs: 38,000 deployed; 70% NVIDIA H100
  • Subsidised rate: ₹65/hour

Sarvam AI:

  • Selected by MeitY under IndiaAI Mission (April 2025)
  • Sarvam-30B: 30B parameters (Feb 18, 2026)
  • Sarvam-105B “Indus”: 105B parameters, 22 Indian languages (Feb 20, 2026)
  • Open-source, Apache License, on Hugging Face

Data Centre Environmental Impact:

  • Current capacity: ~1.5 GW; projected by 2030: 4.5–17 GW
  • Water: 150 billion litres (2024) → 358 billion litres (2030)
  • 100 MW centre = 2 million litres water/day
  • 60–80% of India’s data centres face high water stress
  • Google: 1 GW centre in Visakhapatnam (243 ha)
  • No EIA or carbon framework for data centres in India

AI for Good (UN/ITU):

  • Launched: 2017 by ITU (International Telecommunication Union)
  • 53+ UN organisations as partners
  • 37,000 contributors from 180+ countries
  • Annual summit in Geneva since 2017

Other Relevant Facts:

  • EU AI Act: world’s first comprehensive AI regulation (entered force August 2024)
  • UNESCO Recommendation on Ethics of AI: adopted November 2021 (193 countries)
  • Global AI summit series: Bletchley Park (2023) → Seoul (2024) → Paris (2025) → New Delhi (2026)
  • India internet penetration: ~59% (2024); urban-rural digital divide persists
  • Net Zero 2070: India’s long-term climate target
  • NASSCOM: National Association of Software and Services Companies (India’s IT industry body)

Sources: Down to Earth, NITI Aayog, PIB, IndiaAI Mission, ITU