National Strategy for Artificial Intelligence #AIFORALL: What It Says and What Came of It

A clear explanation of India's National Strategy for Artificial Intelligence (#AIFORALL), released by NITI Aayog in June 2018: the five priority sectors, the research structure it proposed, the barriers it flagged, and what actually got built between then and the IndiaAI Mission. Plus what the strategy means in practice for students, professionals and institutions.

What #AIFORALL actually is

The National Strategy for Artificial Intelligence #AIFORALL is a discussion paper published by NITI Aayog in June 2018. It is India's first national-level AI strategy document, and it does two things: it picks five sectors where AI should be applied first, and it lays out what India would need to build (research institutions, compute, data, skills) to make that happen. It is a strategy paper, not a law, so nothing in it binds anyone.

The hashtag in the title is not decoration. It carries the actual argument of the document. NITI Aayog explicitly chose not to frame India as competing for AI supremacy against the US and China. The stated goal was inclusive growth, and the phrase used in the paper was that India should become the AI Garage for 40 percent of the world, meaning solutions built for Indian constraints (low resources, many languages, thin infrastructure) could be exported across other developing economies.

The five sectors were chosen on the basis of maximum social impact rather than commercial return.

Focus sector	Why it was picked
Healthcare	Doctor and specialist shortage, poor rural access, screening and diagnostics at scale
Agriculture	Low yields, poor price discovery, crop advisory and pest detection for small farmers
Education	Learning outcome gaps, teacher shortage, personalised and adaptive learning
Smart cities and infrastructure	Rapid urbanisation, traffic, utilities, crowd and energy management
Smart mobility and transportation	Road safety, congestion, autonomous and assisted transport, logistics

The barriers the paper was honest about

The most useful part of the 2018 document is not the ambition. It is the list of things India did not have. NITI Aayog named a shortage of formal AI expertise, the absence of enabling data ecosystems, high compute cost, weak intellectual property frameworks, low awareness of what AI could do for business, and no serious collaborative structure between research, industry and government.

Read that list again and ask how much of it is fixed. Compute has improved a lot. Data has improved somewhat. The skills gap is still the biggest one, and it has changed shape rather than closed, because in 2018 the shortage was of researchers and today the shortage is of people who can apply existing models to a real workflow.

The paper also cited an Accenture estimate that AI could add around 957 billion dollars to India's economy by 2035. That number gets quoted constantly. Treat it as a directional argument for investment, not a forecast.

What it proposed to build

NITI Aayog recommended a two-tier research structure. COREs, or Centres of Research Excellence, were meant to do fundamental research inside academic institutions. ICTAIs, International Centers for Transformational AI, were meant to sit closer to industry and turn research into deployable applications. The paper also asked for a national AI marketplace for data and models, and for shared compute, which later showed up as AIRAWAT at C-DAC Pune, a national AI supercomputing platform that eventually entered the global top 100 list in 2023.

The two-tier idea was sound. Execution was slow and uneven, which is the usual fate of a discussion paper with no budget attached to it.

From a 2018 paper to a funded mission

If you are searching for this strategy in 2025 or later, the thing you actually need to know is that the policy centre of gravity has moved. The 2018 paper set the direction. The IndiaAI Mission, approved by the Union Cabinet in March 2024 with an outlay of around 10,371 crore rupees over five years, is where the money and the machinery now sit.

The mission runs on seven pillars, and you can map most of them straight back to the 2018 barriers list: compute capacity (a large shared GPU pool), an innovation centre for indigenous foundation models, a datasets platform, application development, startup financing, FutureSkills for AI education, and a Safe and Trusted AI track. MeitY followed up with India AI Governance Guidelines in November 2025, and India is hosting the AI Impact Summit in New Delhi in February 2026.

So the honest one-line answer to what happened to #AIFORALL is: the vision survived, the delivery vehicle changed.

Year	What happened
2018	NITI Aayog releases National Strategy for AI #AIFORALL
2021	NITI Aayog publishes Responsible AI approach documents (principles, then operationalisation)
2023	AIRAWAT national AI supercomputer enters global top 100; DPDP Act passed
2024	Cabinet approves IndiaAI Mission with roughly Rs 10,371 crore across seven pillars
2025	MeitY releases India AI Governance Guidelines
2026	India hosts the AI Impact Summit in New Delhi

What this means if you are not a policymaker

Most people searching this query are students writing a paper, professionals trying to understand where India is heading, or educators building a curriculum. Here is the practical read for each.

If you are a student or a young professional, the strategy tells you where demand will be concentrated. Health, agri, education, mobility and public infrastructure are the sectors where Indian AI jobs are being created with public money behind them, and they need domain plus AI, not AI alone. An agronomy graduate who can build a crop advisory tool is more employable than a generic prompt engineer. That combination is not taught anywhere in a degree, which is why hands-on programmes matter more than another certificate; if you want to build and ship actual projects with mentors instead of reading about policy, the AI Creator Fellowship is built exactly for that eight-week gap between knowing and doing.

If you run a college or a school, IndiaAI FutureSkills is going to push AI content into your curriculum whether you plan for it or not. Getting ahead of that with structured AI workshops and certifications for your faculty is cheaper than retrofitting later.

If you run a business, the strategy is a signal about where data and compute will get cheaper, not a subsidy you can apply for tomorrow.

The part nobody solved

India has compute now. It has funding, a governance framework, datasets programmes and a global summit. What it does not have is enough people who can take a working model and wire it into a hospital's patient flow, a mandi's price system or a school's assessment cycle.

That is not a policy problem anymore. It is a skills problem, and it gets solved one person at a time, by people who build things instead of reading strategy documents about building things. #AIFORALL was always aspirational. Whether it becomes true depends on how many people decide to be part of the delivery rather than the audience.

FAQs

1. Who released the National Strategy for Artificial Intelligence and when?

NITI Aayog released it as a discussion paper in June 2018, under the title National Strategy for Artificial Intelligence #AIFORALL. It was prepared following a mandate in the Union Budget 2018-19 for NITI Aayog to build a national programme on AI.

2. Is the National Strategy for AI a law or a policy?

Neither. It is a discussion paper with recommendations, so it has no legal force and no budget of its own. The binding instruments that came later are the Digital Personal Data Protection Act 2023 and the funded IndiaAI Mission approved in 2024.

3. What is the difference between #AIFORALL and the IndiaAI Mission?

#AIFORALL (2018) set the vision and named the five priority sectors and the obstacles. The IndiaAI Mission (2024) is the funded implementation programme, run by MeitY, with roughly Rs 10,371 crore and seven pillars covering compute, datasets, models, applications, startups, skills and safe AI.

4. What are COREs and ICTAIs in the AI strategy?

COREs are Centres of Research Excellence, proposed to do fundamental AI research inside academic institutions. ICTAIs are International Centers for Transformational AI, meant to work closer to industry and convert research into deployable applications, typically through public-private partnership.

5. What is AIRAWAT?

AIRAWAT is India's national AI research and compute platform, hosted at C-DAC Pune. It came out of the 2018 strategy's recommendation for shared national compute and entered the global top 100 supercomputer rankings in 2023.

6. Does India have AI regulation now?

India has no standalone AI Act. Data use is governed by the Digital Personal Data Protection Act 2023, and MeitY issued the India AI Governance Guidelines in November 2025 as a principles-based framework rather than binding law.

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