IndiaAI Mission's FutureSkills Pillar: Building India's AI-Ready Talent Pipeline

Policy Update
Prisha Sachdeva

Background

IndiaAI Mission was launched in March 2024 and is centered on addressing existing gaps in data, research, and skill mismatch so that the benefits of AI can contribute to the growth of our country. The Ministry of Electronics and Information Technology (MeitY) identified seven pillars: IndiaAI Compute, Foundation Models, AIKosh, IndiaAI Application Development Initiative, FutureSkills, Startup Financing, and Safe & Trusted AI.

The goal of this mission is AI for All, with an outlay of ₹10,371 crore over five years to build a comprehensive AI ecosystem in the country. AI is worth $120 billion as a market, is growing by more than 20% each year, and is expected to reach a total of $1.5 trillion by 2030. Further, the global market for AI-specialised hardware is expected to grow 9x to $90 billion by 2030.

The FutureSkills pillar aims to reduce barriers in AI programmes by increasing AI courses at undergraduate, postgraduate, and PhD levels. It specifically works on model and curriculum development, categorised courses (technology-specific, application-specific, infrastructure-specific), research fellowships, faculty training, and career mapping through its three key areas: fellowships for UG, PG, dual degree, and PhD students; setting up AI and Data Labs; and courses for skill development.

These strategies are aimed at addressing the growing demand for AI skills and preparing students for future work in AI. The working group wants to stay ahead and remain competitive in the AI market with its new vision: “A Transformative Approach: From Job Takers to Job Providers.”

Functioning

The FutureSkills pillar aims to enhance India’s AI workforce by skilling the nation. Its objective is to help individuals become AI experts. It is implemented under the Ministry of Electronics and Information Technology (MeitY) through the IndiaAI Mission and collaborates with academic institutions, the Ministry of Skill Development and Entrepreneurship (MSDE), and NASSCOM to provide AI education.

How does it operate?

This pillar works in three broad areas:

Providing fellowships for UG, PG, and PhD programmes with the objective of building deep AI talent. It aims to support high-potential students pursuing advanced studies and research in AI to build a strong group of researchers and innovators.
Setting up AI and Data Labs to improve access to high-quality AI education in Tier 2 and Tier 3 cities. It aims to provide hands-on exposure to tools, datasets, and problem-solving environments. These labs will act as hubs for innovation, experimentation, learning, and collaboration.
Developing skill development courses to help beginners excel in AI careers while promoting the use of ethical AI. IndiaAI collaborates with expert partners to design these courses with an aim to create specialised courses for sectors such as healthcare, marketing, and agriculture.

Platform

The fellowship programme is accessible on the IndiaAI Mission website ([https://fellowship.indiaai.gov.in/login] for UG, PG, PhD, and dual degree programmes. Students who meet the eligibility criteria can apply for the fellowship on the website itself.

Courses are delivered through IndiaAI’s own Data & AI Labs (hands-on, hub-based) as well as through existing digital platforms such as FutureSkills Prime and iGOT Karmayogi (for the mass-awareness YUVA AI course). These platforms are shared delivery channels, not the scheme itself.

In summary, the FutureSkills pillar aims to equip students with in-demand future skills through courses and fellowship programmes that will create more job opportunities for individuals.

Funding structure

The IndiaAI Mission was implemented with a total outlay of Rs. 10,371.92 Cr for a period of 5 years. The detailed budget for 7 pillars is as follows

S.no	Components	Total Allocation (₹ Cr)
1.	IndiaAI Compute Capacity	4563.36
2.	IndiaAI Foundation Models	1971.37
3.	IndiaAI Datasets Platform	199.55
4.	IndiaAI Application Development Initiative	689.05
5.	IndiaAI FutureSkills	882.94
6.	IndiaAI Startup Financing	1942.5
7.	Safe & Trusted AI	20.46
8.	IndiaAI Overheads and Contingency @1%	102.69
	Total	10,371.92

Source: Ministry of Electronics and Information Technology, Lok Sabha reply (2026).

Performance

So far, the performance of the FutureSkills pillar is mixed, as the Data & AI Labs component has gone ahead of its target, whereas the fellowship programme is still far behind its target.

Fellowship programs

The targeted and actual participation rate of students and institutes are as follows

	Participation of Students	Targeted Participation	Achievement %
UG	288	8000	3.6%
PG	145	5000	2.9%
PhD	228	500	45.6%
Total	680	13500	5.0%

Source – IndiaAI Fellowship Portal

PIB Press Note — IndiaAI Mission Progress

AI and Data labs

	Actual	Targeted	Achievement %
Labs (Tier 2/3 cities, with NIELIT)	31	27	114.8%

In addition, 543 ITIs and polytechnics across all States and Union Territories have been approved to set up additional IndiaAI Data and AI Labs.

Source – Lok Sabha Unstarred Question No. 3246

Course completion funnel rate

Course	Registered	Trained	Certified	Certification rate
Data Annotation	2611	1552	549	21%
Data Curation	2933	1609	700	22%
Total	5544	3161	1249	24.5%

Source – IndiaAI FutureSkills Hub

The tables show the Mission’s budget allocation, the gap between fellowship targets and actual participation, the progress of AI and Data Labs beyond target, and the low conversion rate from course registration to certification.

Impact

The impact of the FutureSkills pillar appears to be early-stage but promising. By building AI-relevant skills, the pillar has the potential to improve students’ access to future job opportunities, although concrete outcome data is still needed before this can be confirmed at scale.

The pillar’s original vision — moving India “from Job Takers to Job Providers” — envisioned an AI ecosystem in which students actively build and apply skills rather than merely consume AI technologies developed elsewhere. In practice, however, the fellowship programme, which is central to building deep research talent, remains far behind its targets, while the Data & AI Labs component has already exceeded its own targets. This suggests that the pillar’s core vision of producing deep AI talent and researchers is still far from being realised, even as its broader infrastructure-building goals are progressing well.

The course completion funnel data reinforces this unevenness: a significant drop-off between registration and certification indicates that, while access to training is widely available, completing and certifying that training remains difficult for a large share of participants. This weakens the pillar’s ability to convert enrolment into an actual job-ready, skilled workforce.

Emerging Issues

While the Data and AI Labs have scaled rapidly, the fellowship programmes and course completion rates are very low, revealing several concerns about the pillar’s long-term ability to build an AI-ready generation.

The eligibility for fellowship programmes is restricted to Tier 1 colleges (top 50 NIRF-ranked institutions), but the original intent was to give priority to Tier 2, Tier 3, and Tier 4 colleges, highlighting a significant gap in accessibility for students.

The course completion rate is also very low compared with the course registration rate, showcasing the difficulty in completing the courses.

Way Forward

The next step for the FutureSkills pillar under the IndiaAI Mission should be to simplify the application process for fellowship programmes and to track intermediate steps, so that the problems faced by students can be better understood.

The next phase should focus on setting up Data and AI Labs in Tier 2, Tier 3, and Tier 4 colleges to increase inclusivity and provide mentorship to registered students in order to reduce drop-off rates. Efforts should be made to expand fellowship eligibility beyond the top 50 NIRF institutes to include state and central universities that meet the baseline criteria.

Additionally, mandatory upskilling of faculty should be introduced to ensure trainers and mentors remain updated with the latest skills.Institutes should partner with industry bodies such as NASSCOM and tech companies to provide internships alongside fellowships, enabling students to gain hands-on industry experience.

References

IndiaAI. (2025). Updated guidelines — IndiaAI FutureSkills Fellowship. https://fellowship.indiaai.gov.in/formats/Updated_Guidelines_IndiaAI_Fellowship_010725.pdf

IndiaAI. (2026). IndiaAI Fellowship — student selection dashboard. https://fellowship.indiaai.gov.in/login

IndiaAI. (2026). IndiaAI FutureSkills hub — course completion data. https://indiaai.gov.in/hub/indiaai-futureskills

Ministry of Electronics and Information Technology. (n.d.). Lok Sabha Question Annex 184 — AU3093. Government of India. https://sansad.in/getFile/loksabhaquestions/annex/184/AU3093_geVjkv.pdf?source=pqals

Ministry of Electronics and Information Technology. (2023). Seven MeitY AI Working Groups submit first edition of IndiaAI Report. Press Information Bureau. https://www.pib.gov.in/PressReleaseDetail.aspx?PRID=1967487&reg=48&lang=1

Ministry of Electronics and Information Technology. (2023). IndiaAI Expert Group Report — First Edition. https://indiaai.s3.ap-south-1.amazonaws.com/docs/IndiaAI+Expert+Group+Report-First+Edition.pdf

Ministry of Electronics and Information Technology. (2025). Press Note on IndiaAI Mission progress — FutureSkills pillar targets. Press Information Bureau. https://www.pib.gov.in/PressNoteDetails.aspx?ModuleId=3&NoteId=156786&lang=1&reg=3

Ministry of Electronics and Information Technology. (2026). Lok Sabha Unstarred Question No. 3246 — IndiaAI Mission budget and labs data. Government of India. https://sansad.in/getFile/annex/270/AU3246_wa5YLu.pdf?source=pqars

Ministry of Electronics and Information Technology. (2026). Safe & Trusted AI Pillar under IndiaAI Mission strengthens citizen trust. Press Information Bureau. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2289946&reg=3&lang=1

About the Contributor

Prisha Sachdeva is a Research & Editorial intern at IMPRI. She’s pursuing Bachelors in psychology (Honours) from University of Delhi . Her interest lies in cognitive science , human behavior with focus on evidence based policy and behavioral research.