“AI will not replace humans, but those who use AI will replace those who don’t”
Ginni Rometty, Former CEO of IBM
- Introduction
Data and compute are the raw materials of AI. As India builds public data platforms, how this data is curated, accessed and governed will shape innovation and adoption. Without transparent, democratic data governance frameworks, unfortunately these ecosystems risk reinforcing corporate concentration and undermining public trust.[1] And Nowhere is the governance gap starker than in employment. In 2024 alone, India’s top three IT services firms TCS, Infosys and WIPRO shed nearly 65000 jobs.[2] The IMF estimates that 26% of India’s workforce is exposed to Generative AI with 12% at the risk of displacement. The national AI initiative notwithstanding, it does not sufficiently address employment transition workforce planning or social protection. Addressing these gaps can help ensure that AI adoption supports economic resilience and social stability.
India’s IT sector employing over 5 million people and contributing around 7.5% to the country’s GDP has been one of the most reliable job creators, especially for the aspirational middle class. Ergo, a sudden disruption in the sector has wider socio-economic ramifications. Though AI cannot replace all jobs, sectors other than IT are also likely to be affected. A recent research by Microsoft lists 40 professions most and least likely to be impacted by AI and Large language Models (LLMs). More intellectually demanding, communication heavy roles are among those most vulnerable to AI, while jobs requiring manual labor will remain relatively safe. India faces a paradox today vis-à-vis shaping an AI workforce. It produces a burgeoning 1.5 million engineering graduates annually, yet companies struggle to find candidates capable of handling sophisticated AI development.[3] A recent report by Bain & Company paints a rather sobering picture when it highlights that the country could face a shortage of more than a million skilled professionals by 2027 unless urgent steps are taken to upskill the workforce. Young workers are more vulnerable to AI induced shifts in the economy. This comes on heels of an Indian Software giant shedding 12000 jobs and making an AI pivot.[4] Further, experts are also hinting at an Engels’ pause in our modern AI economy, where productivity surges but broad based prosperity stalls. Job displacement and task transformation will be early measures to ascertain a modern Engels’ pause. Without AI governance the Engels’ pause may persist.
- The AI Talent Gap: Global and Indian Perspectives
Global Demand for AI talent
According to a study by Upwork done in 2023, The top 10 Generative AI-related skills listed in Upwork job seeker profiles with the largest quarter-over-quarter growth (Q2 2023 vs Q1 2023) were: Large Language Model (LLM); Generative AI; You Only Look Once (YOLO); Object Detection; Stable Diffusion; Prompt Engineering; ChatGPT; Azure OpenAI; AI Chatbot; and AI Text-to-Speech. The LinkedIn report’s analysis of how AI skills are emerging across 25 countries shows that the pace at which LinkedIn members added AI skills to their profiles nearly doubled since the launch of ChatGPT, rising from 7.7% (May–November 2022) to 13% (November 2022–June 2023). [5]
In an attempt to track the AI talent concentration globally, LinkedIn has released its “AI talent concentration” metric, which is based on the member profile data collected from the professional networking site. In 2024, Israel topped the list, as the country’s supply of AI talent is 1.98% of its workforce. Singapore follows in second place, as the city-state boasts an AI talent supply that is 1.64% of its workforce, while Luxembourg is in third, showing a supply that is 1.44% of its workforce. All these countries are able to make it to the list because of thriving ecosystems where talent is nurtured when companies are invested in their employees’ skill development, and governments create policies that encourage continuous learning. Though India did not make it to the top 10, the country has seen a staggering 252% increase in this metric between 2016 and 2024, which signals professionals in the country are “actively building their AI-related skills”. [6]
The actual malady is that the talent gap extends beyond coding proficiency. Modern AI development demands professionals who can navigate complex ethical considerations, understand human psychology, design for accessibility, and anticipate societal impacts. These interdisciplinary skills remain virtually absent from traditional engineering programs. When an AI system makes a biased decision affecting millions, the solution is not simply better code, it requires developers who understand the social contexts in which their creations operate. When autonomous systems must make split-second ethical choices, developers need philosophical frameworks alongside algorithmic ones. Our current education system addresses none of these dimensions adequately.[7]
India’s AI talent landscape
While India excels in its ability to identify and recruit for future-focused skills, as per the QS’s ‘Future of Skills Index’, where it scored 99.1 in the ‘Future of Work’ parameter, its performance in ‘Skills Fit’ — the ability of the workforce to meet these demands — lags significantly, with the country scoring just 59.[8] The report also identifies deficiencies in fostering entrepreneurial and innovative mindsets, placing India in a modest 26th position when it comes to‘Academic Readiness’ (ibid.).
- Global Best Practices in AI Talent Development
University-led initiatives
Universities play a vital role in addressing the digital divide and technological inclusivity, ensuring that AI benefits are equitably distributed. As such, universities are emerging as key hubs for developing AI talent pipelines and guiding AI innovations towards broader societal goals. For instance, Massachusetts Institute of Technology (MIT) hosts one of the largest and most prestigious AI research labs in the world. The university has also committed $1 billion to create the MIT Stephen A. Schwarzman College of Computing, which has a strong emphasis on interdisciplinary AI education and research.[9] The Human-Centered AI Institute (HAI) and Stanford Artificial Intelligence Laboratory (SAIL) at Stanford University are other initiatives shaping the talent pool. Singapore is another brilliant example of how a skill transition program is crucial in developing the AI workforce. Its ‘SkillsFuture’ program provides continuous education credits for workers to reskill.[10] We also have the world’s first AI university in Abu Dhabi, the Mohammed Bin Zayed University of Artificial Intelligence (MBZUAI) as another example of skilling a new generation of AI related human capital creation.[11]
Government-led AI Initiatives
Government policies are the architectural plans that shape an industry’s structure. They set the rules, standards and incentives that guide the AI industry, ensuring it thrives while benefits are equitably distributed. Afterall, policies are the infrastructure that you don’t see but are impacted by it. One crucial role of the government is ensuring that the workforce is equipped with the right skills. For instance, through the Pan-Canadian Artificial Intelligence Strategy, the Government of Canada is investing in efforts to drive the adoption of AI across Canada’s economy and society. The strategy also bridges Canada’s world-class talent and research capacity with programs to enable commercialization and adoption to help ensure that Canadian ideas and knowledge are mobilized and commercialized here at home.[12]
To cultivate a strong domestic talent pipeline in the field of AI, Singapore has come up with its National AI strategy. The strategy is built on the twin goals of achieving “peaks of excellence” in AI development and empowering citizens and businesses to use AI confidently and ethically. This new vision marks a crucial shift, treating AI as a “must know” necessity rather than an optional skill. It adopts a global, systems-based approach that moves beyond individual projects to build robust national capabilities in computing, talent, and data, ensuring Singapore can effectively scale AI solutions and thrive.[13] Driven by the rapid pace of technological change and the need for a human-centric approach to the development of artificial intelligence (AI). The EU promotes cooperation between the states and contributes with proposals for reforms and investment, leaving the education and training policies within the remit of the Member States. The European Commission’s 2024 political guidelines, together with the Mission Letter to Executive Vice-President Roxana Mînzatu, the Draghi Report on EU competitiveness and the communication on the union of skills adopted on 5 March 2025, describe the union of skills as a policy initiative whose goal is to strengthen human capital, create a resilient and inclusive labour market, promote constant upskilling and help with skill retention. The communication consists of four pillars: (i) Building skills for quality jobs and lives; (ii) Upskilling and reskilling; (iii) Circulating skills (i.e. skilled workers) within the EU; and (iv) Attracting and retaining talent. [14], [15], [16], [17]
Industry-Academia collaboration
Tech giants such as Google are also expanding their footprint through talent development programs. In its efforts to continue advancing AI that is responsible and globally accessible, Google is strengthening its partnership with the University of Cambridge by funding a new AI research centre (Centre for Human-Inspired Artificial Intelligence).[18] To develop AI talent pool and strengthen collaborative ecosystem, Microsoft Research Asia is collaborating with National University of Singapore and a few other universities in Singapore to advance both fundamental and applied research, while equipping the next generation of researchers with real-world experience.[19]
Mostly established by corporations, AI startup programs provide an effective way to access valuable resources like cloud credits, industry knowledge, and connections to help you acquire more clients. Corporations that establish these startup programs often aim to partner with the most promising startups completing the program, offering a potential pathway to securing enterprise clients. These startup programs are ideal for bootstrapping startups that want to retain control, as most of them are equity-free, allowing you to scale without giving up ownership. Such as, Google AI First targets AI-centric startups aiming to solve significant global challenges. Startups receive Google Cloud credits and benefit from mentorship with Google’s AI experts. The program provides support in scaling AI-driven solutions, leveraging Google’s powerful cloud infrastructure to help startups build, deploy, and optimize AI models efficiently. Microsoft for Startups helps startups accelerate their growth by providing access to Microsoft’s advanced cloud, AI, and development tools. The program offers up to $150,000 in Azure cloud credits, allowing startups to build, scale, and deploy AI and tech-driven solutions efficiently using Microsoft’s Azure infrastructure, including access to models like OpenAI GPT-4 and Meta’s Llama 2. Beyond technical resources, the program also offers 1:1 technical advisory from Microsoft engineers, who assist startups with AI implementation, infrastructure optimization, and scaling.
- India’s AI Talent Development Efforts: Progress and Gaps
Key Initiatives
India is also witnessing the demand for new digital age jobs, which can be attributed to three factors ,viz., adoption of technology, shift in the market and evolving nature of globalisation. In this context NITI Aayog came up with the National AI Strategy 2018, which touches upon the talent and skills part, where it says that “India may be well positioned to take advantage of AI disruption by virtue of its advanced IT sector and large youth demographic potential…as the future hub for AI”.[20] However, it also issues a caveat that without urgent government intervention this advantage can become a liability. This is a critical component of AI development and should be a national priority. The National AI Strategy’s approach to skilling targets both the current workforce and the student population. For the existing workforce, the focus is on reskilling, promoting new jobs like data annotation, and standardizing training institutions. For students, the strategy aims to realign the education sector through skill-based learning in schools and stronger industry-academia collaboration in higher education. This dual approach is designed to prepare India’s human resources for the impending AI-driven economic shift.
While the upskilling and reskilling falls within the ambit of industry and government. However, making sure that the country has a robust, tech savvy workforce with foundational skills is the duty of the schools and higher educational institutions (HEIs). There has been a consistent gap between the skills-in demand vs the skills the graduates possess because of automation and changing nature of the jobs. As a result we see that both industries face shortage of the desired talent and job entrants face a tough time in the job market. HEIs in the country are cognisant of the issue and are increasingly focussing on AI training programs. Initially, AI was introduced as a subject within the broader curriculum of computer science and engineering. However, recognising its potential, institutions began offering specialised courses, research programs and dedicated AI centres. For instance, Indian Institute of Technology (IIT) Madras, has established the Robert Bosch Centre for Data Science and AI, one of the largest AI research centers.[21] The institute’s AI curriculum is designed to be rigorous and comprehensive, covering foundational topics and advanced concepts. IIT Delhi’s Yardee School of Artificial Intelligence is another key academic initiative to strengthen education and research in artificial intelligence (AI), machine learning (ML), data science (DS) and their broad applications such as in healthcare, materials science, robotics, industry 4.0, weather prediction, and transportation. Indian Institute of Science Bangalore, another pioneer in science and technology research, offers specialised courses in AI. The institute’s curriculum is designed to provide a deep understanding of AI concepts, complemented by practical training and research opportunities.
Grooming AI talent is one of the key aspects of building AI competence, this is where Industry comes into the picture. NASSCOM, an industry body in association with the Government of Karnataka, Industry and Academia, established India’s first Center of Excellence (CoE) for Data Science and Artificial Intelligence (DSAI). One of the key tasks of the CoE is to develop appropriate skills and talent in the data science and AI space. Further, NASSCOM’s Sector Skills Council (SSC) has identified 19 roles in AI for business competence and developed ‘Qualification Packs’ for these jobs roles. The SSC has got the approval of National Skills Development Corporations and will undertake streamlining and standardisation of varying levels of AI competence in India. Wipro, a leading technology services and consulting company launched a new CoE on Generative Artificial Intelligence (AI) in partnership with the Indian Institute of Technology (IIT) Delhi. The CoE will serve as an R&D hub, bringing together Wipro researchers with School of AI (ScAI) faculty members and graduate students to address at-scale real-world problems.[22] Recently, OpenAI Academy in partnership with IndiaAI Mission under the IT Ministry launched the OpenAI Academy in India. The initiative seeks to broaden access to AI education and tools, tapping into India’s fast growing developer community, digital infrastructure, and networks of startups and innovators. [23]
India’s AI talent initiatives, while promising, suffer from critical lacunae. The efforts are largely concentrated in elite institutions, creating a significant gap in scale and accessibility for the majority of students. There’s an overemphasis on high-level R&D, often overlooking the urgent need for job-ready foundational skills across the wider graduate pool. Crucially, a systemic “train the trainer” program to develop qualified faculty is absent from the strategies/ initiatives undertaken. Furthermore, the initiatives are narrowly focused on technical domains, neglecting the essential need for AI literacy in non-technical fields like business and policy to ensure holistic and ethical AI adoption.
Talent migration is another issue for India to tackle. On the talent aspect, the government’s National Strategy document simply recommends increasing the number and type of AI courses at different levels. But they fail to address, for example, the reasons why India’s top-tier AI talent often migrates outside India.[24] Fixing the quality element will also be critical; else many of these engineering graduates will likely be unable to compete with AI for basic coding tasks. At the same time, the need to develop India’s existing IT talent into an AI-enabled workforce through upskilling will be a critical challenge for India’s tech and IT services industry.
- Strengthening India’s AI Talent Pipeline
India’s ambition to become a global AI leader hinges on developing a robust, multi-tiered talent pipeline. While the nation has a large pool of STEM graduates, significant gaps exist in quality, specialization, and accessibility. Closing these gaps requires a concerted, multi-stakeholder effort focused on integrating AI into education at all levels, fostering interdisciplinary expertise, deepening industry-academia collaboration, and executing large-scale workforce reskilling. A foundational step is to embed AI education throughout the academic journey, from K-12 to higher education, to build a strong pipeline from the ground up. India should converge basic digital literacy with foundational AI concepts early. The government has already taken positive steps, with the Central Board of Secondary Education (CBSE) introducing AI as a subject for classes 8-10 and partnering with IBM and Intel on curriculum support, and Council for the Indian School Certificate Examinations (CISCE) adding robotics and AI from the 2025-26 session.[25] These initiatives should be scaled nationwide, ensuring the curriculum focuses on skill-based, computational thinking rather than rote knowledge. Higher educational institutions must develop a layered talent strategy. This includes creating programs for different expertise levels.
They should integrate mandatory AI awareness modules into all degree programs, not just technical ones, to create a broad base of AI-literate graduates. Engineering and computer science curricula need urgent and continuous revision to move beyond fundamentals and include advanced, practical training in areas like advanced Machine Learning (ML), Natural Language Processing (NLP), and AI model deployment. To solve the “brain drain” of top research talent, India must invest heavily in 25-30 universities to create world-class postgraduate and doctoral programs in AI, offering globally competitive incentives and research infrastructure. Further as the United States is tightening its visa rules, it also offers India an opportunity of luring back its talent by offering a conducive growth path in the country to take advantage of a potential reverse brain.
To drive innovation, AI skills must permeate beyond traditional computer science into various other domains, fostering an “AI + X” paradigm.[26] The higher educational institutions should offer “bridge courses” for post-graduates from non-computer science backgrounds to gain expertise in AI. This will enable professionals in fields like medicine, agriculture, and finance to apply AI to solve domain-specific problems, which is critical for social and economic impact. Academic programs must be planned in coordination with industry to produce not just AI engineers, but also AI product managers, ethicists, designers, and entrepreneurs.
Industry must collaborate closely with universities to co-design curricula that are aligned with real-world demands and the changing nature of jobs. This goes beyond guest lectures to involve joint projects, industry-led workshops, and practical training on platforms like Infosys Springboard. This collaboration is vital, especially since many engineering graduates are considered unemployable due to a gap between their skills and industry needs. Industry should offer specialized internships, hackathons, and mentorship programs to provide students with hands-on experience in applying AI tools and technologies. These practical experiences are invaluable for bridging the gap between theoretical knowledge and job readiness. A significant bottleneck is the lack of qualified faculty to teach advanced AI concepts. Industry leaders should partner with academic institutions to establish “Train the Trainer” academies, equipping educators with the latest knowledge and pedagogical tools to effectively teach AI.22
When it comes to the private sector, companies must follow the lead of firms like TCS, which trained 350,000 employees on AI, and Wipro, which trained 220,000.[27], [28] These massive internal upskilling programs are essential for transitioning the existing IT workforce into an AI-enabled one. Global tech majors have also committed to training millions in India, an effort that needs to be broadened across more companies. The government should introduce financial incentives like tax breaks, public grants, or payroll tax deductions for companies that invest significantly in reskilling their employees. This can help offset the high opportunity cost of training and encourage widespread participation, especially among smaller firms. To ensure quality, the government and industry bodies like NASSCOM should work to standardize and certify informal training institutions based on frameworks like the National Skill Qualification Framework (NSQF). This helps both employees and employers trust the value of the training received.
- Conclusion
India’s ambition for global AI leadership is challenged by a critical talent gap, despite its large demographic and IT sector. Recent job losses in major IT firms underscore the urgent need for a national strategy to manage this workforce transition and avoid a modern “Engels’ Pause,” where productivity surges but prosperity stalls. The talent deficit is not merely quantitative but qualitative, demanding interdisciplinary skills like ethics and social context that traditional engineering programs lack.
Current initiatives, while promising, are concentrated in elite institutions, lacking the scale, accessibility, and faculty development required for national impact. Drawing from global best practices, the path forward requires a holistic, multi-stakeholder strategy. This involves embedding AI education from K-12 upwards, fostering interdisciplinary “AI+X” expertise, scaling industry-academia partnerships for curriculum design, and executing large-scale workforce reskilling backed by government incentives. By systematically bridging these gaps, India can transform its potential workforce from a liability into a key asset, mitigating displacement risks and harnessing AI for inclusive, sustainable growth.
[1] Gupta, R., (2025, July 3). AI in India: Strategy must precede mission. The Hindu. https://www.thehindu.com/opinion/op-ed/ai-in-india-strategy-must-precede-mission/article69764952.ece
[2] Chatterjee, C., (2025, September 30). An Engels pause in an AI shaped world. The Hindu. https://www.thehindu.com/opinion/lead/an-engels-pause-in-an-ai-shaped-world/article70106049.ece
[3] Sarda, A. (2025, May 28). India’s AI talent gap is real: Here’s how we can fix it with future-first higher education. IndiaToday Best Colleges. https://bestcolleges.indiatoday.in/news-detail/indias-ai-talent-gap-is-real-heres-how-we-can-fix-it-with-future-first-higher-education-3688
[4] Bain & Company. (2025, February). AI: The ambitions are bold, but the talent is scarce . https://www.bain.com/insights/ai-the-ambitions-are-bold-but-the-talent-is-scarce-snap-chart/
[5] Monahan, K. (2023, August 22). The evolving marketplace for generative AI. Upwork. https://www.upwork.com/blog/generative-ai-marketplace
[6] Microsoft & LinkedIn. (2024, May 8). 2024 Work Trend Index annual report: AI at work is here. Now comes the hard part [PDF]. https://assets-c4akfrf5b4d3f4b7.z01.azurefd.net/assets/2024/05/2024_Work_Trend_Index_Annual_Report_6_7_24_666b2e2fafceb.pdf
[7] Sarda, A. (2025, May 28). India’s AI talent gap is real: Here’s how we can fix it with future-first higher education. IndiaToday Best Colleges. https://bestcolleges.indiatoday.in/news-detail/indias-ai-talent-gap-is-real-heres-how-we-can-fix-it-with-future-first-higher-education-3688
[8] Quacquarelli Symonds (QS). (2025, January). QS World Future Skills Index: Transforming higher education for the skills economy [PDF]. https://insights.qs.com/hubfs/Reports/QS%20World%20Future%20Skills%20Index.pdf
[9] MIT Schwarzman College of Computing. (n.d.).. Retrieved October 4, 2025, from https://computing.mit.edu/about/
[10] AI Singapore. (n.d.). AI Apprenticeship Programme (AIAP). Retrieved from https://aiap.sg/apprenticeship/#:~:text=Going%20beyond%20Jupyter%20notebooks%20to,Project%20Phase
[11] Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). (n.d.). Retrieved October 4, 2025, from https://mbzuai.ac.ae/
[12] Innovation, Science and Economic Development Canada. (n.d.). Pan-Canadian Artificial Intelligence Strategy: Pillar 2 – Standards. Retrieved October 4, 2025, from https://ised-isde.canada.ca/site/ai-strategy/en#pillar2
[13] Smart Nation Singapore. (2025, August 12). National AI Strategy. Retrieved October 4, 2025, from https://www.smartnation.gov.sg/initiatives/national-ai-strategy/
[14] European Commission. (2024). Political guidelines 2024-2029: Europe’s choice [PDF]. https://commission.europa.eu/document/download/e6cd4328-673c-4e7a-8683-f63ffb2cf648_en?filename=Political%20Guidelines%202024-2029_EN.pdf
[15] European Commission. (2024, September 17). Roxana Mînzatu – Mission letter [PDF]. https://commission.europa.eu/document/27ac73de-6b5c-430d-8504-a76b634d5f2d_en
[16] European Commission. (n.d.). The Draghi report on EU competitiveness: The future of European competitiveness. Retrieved October 4, 2025, from https://commission.europa.eu/topics/eu-competitiveness/draghi-report_en
[17] European Commission. (2025, March 5). Communication from the Commission to the European Parliament, the European Council, the Council, the European Economic and Social Committee and the Committee of the Regions: The Union of Skills (COM(2025) 90 final) [PDF]. https://eur-lex.europa.eu/legal-content/en/TXT/PDF/?uri=CELEX%3A52025DC0090
[18] Centre for Human-Inspired Artificial Intelligence (CHIA), University of Cambridge. (n.d.). Home [Web page]. Retrieved October 4, 2025, from https://www.chia.cam.ac.uk
[19] Knobel, Z. (2025, July 24). Microsoft Research Asia launches Singapore lab to drive AI innovation, industrial transformation, and talent development. Microsoft. https://news.microsoft.com/source/asia/2025/07/24/microsoft-research-asia-launches-singapore-lab-to-drive-ai-innovation-industrial-transformation-and-talent-development/
[20] NITI Aayog. (2018, June).National strategy for artificial intelligence: #AIFORALL. Government of India.https://www.niti.gov.in/writereaddata/files/document_publication/NationalStrategy-for-AI-Discussion-Paper.pdf
[21] Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras. (n.d.). Retrieved October 4, 2025, from https://rbcdsai.iitm.ac.in/
[22] Wipro Limited. (2023, August 16). Wipro launches Center of Excellence on Generative AI at the Indian Institute of Technology Delhi. https://www.wipro.com/newsroom/press-releases/2023/wipro-launches-center-of-excellence-on-generative-ai-at-the-indian-institute-of-technology-delhi/
[23] Mishra, M. (2025, June 5). OpenAI, IndiaAI launch academy to expand AI learning across the country. Business Standard. https://www.business-standard.com/india-news/openai-indiaai-academy-launch-ai-education-platform-across-india-125060501123_1.html
[24] MacroPolo. (n.d.). The Global AI Talent Tracker 2.0. Retrieved October 4, 2025, from https://archivemacropolo.org/interactive/digital-projects/the-global-ai-talent-tracker/
[25] Tomar, A. (2025, January 31). How AI is activating step changes in Indian education. EY-Parthenon India. https://www.ey.com/en_in/insights/education/how-ai-is-activating-step-changes-in-indian-education
[26] NITI Aayog. (2023, March). National Strategy for Artificial Intelligence. https://www.niti.gov.in/sites/default/files/2023-03/National-Strategy-for-Artificial-Intelligence.pdf
[27] PTI. (2024, March 29). TCS says it trained 3.5 lakh employees in generative AI skills. The Economic Times. https://economictimes.indiatimes.com/tech/information-tech/tcs-says-it-trained-3-5-lakh-employees-in-generative-ai-skills/articleshow/108877621.cms
[28] Baruah, A. (2024, March 28). Wipro to train all employees on AI to become an AI-first company. Business Standard. https://www.business-standard.com/companies/news/wipro-to-train-all-employees-on-ai-to-become-an-ai-first-company-124032800645_1.html