An unusual opportunity has emerged for AI startups amid massive layoffs across the IT sector in India. Early signs suggest the adaptability of both the displaced workforce and startups could shape India’s AI landscape in unexpected ways. 

Startups are embracing laid-off IT professionals, seeing an opportunity to bolster their engineering teams, without the immediate costs of hiring fresh graduates and training them. 

The question of retention, however, remains pivotal. While these hires may be a quick fix to address skills shortages, startups need to consider whether they can sustain such hires over the long run. “There may be some integration challenges, laid-off employees might have higher expectations based on previous roles and the company from which they were laid off,” said Aditya Singh Gaur, deputy manager at C3iHub, a technology innovation hub at IIT Kanpur.

Elaborating on challenges for experienced professionals, Gaur said startup environments demand flexibility, a quick decision-making pace, and often offer lower remuneration than that in large corporations.

Anil Agarwal, CEO and cofounder of InCruiter, a talent assessment service, said that laid-off IT professionals end up at AI startups, particularly in roles that demand strong engineering fundamentals or data skills. “These professionals bring with them problem-solving abilities, system knowledge, and process discipline, making them valuable in the short term.”

The Cost-Benefit Trade-Off

The choice between retraining laid-off IT professionals and hiring AI-native freshers is not straightforward. 

Agarwal explains that the trade-off hinges on time-to-productivity and training costs. Retraining IT professionals might require a greater upfront investment, but it offers the benefit of maturity, lower attrition, and domain knowledge that can be critical in project management and system integration.

“Freshers with AI skills can be immediately deployable, but they sometimes lack domain depth and business alignment. Startups balance these options by role-criticality, choosing retraining for core projects needing reliability, and freshers for experimental or high-volume work,” Agarwal said.

The key, according to Gaur, is strategic integration: startups should ensure that these professionals align with team culture and are given clear, challenging roles to avoid frustrations that might arise from mismatched expectations.

Reskilling and Retention

Co-investing in reskilling could benefit everyone involved. Agarwal highlighted that investors could help startups access a strong pool of AI-ready talent, while professionals enjoy career growth and improved retention. Sharing training resources could reduce costs, and by institutionalising reskilling, startups could scale faster despite talent shortages.

This approach could help startups cut redundant costs, as shared training infrastructure would enable them to scale talent acquisition without being hindered by talent shortages or inflated hiring costs. As Agarwal explained, “Reskilling creates a feedback loop where both startups and professionals benefit, leading to better retention and faster scalability.”

“We have observed this often among our client partners… where enterprises are adding a layer of generative AI knowledge to their workforce to make them more efficient and, of course, productive,” Ritesh Malhotra, enterprise head at Great Learning, told AIM. He said that developing talent internally saves time and lowers recruitment costs, improving the return on investment. 

The Efficiency Gap

The ‘efficiency gap’ poses a significant paradox in India’s ambition to become an AI superpower, where high investor valuations conflict with low productivity per capita, Gaur added. 

While a large talent pool and domestic market attract investment, inefficiencies, due to inconsistent infrastructure, skill gaps, and bureaucracy, prevent Indian firms from providing the scalable solutions that justify these valuations. Gaur emphasised that this could lead to perceptions of an overvalued ecosystem deterring long-term investment.

Additionally, despite producing millions of STEM graduates, many are stuck in lower-margin roles like data annotation instead of driving high-value innovations such as foundational model development.

“This not only underutilises their potential but also risks cementing India’s position as a service provider rather than an AI leader, struggling to match the innovative output of hubs in the US or China,” Gaur said.   

What can Regional Universities and Governments do?

In light of the growing demand for AI talent, regional universities and engineering colleges are expected to play a crucial role in closing the talent gap. 

Gaur said that IIT Kanpur established the Wadhwani School of Advanced Artificial Intelligence and Intelligent Systems in April 2025, dedicated to AI, cybersecurity, robotics, and AI policy.

Currently, at least 11 of the 23 Indian Institutes of Technology (IITs) offer BTech programs in AI-related fields such as Artificial Intelligence and Data Science. IIT Kharagpur and IIT Madras launched their AI-focused BTech programs in 2024, he added. 

“Ultimately, performance in a corporate setting isn’t solely dependent on foundational knowledge and is also driven by adaptability, problem-solving abilities, and diverse perspectives. Success is a highly individual matter, governed more by a person’s willingness to learn and grow than by their alma mater,” Malhotra concluded.

As AI startups in India navigate the complexities of hiring laid-off IT talent, it’s clear that retention will be key to ensuring long-term success. While the short-term benefits of hiring experienced professionals are evident, startups must invest in training, cultural alignment, and growth opportunities to truly leverage this talent pool.

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