TeamLease Turns Career Returners Into an AI Talent Bet
With AI salaries climbing and job-ready talent in short supply, the staffing firm is pushing returnships from an inclusion tool into a mainstream hiring strategy.
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India’s scramble for AI talent is pushing companies to reopen the hiring pool, with TeamLease Digital launching POWER, or Professional Opportunity for Workforce Empowerment and Reboot, to bring experienced professionals back into digital and AI roles through a structured returnship program.
Its first initiative, the AI Career Accelerator Returnship Edition, has completed its inaugural cohort, with participants now entering hiring pipelines across the country.
A returnship is a time-bound, often paid pathway designed to help professionals who have taken a career break re-enter the workforce through training, mentoring and project-based work.
Once largely framed as a diversity-focused intervention, the model is increasingly being recast as a practical hiring tool for employers struggling to fill specialist roles.
The shift comes as demand for AI talent continues to outpace supply. TeamLease Digital said salaries in some AI roles have surged two to four times, while India faces a 53% gap in AI-ready professionals, prompting companies to look beyond traditional hiring channels and invest in reskilling experienced mid-career talent.
What were once seen as diversity-led initiatives are now becoming a core hiring strategy. Structured returnship programmes, typically paid and time-bound, are increasingly being used to onboard professionals who stepped away from work due to caregiving or personal commitments.
The shift is driven as much by economics as inclusion. With hiring costs rising and skilled talent in short supply, companies are embedding such programmes into long-term workforce planning rather than treating them as one-off efforts.
Data from multiple returnship initiatives shows conversion rates to full-time roles averaging around 70%, with some programmes reaching up to 80%. Employers also point to the advantages returners bring, including prior domain experience, professional maturity, and stronger retention.
The returnship model itself is not new. Goldman Sachs pioneered the concept in 2008, while JPMorgan Chase runs a structured 15-week paid programme to transition professionals back into full-time roles.
In India, Wipro has reported close to 80% retention among hires through its ‘Begin Again’ initiative in FY24–25, with internal assessments suggesting costs comparable to conventional hiring.
These outcomes are reinforcing the idea that returnships can serve as a scalable and sustainable talent pipeline, particularly in high-demand fields like AI, cloud, and cybersecurity.
Parallel to this trend, more women are entering AI-focused learning programmes. Their share in STEM upskilling has risen from 22% in 2018–19 to 33% in 2023, while women now account for 36.2% of tech roles in India.
Online learning platform Coursera reported a 195% year-on-year increase in women enrolling in GenAI courses in 2025, with 3.6 million AI course enrollments across the country.
The broader shift also reflects how companies are beginning to tie inclusion directly to performance. Organisations with higher gender diversity are estimated to be 25–30% more likely to outperform financially, according to industry benchmarks cited in the analysis.
As a result, Indian employers are increasingly formalising inclusion through structured hiring programmes, signalling a move from intent to measurable outcomes.
Commenting on the trend, Neeti Sharma, CEO of TeamLease Digital, said, “India doesn’t have an AI talent shortage—it has an access gap. A significant portion of experienced talent sits outside the workforce today: women on career breaks, ready to return. With structured returnship pathways, this cohort brings proven domain expertise, maturity, and execution discipline—making them high-impact contributors to AI and digital teams from day one.”
She added that research points to a 25–50% talent shortage across AI, cloud, and cybersecurity, with just one qualified engineer available for every ten GenAI roles. This gap reflects a growing mismatch between supply and rapidly rising demand. Addressing it will require activating new, scalable talent pipelines focused on deployability and real business outcomes.
