nimayaAI is changing the way we work, but access to that change is far from equal. For many young women entering the workforce, the challenge is not simply learning a new technology. It is having the right tools, the confidence to use them, and access to skills that will continue to matter as jobs evolve. Nimaya is one of the organisations driving this initiative forward.
The Nimaya Foundation is a not-for-profit career accelerator, co-founded in 2021 by Navya Naveli Nanda and Samyak Chakrabarty. The foundation works towards ensuring young women from disadvantaged and restrictive backgrounds in India are not left behind as AI rewrites the world of work. So instead of training its "Nimaya Naaris" in traditional vocational skills that are already fading, it trains them in Generative AI, digital literacy, and workplace thinking that decides whether a first job becomes a first career.
The organisation has reached more than 10,000 learners across five states and has collaborated with the Government of India’s AI Mission. It is also building an AI-powered learning platform and designing capstone projects that allow participants to leave with something more useful than a certificate.
For this edition of Stories of Impact, we spoke to both founders about what that change actually takes.
The gap, Samyak Chakrabarty says, was never that nobody was training young women because plenty of people were. The problem was what they were being trained for. "Walk into most skilling programmes, and you'll find tailoring, beauty, data entry, basic MS Office," he says. "Honest skills, but they sit exactly in the path of automation." Most curricula also treat confidence and communication as an afterthought, when that's often what decides whether someone survives month three at a job. Nimaya, he says, came from one conviction, and that a woman's background should be her starting point, not her ceiling.
Why AI specifically? "For the first time in my working life, the entry barrier to a powerful technology is language, not capital or code." A woman entering the workforce now has no old habits to unlearn, so she can end up more fluent with these tools than the person interviewing her.
But he's careful not to oversell it: "AI doesn't hand anyone a career. It multiplies whatever judgement you bring." Which is why half of Nimaya's forty programme hours go into workplace thinking and placement readiness, not tools alone.
Nimaya designs for transfer, not for tools, because every tool taught will look different in eighteen months. Prompting, verification, knowing when an answer is technically right but wrong for the room these things transfer. Practically, it comes down to the first 90 days (where most jobs are actually lost, so Nimaya teaches office jargon, POSH, money, digital hygiene) and staying involved after placement through a coaching bot and a twelve-month Fellowship.
On measuring impact, he says, "Trained headcount is the easiest number to produce and the least meaningful." What he watches is retention and trajectory, and if the woman is still employed at twelve months, did she negotiate a raise, did she move upward on her own. The most honest signal, he thinks, is usage, and if she still opens these tools three months later, unprompted, to solve something nobody taught her. He admits agency and confidence are the real product, and the hardest things to measure rigorously.
During the initial days of Nimaya, three things surprised Navya Naveli Nanda. First, that ambition was not missing; second, that the women who struggle most in week one are often the most capable in the room; and third, that the fear of AI that dominates corporate conversations barely exists here. "She isn't scared the machine will take her job. She's scared of looking stupid asking a basic question." The barrier, she realised, is social, not technological.
Navya shares that a moment that stayed with her was with Chandani, from Faridabad, who arrived not knowing what "prompting" meant and left freelancing for a local cafe, a job she found and pitched herself. "She wasn't a beneficiary being placed somewhere. She was a person a business chose to pay."
Nimaya treats the first job as the start of its work and not the end, because the real reason careers plateau is because of having nobody to call when something goes wrong in month four. Privileged workers ring an uncle or a family friend; Nimaya's participants often can't. So the network is built deliberately, through a year-long Fellowship, senior mentors, live company projects, and a coaching bot that alumnae keep using, plus a steady push towards a second income, because one employer isn't a career.
When discussing the barriers that don't make it into reports, she says, are just as hard as fees and mobility above all. And the deepest barrier is that failure isn't judged equally: like a privileged man's failed attempt becomes a dinner-party story but hers becomes proof she shouldn't have tried. "The job isn't to tell her to be braver. It's to lower the cost of her first few attempts."
On AI, she pushes back gently on easy optimism. "The moment you decide the simplified curriculum is good enough for her, you've rebuilt the exact hierarchy you claimed you were dismantling."
Thus, for Nimaya, the goal is to give women enough understanding to use it as a tool for work, income, and independence. It is part of a larger shift in how young women are prepared for the future, not by lowering the ambition of the opportunity, but by giving them the skills and support to meet it.
That is where Nimaya's impact lies. It is about what happens when a woman who was once being prepared to fit into the workforce is instead given the tools to help shape what that workforce becomes.