‘AI is actually more aligned with the builder mentality that has always existed in India’: Aneesh Raman of LinkedIn

Early on in their new book, Open to Work: How to Get Ahead in the Age of AI, authors Ryan Roslansky and Aneesh Raman, EVP of LinkedIn and Microsoft Office and chief economic opportunity officer at LinkedIn respectively, offer sage advice. In “moments of existential crisis,” they write, “the choice isn’t between success and failure; it’s between action and paralysis.” The crisis they refer to is the adoption of AI in workplaces around the world, giving rise to fears of job loss, but unlike many big-tech leaders, Roslansky and Raman aren’t interested in peddling hollow assurance or acting gung-ho about the AI revolution.

As leaders of a professional networking platform with over one billion users, they approach AI’s impact from a data-rich perspective, offering practical tips on keeping the fire of humanity burning, and helping imagine a future where new tech will define new categories of work rather than simply leave people unemployed. Organizations will need to “fundamentally rebuild structures around AI” instead of trying to tack it on to existing structures. Workers, in contrast, will have to double down on “soft skills”—the authors suggest a 5C framework—to remain relevant and irreplaceable in the age of robots.

San Francisco-based Raman spoke to Mint about the future of work and AI by email. Edited excerpts:

The book advocates for a skills-first hiring approach over traditional degrees. But degrees and past brand-name employers currently serve as “trust proxy” for recruiters. If we strip those away, how do we prevent the process from becoming biased towards those who are simply better at gaming AI-driven skill assessments?

Hiring for elite degrees and brand-name employers became shortcuts because actually understanding what someone can do takes time and processes most companies didn’t have. But AI is a tool that can finally help employers do that at scale. It can analyse work samples, assess problem-solving approaches, and identify skills in ways that weren’t possible before. The key is that AI is only as good as how we design and oversee it. If you design a system to screen people out who don’t have the pedigree, AI will help you do that efficiently. But if you design it to screen people in, based on demonstrated capability across a wide variety of backgrounds, AI can do that even better.

The other key shift accelerating skills-first hiring is that the new resume isn’t where you went to school. It’s your work product. At LinkedIn, we already have certain entry-level roles where we don’t ask for your resume. We ask you to show us what you’ve built. What used to take months and real capital can now be tested over a weekend. AI has put tools in people’s hands that used to be reserved for those with resources and connections. That’s opening doors for a lot more people to go build and then get hired for what they’ve built.

AI is exceptionally good at the tasks traditionally assigned to junior employees. If the entry-level rung of the career ladder is automated, how do we develop the next generation of experts who historically learned by doing grunt work?

Work is changing, not ending and that’s as true for entry-level jobs as for any other. Entry-level jobs are core to how individuals build careers, how companies build leaders, and how societies build economic mobility. They aren’t going anywhere.

What is changing is the shape of the work itself. For people just entering the labour market, the grunt work getting automated presents new opportunities. It means more entry-level workers get to skip straight to the more interesting, strategic parts of work. Instead of spending two years formatting decks or pulling data, you’re building things, solving problems, working alongside senior people from day one. The learning curve doesn’t disappear; it just changes shape. And this generation is better positioned than any before them to navigate that. They are an AI-fluent and entrepreneurial-minded generation, and they will bring new ideas and thinking that companies need to grow. If you’re a company, you want to be hiring from this group right now.

You speak about the need for constant learning. But for the average worker, constant pivoting can feel like a recipe for burnout and financial instability. At what point does the responsibility for re-skilling shift from the individual to the corporation or the state?

Constant learning doesn’t mean a complete overhaul of your skills overnight. The workers navigating this moment best identify their core strengths, build on them, and then stay curious enough to adapt day-by-day as their job changes and new tools emerge. That’s a different posture than reinventing yourself every six months. And it’s about small steps not big leaps.

The responsibility here is distributed, and each actor has a distinct job to do. The individual’s job is to stay curious and keep adapting as the work changes around them. The employer’s job is to invest in the infrastructure that lets them do it—career-driven learning programmes, internal mobility, exposure to new tools on the job. The encouraging signal here is that 79% of Indian companies we surveyed said they planned to maintain or increase their investment in career-driven learning in 2025. The government’s job is the broader infrastructure layer: democratizing access to AI tools, supporting local-language capability, and building AI fluency into the national workforce. India is moving in the right direction on all three fronts.

Issues arise when any one of these three players puts its share of responsibility onto the others, like when companies expect workers to reskill entirely on their own time, or when governments expect companies to solve population-scale challenges alone. Getting this right is the difference between an AI era that expands opportunity for more people and one that concentrates it among fewer.

While the book offers a road map for the future, there is a growing demographic of mid-career professionals whose high-salary roles are being hollowed out by AI. Beyond just learning AI tools, what is your specific advice for the 45-year-old manager whose specialized expertise is being automated faster than they can pivot?

Work is changing for everyone, and mid-career professionals are not exempt. What got you here is not going to get you to the next stage. So yes, you’re going to have to reinvent yourself a bit. That can feel like an impossible task when you’re 45 and you’ve spent two decades building expertise, but it doesn’t have to be. As we write in the book, you don’t need to overhaul everything overnight. But you do need to start.

Here’s where I’d start: forget the job title. Think about your job as a set of tasks. Last week, you probably did a dozen tasks that mattered. Start bucketing them honestly. Bucket one is what AI can already do: quick analysis, first drafts, research, routine reporting. If you’re not sure what goes in that bucket, that’s issue number one. You have to be using these tools, in new ways, not just one chatbot you treat like a better search engine. Bucket two is what you’re doing with AI to up-level your own work and thinking. Build that bucket. Bucket three is what you’re doing with other people that’s genuinely new…. It’s a bunch of people with a bunch of AI tools doing big new things together. If you’re heavy in bucket one, start looking at adjacencies. If you’re in sales but you’re good at the marketing side of what you do, grow into that. Don’t worry about doing your boss’s job. Worry about the skills you uniquely bring.

You write that the "where" of work is changing. Yet many leaders argue that remote work erodes the social capital and network that your book suggests is vital for career resilience. How do we reconcile a global, skills-based talent marketplace with a deeply human need for localized, high-trust work cultures?

Different kinds of work require different environments, and there is no one org chart structure or office policy that works for every company. We saw this come to a head during the pandemic. When entire sectors moved remote overnight, productivity in many places actually went up. Meetings that couldn't possibly be emails became emails.

But here's the deeper insight from the last five years: a global, skills-based talent marketplace doesn't erode high-trust culture. It demands more of it. When your team can be anywhere, culture stops being something that happens by accident in the hallway. It becomes something you have to deliberately design. The companies that struggled with distributed work weren't the ones with globally dispersed teams. They were the ones who assumed culture would take care of itself. The companies that thrived — including a lot of Indian startups that went remote-first during the pandemic — invested deliberately in how people connect, build trust, and learn from each other across geographies.

For Indian companies especially, this is familiar territory. India has always had a distributed workforce — across states, languages, and time zones — and has always had to build trust across those differences. That's an edge in a global skills marketplace, not a burden. The important question isn't where you log on every morning. It's whether you're in a culture that's genuinely experimenting with new tools, leaning into this moment rather than waiting it out, and building the human skills that make your people resilient as work keeps changing. That's what separates the companies that stall from the ones that find a new gear.

As AI masters hard skills, you argue that behavioural skills will command a premium. Do you foresee a future when technology will become mature enough to erode the importance of these?

AI can process patterns at extraordinary speed. It can simulate conversation, optimize solutions, and generate first drafts faster than any human. But there is a meaningful difference between simulating something and actually doing it. Part of the reason people are so pessimistic about AI replacing us at work is that we've never done a good job defining what makes humans unique in the first place. Ryan and I spoke to neuroscientists, behavioural psychologists, and workplace experts and landed on five capabilities we call the 5Cs: curiosity, creativity, courage, compassion, and communication.

AI can help us with these, even mimic these. But it cannot replace them. Curiosity isn't just gathering information. It's wondering why things are the way they are and what happens when you push against those assumptions. Compassion without truly caring about another human being is performance. Courage requires something real to be at stake. These capabilities are the engine of human innovation, and we spent a century undervaluing them as "soft skills" because they were hard to measure. As AI takes over more of the efficiency work, people get time back to practice and develop these capabilities. AI can do a lot. But so can humans.

In a conservative market like India, where career life cycles have tended to follow a beaten track for decades, how do you foresee the influence of AI on workplace cultures?

India has always had an extraordinary entrepreneurial spirit, and AI is about to underscore that. We're already seeing it in the data. Conversations on LinkedIn about entrepreneurship have been surging, and India is one of the markets leading that trend. The number of people adding "founder" to their profiles jumped 67% from 2024 to 2025 across major economies.

The old career ladder, pick a lane, stay in it, work your way up, was never really built for how Indians think about ambition and hustle. AI is actually more aligned with the builder mentality that has always existed in India. You no longer need to raise capital to think like an entrepreneur. You need curiosity, a willingness to experiment, and access to tools that can now help one person do what used to require a whole team. Small and medium businesses are the backbone of India's economy, and they stand to gain enormously from this. AI gives a local business owner insights that once required hiring a team of analysts. It helps the people you already have do more sophisticated work. The career life cycle is not narrowing in the age of AI. For people willing to think like builders, it is opening up in ways we have not seen before.