Hello, and welcome back to Inc.'s 1 Smart Business Story. As anxiety grows over AI replacing jobs, LinkedIn CEO Ryan Roslansky and chief economic opportunity officer Aneesh Raman argue the opposite: AI is making entrepreneurship more accessible than ever. In their new book, Open to Work, they lay out how AI lowers traditional barriers to starting a business—capital, expertise, and gatekeepers—by giving individuals tools to build, test, and scale ideas quickly. Drawing on founder case studies and new research, the book reframes AI as an accelerant for ownership rather than a threat to work, and suggests opportunity will increasingly come from unexpected people and places.

In this article you’ll learn:

• Why LinkedIn believes AI lowers the barriers to becoming a founder

• How AI is shifting work away from titles and toward skills

• What this means for where the next generation of startups will emerge

BY KAYLA WEBSTER, STAFF EDITOR

In a new book, LinkedIn executive Ryan Roslansky and Aneesh Raman argue that AI is dismantling the traditional gates to starting a business.

As workers worry that AI will automate their jobs away, LinkedIn CEO Ryan Roslansky and Aneesh Raman argue something different: AI is about to make entrepreneurship far more accessible. That’s the thesis of Open to Work: How to Get Ahead in the Age of AI, LinkedIn’s first book, released today. Co‑authored by Roslansky and Raman, the book lays out how AI can strip away many of the traditional barriers to starting a business—capital, gatekeepers, specialized expertise—and replace them with tools that let individuals build, test, and scale ideas on their own terms. Drawing on founder case studies and research from MIT Sloan senior lecturer Paul Cheek, the book frames AI not as a threat to work, but as an accelerant for self‑employment and ownership.

Raman’s own career mirrors that premise. His path—from CNN correspondent to presidential speechwriter to LinkedIn executive—wasn’t linear, but it was intentional. Each role, he says, was a way to expand impact and adapt as opportunity shifted. In Open to Work, Raman connects that mindset to the moment founders now face in a labor market where titles matter less than skills, and where AI can help individuals turn experience into businesses faster than ever before.

I sat down with Raman and Cheek to discuss the book and its practical applications.

In this piece, you’ll learn: 

Kayla Webster: Can you tell me why now is the right time for LinkedIn to publish a book?

Aneesh Raman: For the past couple of years, we’ve watched the conversation around AI become increasingly fear‑driven. Workers look at headlines predicting either total job loss or unrealistic utopias. What’s been missing is a grounded, human‑first explanation of what’s actually happening—and practical guidance on what individuals can do about it. That’s what motivated us to write this book.

Workers’ fears aren’t unfounded. CEOs often cite AI as a catalyst for layoffs. With that in mind, what should workers be doing right now?

Raman: The worst thing we can do is sit back and wait for CEOs to figure it out. Historically, big shifts—like the move from steam power to electricity—fell flat until leaders reimagined work entirely. Companies today are struggling because they’re bolting AI onto old workflows. The real gains will come when workers start using these tools to build new ways of working. Don’t cling to your job title. Look at the tasks you do in a week, decide which ones AI can take off your plate, and focus on the parts that require your uniquely human judgment.

You mention in the book examples like switchboard operators or ATMs—moments when automation didn’t kill jobs but transformed them. Are we seeing that dynamic now?

Raman: Absolutely. Software engineering is a great example. People assumed AI-generated code would make the role disappear. Instead, we’re seeing the job evolve. Some companies now hire engineers with philosophy backgrounds to help guide ethical judgment. Engineers are spending more time with customers because communication skills matter more. AI is shifting jobs toward the human-to-human elements—and that’s a huge opportunity.

The book makes a bold claim that AI will democratize entrepreneurship. That’s a big statement, especially at a time when CEOs are using AI as a justification for layoffs. Why do you believe that?

Raman: Historically, becoming an entrepreneur required two things: belief and resources. Most people didn’t think they had either. Now, AI fills the knowledge gaps—you can ask it how to build a business, how to market an idea, even how to prototype an app. We’re already seeing everyday people create tools based on their lived experiences. That’s the start of an innovation explosion. And it’s going to come from everywhere, not just Silicon Valley.

Paul Cheek: One of the biggest misconceptions is that entrepreneurs are born, not made. That’s just not true. Entrepreneurship can be taught, it can be learned, and we now have data to prove it.

At MIT, we ran a longitudinal study on founders who came through our accelerator building what we call innovation-driven enterprises—companies with an innovative product that scale not only in revenue but in positive societal impact. We found that 61 percent of them were successful.

When I ask audiences what they think the average startup success rate is, people say one percent, maybe 10 percent if they’re feeling optimistic. In reality, it’s low single digits. So when you see 61 percent, it tells you that if you teach people a structured, rigorous way to pursue entrepreneurship, you can dramatically increase their odds of success.

What’s different now is that AI is taking what used to be a major advantage—having a sophisticated business plan and go‑to‑market strategy—and putting it within reach of anyone with an internet connection. Ten years ago, that edge mostly belonged to people with access to elite education, capital, or networks.

Today, anyone can ask an AI to help them generate a high‑quality, research‑backed business plan, refine their target customer, design a business model, sketch a go‑to‑market strategy. That doesn’t erase every structural disadvantage, but it flattens the starting line in a way we haven’t seen before.

You’ve (Paul) said the “cost of creation” has collapsed. What does that actually mean for a first‑time founder?

Cheek: Historically, building an innovation‑driven company required two big things: a lot of time and a lot of risk capital. You needed teams of experts working for years, plus significant investment, just to get a product to market.

AI now attacks both of those constraints. It lets a small team—or even a solo founder—do, in months or weeks, what used to take years. The time required shrinks, the amount of money required shrinks, and all of a sudden far more people can realistically say, “I could build something meaningful.”

We’re already seeing examples. Companies like Cursor and Lovable have hit serious revenue milestones incredibly fast with tiny teams. Cursor went from zero to around $100 million in annual recurring revenue in under a year with about 20 people. That would have been unthinkable a decade ago.

To me, that’s what democratization looks like in practice: more people, in more places, able to build high‑impact companies with far fewer resources.

A lot of people hear that and immediately think, “Okay, so AI replaces jobs.” Are we actually looking at fewer jobs—or just different ones?

Cheek: If you zoom out historically, new technologies tend to create more jobs than they displace. I think AI will follow that pattern—but only if we have more entrepreneurs creating those jobs.

I actually worry less about “AI replacing workers” and more about AI‑enabled companies replacing companies that don’t use AI at all. In other words, if your competitors are using AI intelligently and you’re not, it’s the business that’s at risk.

That’s why I’m such a proponent of entrepreneurial thinking inside existing organizations. We need people in big companies, in government, in nonprofits who behave like entrepreneurs—who do more than is reasonable with the resources they control. And they need to be using AI in an entrepreneurial way: launching new products, new business lines, new experiments, not just cutting costs.

We tend to picture “startup land” as San Francisco or New York. Does AI actually change the geography of opportunity?

Cheek: I think it does. You still see the usual tech hubs—San Francisco, New York, Boston—further along in formal AI adoption. But in terms of entrepreneurial opportunity, AI is making it possible for people to start and scale companies from anywhere.

The cost of building has gone down. The tools are available globally. Distribution for digital products is global by default. So if you’re in “Middle America” or a smaller city, you don’t have to move coasts to participate in this wave.

We’re already seeing it in the data. “Founder” is now one of the top job titles being added on LinkedIn. Organizations like the Kauffman Foundation are also seeing an uptick in entrepreneurial activity. To me, that’s strong evidence that people everywhere are starting to act on this new set of possibilities.

If you could leave Inc.’s readers—founders, startup employees, and would‑be entrepreneurs—with one message about AI and entrepreneurship, what would it be?

Cheek: There has never been a better time to invest in both AI and entrepreneurship—but more importantly, in the integration of those two. We’re at a really important moment in history, and I want people to recognize that they’re capable of seizing the opportunity in front of them.

And for someone who’s curious, but doesn’t quite feel like “an entrepreneur” yet, what’s one concrete thing you’d have them do?

Cheek: Take a day off just to tinker with AI. Most companies don’t carve out time for experimentation because there are always deadlines and deliverables. But if you give yourself a full day to explore tools, test ideas, and see how quickly you can bring even a small concept to life, you’ll build the AI literacy and confidence that lets you be more entrepreneurial—whether that’s in your current role or in something you eventually build for yourself.

Raman: Just start. Use these tools in your day‑to‑day—on something small, something tedious, or something that scares you a little. Notice where you feel energized. AI isn’t the point. You with AI is the point. You’re building the future version of yourself: the one who learns faster, builds faster, and believes more deeply in their own potential.

This interview has been edited for length and clarity.