Is the org chart dead in the age of AI? LinkedIn’s chief economic opportunity officer thinks so
The humble org chart isn’t usually blamed for holding back innovation. But as companies push their employees to adopt AI, LinkedIn executive Aneesh Raman thinks the relationships that structure most workplaces are what’s holding things back.
“The org chart was built in the industrial age to bring order, predictability, and stability to rapidly growing organizations,” says Raman, LinkedIn’s chief economic opportunity officer and co-author of a new book on the future of work. “Companies need to let that go, as it’s going to hold back innovation.”
Instead of waiting for top-down transformation programs, Raman argues, executives will need to get comfortable with workers figuring out AI on their own, even if those experiments cut across departments and job descriptions. “Where you’re going to see the real returns on AI isn’t just a new workflow around AI, but rather new work around human capability,” he says.
Raman, a former CNN war correspondent and Obama speechwriter, is the co-author of Open to Work: How to Get Ahead in the Age of AI, alongside Linkedin CEO Ryan Roslansky. The book draws on LinkedIn data and case studies of early adopters to offer what he calls a “how-to-human-with-AI” playbook that tries to counter the “fatalism” that dominates most conversations about AI’s effect on employment.
Courtesy of LinkedIn
He urges workers to think about their work, and how AI relates to it, in three categories. The first bucket covers activities AI already does today, like generating code, running quick analyses, or writing a first draft to inspire someone else’s writing. The second bucket are experiments to create something new with AI. The final bucket involves using the time saved from the first bucket, and the lessons learned from the second bucket, to start using AI as a group. “What are you doing with other people?” he asks.
“It’s going to be a worker-led transition, and so companies are going to have to figure out how to let individuals start to move into this new era in their day-to-day work,” Raman says. “We have more autonomy than we often think in terms of pushing for what we want to do that might push our work to the next level.”
What skills will matter in the AI workforce?
LinkedIn is in the middle of a pivot to what it calls a “skills-first approach” to hiring and employment. In theory, employers are looking for specific skills and capabilities—and proof that potential hires have those skills—instead of just looking at a list of job titles on a resume. LinkedIn is also integrating AI into its own product, such as a new AI agent to help with hiring.
But as AI’s capacity to automate knowledge work grows, there’s still confusion over what skills employees will need. Take coding: For more than a decade, universities and policymakers told young people that learning to code was the surest path to a high-paying job. That advice looks less certain in the age of “vibe-coding”: Claude developer Anthropic now sees computer and math careers as leading the way in terms of current and possible coverage by AI.
Raman, for his part, thinks computer science isn’t obsolete. Instead, employers need to look at the broader skills a degree like computer science provides. “A computer science degree doesn’t just teach coding alone. It teaches complex thinking, organizational design, and structures of systems” he points out.
Workers, at least in the U.S., aren’t convinced they will come out ahead. A CBS News poll released last week reported that two thirds of Americans believe that AI will decrease the number of jobs; around the same share don’t believe that tech companies will use AI in appropriate ways.
AI could get more traction in Asia, where populations are more comfortable with AI. A Pew Research Center survey from October found lower rates of concern among Asia-based respondents than Western ones. For example, just 16% of South Koreans reported being “more concerned than excited” about AI, the lowest share among the 25 countries Pew surveyed; the U.S., in contrast, had the highest share, at 50% reporting concern.
More recently, Chinese consumers have flocked to install OpenClaw, the open-source AI agent framework, on their devices, and local governments are rushing to support “one-person companies,” or AI startups trying to build new products.
“There’s a hunger in Asia, not just among companies but also among workers, to learn about these tools and put them to use,” Raman says. “There’s an entrepreneurial culture in a lot of countries in Asia.”
Time to adapt
Still, Raman is sympathetic to workers concerned about automation. “There was a career ladder, and there was extreme clarity about what you had to do to get on each rung of that ladder,” he says.
But he’s optimistic that, ultimately, employees will be better off as AI starts to dismantle the ways companies traditionally organize and reward their talent. “Very few people have ever had real control over their career,” he says. “Because of AI, I think we’re about to have the first generations at work that have more control over their career than any who’ve come before.”
But what if someone doesn’t want to be an innovator at their job? What if someone wants to do their responsibilities and earn a stable wage?
Raman’s answer to those people is direct: “Nobody is coming to save any individual but themselves.”
Change is coming, like it or not. “It’s just a question of when this change hits you, and how hard it hits you,” he says.