The current disengagement in the workforce is pervasive and teetering on the edge of explosive. In short, people aren’t happy with the current arrangement of working in an office eight hours a day, five days a week for an employer who, in return, offers little to no stability. Pair that with an inconsistent rhetoric around the impact of AI on the job market and you have a scenario where people are deeply mistrustful, burned out, and fearful of what the next source of income stability may be. “This world of work was always built to be broken when it comes to humans, and the labor market has been explicitly exploitative,” says Aneesh Raman, Chief Economic Opportunity Officer at LinkedIn and former speechwriter to Barack Obama. But Raman thinks that by shifting the focus to skills rather than jobs and embracing an entrepreneurial spirit, we can build something better to take its place.
At a recent LinkedIn event in London, Raman explained how he sees work shifting from the current knowledge economy to an innovation economy. The innovation economy is based on creativity and new ideas — and it’s this creativity that is going to be a driver of growth. It’s also something AI will struggle to replace. “In some parts of the world, including Silicon Valley, there is a view that the most efficient way for AI to grow the economy is a billion-dollar business with no employees. Obviously, I think that’s misguided given all the human capability that’s going to come to the center. But I think what is possible is a billion-dollar person who has never had to work at a company, and that’s going to completely change how work works,” says Raman. What Raman is tapping into is a sense of optimism and opportunity. It’s not about what jobs are left after AI becomes embedded in the mainstream; it’s about what new opportunities exist because of it. “It’s not just innovation at work as employees, but innovating at work as entrepreneurs,” says Raman. “With people questioning why they work, not just what they do, mixed in with these big technological changes that are happening, I think we’re entering an entirely new dynamic for what is work.”
How long until this shift to an innovation economy is a reality? After all, the rhetoric around the pace of change doesn’t seem to match the actual pace of AI adoption, creation, and displacement. “I think for most people it will feel like it’s slow until it’s fast,” says Raman. “More of us are thinking about the new way work should go. Some of us are creating entirely new jobs based on the moment we’re in and leveraging skill sets in ways that org charts might not have allowed.” But Raman acknowledges that companies and social structures will require more time to catch up. The current system isn’t set up for a network of freelancers or to grant opportunities equally to everyone. “We’ve got to create more of an environment of dynamism in our economies for individuals to be more entrepreneurial. It’s on societies to structure the social economic security in a way that supports innovation.”
Additionally companies — despite all the talk about skills-based hiring — aren’t doing a great job of identifying what they have and what they need to embrace this shift. Raman thinks better data can help bridge the gap. “This is a big moment for people analytics,” says Raman when asked how companies can accurately assess what they need. “Many of us have been talking about skills for ages, but it didn’t take off because it wasn’t as easy to filter for skills as it was for degrees. Generative AI has changed all that because jobs are no longer titles. The only way to understand what a job is is as a set of tasks. Some of the tasks AI will do, and then some of the tasks will be uniquely ours to do based on our core human capabilities.” Raman defines those capabilities as communication, creativity, compassion, courage, and curiosity.
That still leaves the question of how companies can screen for and measure those skills. “We have a lot of work to do to credential and assess human capability because we’ve never put any effort into it,” says Raman. “For 100 years now, we’ve built all these systems of teaching, training, credentialing, and assessing around technical skills.” That approach may have worked for the knowledge economy, but it won’t get people very far in the innovation economy. “How do we help people who have never been taught how to think about courage, compassion, or creativity?”
This shift to an innovation economy should also help inject a sense of hope in those who are feeling down about the current job market. “We know that people are less confident right now,” Raman acknowledges. “People feel down about their career prospects. The biggest thing I can say is that feeling is based on a correct belief of old that our opportunities as workers were dependent upon the company’s benevolence as an employer, and that is ceasing to be true by the day.”
Ultimately, AI adoption isn’t going to be the biggest challenge. It’s innovation — and what humans can dream up. Raman articulates this idea quite powerfully. “The people that are the most curious uncover the greatest agency.”