While most people agree that some job roles will become obsolete with the advent of AI, it could also lead to an even larger number of jobs being created.
This optimistic vision comes from Vlad Tenev, CEO of Robinhood, the popular stock trading platform. In a recent talk, Tenev introduces a fascinating counterpoint to the doom-and-gloom narratives around AI-driven unemployment. Rather than focusing on job displacement, he proposes the concept of a “job singularity,” drawing a parallel to the AI singularity that researchers often discuss. His perspective is particularly intriguing because it reframes our understanding of what “work” might look like in an AI-powered future.
“AI researchers talk about this idea of a singularity, an intelligence explosion, but what we see in the data is that we’re also on a curve of rapidly accelerating job creation, which I like to call the job singularity,” Tenev explained. “A Cambrian explosion of not just new jobs, but new job families across every imaginable field where the internet gave people worldwide reach. AI gives them a world class staff.”
The Robinhood CEO’s vision extends beyond simply more of the same kinds of jobs. He anticipates fundamental shifts in how work is organized and executed. “If you look at this cloud of jobs, certainly there’s gonna be some jobs that we can’t predict yet, but I think we can make some predictions,” he said. “There’s gonna be a flurry of new entrepreneurial activity with micro corporations, solo institutions, and single person unicorns. Which by the way, I don’t think we’re very far from.”
This idea of dramatically smaller organizational units isn’t entirely theoretical. Companies are already experimenting with AI-augmented workforces. McKinsey, for instance, now has 60,000 people on its roster, but 20,000 of them are AI agents, fundamentally changing how the consulting giant operates.
Perhaps most provocatively, Tenev suggests that future jobs won’t even be recognizable as “work” to us today. “Another defining feature of this job singularity is that when you look into the future, the jobs will not look like real work. Much like to our predecessors, our current jobs would’ve looked like leisure,” he noted. “We have people getting paid to play video games, eat at restaurants, travel, and talk to their friends on video. Those last people we called podcast bros. And we take our jobs very seriously. Those of us that do well, certainly wouldn’t say it’s easy, but if you took someone from the 20th century, when people first started contemplating these problems and they could peek into our world today, they would think that all of the predictions around technological unemployment came true. They’d say, we don’t have any more jobs. And I bet that we would feel the same about our descendants in the future.”
Tenev’s perspective stands in interesting contrast to other tech leaders who have acknowledged the disruptive potential of AI. OpenAI CEO Sam Altman has stated that people will lose jobs to AI and that the definition of work will change, while ChatGPT’s founder has warned that AI will disrupt white-collar and creative jobs first. Even Cisco’s CEO has acknowledged that AI will make some jobs go away, though he also sees the potential for more efficient organizations.
What makes Tenev’s “job singularity” thesis compelling is its grounding in historical precedent. Just as the agricultural revolution didn’t lead to permanent mass unemployment but rather to entirely new categories of work, and the internet created job titles that would have been incomprehensible a generation ago, AI may catalyze a similar transformation. The concept of “single person unicorns” suggests a future where individuals, armed with AI tools, can create billion-dollar enterprises without traditional corporate infrastructure. This represents not just an evolution in work, but a fundamental reimagining of the relationship between technology, productivity, and human creativity. Whether this optimistic vision materializes or whether the transition proves more painful than Tenev anticipates remains to be seen, but his framework offers a valuable lens for thinking about AI’s impact on employment beyond simple displacement narratives.