As AI automates cognitive tasks and accelerates the expansion of digital infrastructure, debate is growing around a possible revaluation of manual work — driven by both economic and behavioral forces.
It is a fact that in recent years we have witnessed major paradigm shifts in work formats: from 9-to-5 employment to entrepreneurship, from traditional offices to digital nomadism, and a growing number of executives leaving corporate careers to become solopreneurs. I am personally an example of this transition.
But recently, a post on Threads caught my attention because it suggested something different — not just a change in work format, but a change in the very nature of work itself.
A designer, Dan Queirolo, shared that he is leaving a 20-year career in design to become a residential painter. According to him, the decision is preparation for a world in which artificial intelligence is rapidly advancing into cognitive activities — potentially replacing his work as a designer. He was not alone. In the comments, several similar stories emerged: a physician who now bakes sourdough bread, a lawyer who became a dog trainer, and many other examples.
This immediately reminded me of a statement by Geoffrey Hinton, often referred to as the “godfather of AI”: “Want a job in 2030? Then train to be a plumber.” More recently, at Davos, Jensen Huang, CEO of NVIDIA, stated that the expansion of AI infrastructure will create strong demand for electricians and construction workers as new data centers are built.
Are we witnessing a new structural trend? A migration from cognitive work — dominant over the past decades — back to manual work?
There are at least two reasons that help explain this movement.
The first is technological. AI already outperforms humans in various standardized cognitive tasks: text generation, data analysis, basic programming, customer service. At the same time, it still struggles to replicate complex manual skills, especially those that are non-repetitive and performed in unpredictable contexts. The physical world is far less structured than the digital one, partly due to asymmetries in data availability — and that matters.
Moreover, the expansion of AI itself requires intensive physical infrastructure. Data centers, electrical grids, cooling systems, and specialized construction all create demand for technical professionals. In this sense, the growth of the digital economy paradoxically depends on a robust manual foundation.
But there is a second reason, less obvious and more cultural.
We live in an environment of hyper-productivity, information overload, and constant pressure for cognitive performance. Digital work is often fragmented, mediated by screens and metrics. Manual work, by contrast, offers immediate tangibility: something concrete is built, repaired, or transformed.
In Dan’s account, there is an element that goes beyond career strategy. He says he has gone five days without touching a mouse or computer — and has never felt more fulfilled. Whether or not this is economically optimal, there is an evident psychological component: control, focus, and quality replacing speed and volume.
This leads to a deeper question: are we observing merely a temporary reaction to AI’s advance, or the beginning of a structural revaluation of manual skills?
Historically, the labor market evolved from agriculture to craftsmanship, from craftsmanship to industrial mass production, from industry to office-based work. Now, as cognitive automation accelerates, there may be a recomposition of value across different types of skills.
This does not mean that everyone will abandon “IQ-based” jobs to become plumbers or painters. But it may signal a shift in the hierarchy of scarcity. If standardized cognitive tasks become abundant through AI, complex and adaptive physical skills may gain relative importance.
The central issue, therefore, is not to romanticize manual labor nor to declare the end of intellectual work. It is to understand how technology redefines what is rare, difficult to automate, and economically valuable.
Perhaps the right question is not whether “the new wealth lies in our hands or in our brains,” but rather: which combinations of skills will remain scarce in a world where the digital becomes increasingly abundant?
And you — on a scale from 0 to 10 — how prepared are you for a scenario in which the nature of work shifts once again?
This is not about knowing how to change a light bulb or build a house alone. It is about clearly understanding which skills will be most in demand — and all signals suggest that our hands, not only our brains, may play a larger role than we assumed.
