The triumph of AI has left many white-collar workers uncertain about whether their jobs will still exist in the future. This disruption is not confined to routine tasks; AI is increasingly encroaching on areas that require judgment, creativity and a nuanced understanding. What will be left for us to do if AI systems take over more and more of our tasks? The most radical scenarios envisage a world in which there is nothing left for us mere humans to do – the end of work.

This closely resembles Karl Marx’s vision, who famously wrote that it would be possible to

do this today, that tomorrow; to hunt in the morning, fish in the afternoon, tend cattle in the evening, and criticise after dinner, as I please, without ever becoming a hunter, fisherman, shepherd, or critic.

However, the young Marx wrote this in 1845, 180 years ago, and it still hasn’t happened. This doesn’t mean it couldn’t happen in the future, of course. Could we fully automate the world and finally rid ourselves of our to-do lists?

In many discussions, auxiliary terms such as ‘creativity’, ‘idea’ or ‘empathy’ are currently being used to describe what is supposedly human and cannot be taken over by machines. The future of work is definitely in the category of things that machines cannot do. However, the progress made in recent years casts serious doubt on the notion that AI cannot be creative, imaginative or empathetic – or at least emulate these qualities sufficiently well.

The question of control

But there is one issue, and it goes straight to the heart of the matter: the question of control. Sooner or later, machines will take over. Samuel Butler expressed this concern in a famous essay back in 1863. The rapid progress of AI has made it seem relevant again. Here’s the thing, though: it’s up to us to decide. In another essay, Stephen Wolfram, who spoke back at NEXT13, put it this way:

But so what’s left that humans can do, and AIs can’t? There’s—almost by definition—one fundamental thing: define what we would consider goals for what to do. We’ll talk more about this later. But for now we can note that any computational system, once “set in motion”, will just follow its rules and do what it does. But what “direction should it be pointed in”? That’s something that has to come from “outside the system”.

In short, Stephen Wolfram’s point is that as long as we care about something – not being extinct, for example – we have work to do, and there’s no end in sight for that. Even in a fully automated world, things wouldn’t stay the same, and human intervention would still be necessary to adjust. Human agency would shift from performing routine tasks to setting priorities, making ethical choices and navigating the unpredictable frontiers of innovation.

Wolfram explains this with a term he coined a while ago: computational irreducibility. Put simply, this means that certain computer processes cannot be simplified, so the only way to obtain the result is to work through the entire process step by step. Even small programmes can generate great complexity. This is what the natural world does. This is why each and every species needs to do something in order to survive.

The undeniable progress of recent centuries may have somewhat obscured this insight. But ultimately, life and survival always require work. While it may become more sophisticated, it’s unlikely to disappear entirely. AI has sparked widespread fear that it could lead to the extinction of human beings. There will always be work to be done just to prevent this from happening, at least.

Still a lot of work, and no end in sight

Even if we were to fully automate the world and let it run its course, we would still need to exercise control (or what we have left of it). That’s a lot of work, especially given the complexity of a fully automated world. In the words of Stephen Wolfram:

Given a particular set of things one cares about at a particular point, one might successfully be able to automate all of them. But computational irreducibility implies there will always be a “frontier”, where choices have to be made. And there’s no “right answer”; no “theoretically derivable” conclusion. Instead, if we humans are involved, this is where we get to define what’s going to happen.

How will we do that? Well, ultimately it’ll be based on our history—biological, cultural, etc. We’ll get to use all that irreducible computation that went into getting us to where we are to define what to do next. In a sense it’ll be something that goes “through us”, and that uses what we are. It’s the place where—even when there’s automation all around—there’s still always something us humans can “meaningfully” do.

It’s not control in the traditional sense. In a fully automated world, AI would behave like nature, operating according to its own rules and occasionally interacting with us. The struggle for meaning and survival will persist. However, it will evolve, shaped by our ability to set goals, make choices, and adapt to an ever-changing landscape.

From an economic perspective, it is a matter of value and values. As AI commodifies intelligence, value creation must move elsewhere. In classical and Marxist economics, value creation is fundamentally tied to human labour. Neoclassical economists moved away from the labour theory of value towards a focus on utility, supply, and demand.

However, AI is not merely automating labour; it is also redefining the relationship between labour, capital, and value. This accelerates a shift in which human effort is no longer the bottleneck for value creation; instead, human oversight, purpose, and distribution mechanisms become more critical. Brian Solis, another former speaker at NEXT, puts it this way:

AI doesn’t just eliminate roles. It rewrites the definition of value.

Ultimately, in an AI-driven world, the future of work is not about maintaining traditional forms of control. Instead, it is about redefining our relationship with technology. Just as we adapt to the rhythms and constraints of the natural world, we will need to find new ways to coexist with intelligent machines. In this sense, the end of work as we know it may not signify the end of human purpose, but rather the start of a new era in which we must find new sources of meaning, fulfilment and connection.

Image by Markus Spiske / Unsplash.