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What will be scarce?
The economics of structural change and the post-commodity future of work
Alex Imas
Apr 14, 2026
Starbucks is a huge company (market cap of $112 billion) that sells one of the most standardized products in the modern economy. Making a cup of coffee or even one of the fancy specialty drinks is very easy to mechanize and reproduce. If the entire economy is soon to be automated, with labor being replaced with increasingly more sophisticated capital, Starbucks should be a canary in the coal mine—the technology for removing labor from its stores and replacing it with automated capital has been around for years. Over the past few years, Starbucks has done exactly that: in efforts to increase thin margins, management has automated more and more of the coffee-making business and instituted tightly mechanized processes for delivering it to customers. But instead of increasing automation, the opposite has happened. After trying to streamline the store experience with fewer workers and more automation, the company concluded that this had been a mistake. CEO Brian Niccol said that ``handwritten notes on cups’’, ceramic cups, and ``the return of great seats’’ had led more customers to ``sit and stay in our cafes’’, showing that ``small details and hospitality drive satisfaction.’’ More baristas are being hired per store and automation is being rolled back.
Economics is the study of decision-making under constraints, i.e., scarcity. If advanced AI brings material abundance—if machines can produce many if not all forms of human production at very low marginal cost—does economics become irrelevant? No, we will still have scarcity, but the kind of scarcity that matters will change. Ultimately the answer to any question about the future economics of advanced AI begins with identifying what becomes scarce. After answering that question, the rest of the analysis is pretty straightforward. In this essay I’m going to explore what becomes scarce when automation can replicate many if not all human production, and what that may mean for the types of jobs that emerge.
Before industrialization, it was difficult to separate a product from the person who made it. The weaver who made your shirt, the baker who made your bread: you personally knew them, and their skill and reputation were tied to the product that they sold. Economic transactions had a distinct social component that was innately linked to the consumption experience. The industrial production process changed this by breaking craft into standardized, repeatable steps. Performed by workers based on predetermined and regularized steps, capitalism produced something new: the commodity form, in which a product’s value lies in the product itself, detached from whoever made it. A table is a table, a phone is a phone. The screen that you’re reading this essay on was designed in one country, manufactured in another, using components from around the world. But none of this matters for the experience of buying and using the device.
Marx described this process in intentionally loaded language. The commodity form, he argued, was built on exploitation: the ability to pay workers less than the value of what they produce. They were able to do this because the capitalist production process was based on alienation: severing workers from the product of their labor, from the process of making it, and ultimately from each other. What had once been a person’s craft became abstract ``labor power,’’ a factor of production to be bought and sold like raw materials. Marx saw this as capitalism’s deepest pathology. But to economists, and to the world writ large, the commodity form was an engine of extraordinary prosperity. If production was no longer tied to specific people, it could be disaggregated, reorganized, shipped across oceans, and scaled in ways that turned few resources into vast riches. Both things were true at once: the commodity form created enormous wealth and prosperity, but it made the human behind any specific product invisible, and ultimately, replaceable.
This is most people’s mental model of what AI will do to the economy. If a machine can produce anything a human can, write the brief, generate the image, compose the song, determine the diagnosis from a radiology scan, then the human will be replaced across all facets of production and jobs will simply disappear. Labor will be replaced with capital. David Autor and Neil Thompson push back on this in an important recent paper. They argue that AI won’t simply eliminate jobs; it will reshape the economic value of human expertise. Their framework distinguishes between expert and inexpert tasks within any given occupation. When automation removes the simpler tasks (as accounting software did for bookkeeping clerks), the remaining work becomes more specialized, wages rise, and fewer workers qualify. When it removes the harder tasks (as inventory management systems did for warehouse workers), the job becomes more accessible, employment expands, and wages fall. Same technology, opposite labor market outcomes, depending on which part of the job gets automated.
But Autor and Thompson also consider a starker possibility: that AI advances to the point where human expertise loses its economic value altogether. Under this scenario, AI will eliminate labor scarcity and produce what Herbert Simon once called ``intolerable abundance.’’ Automation of production will no longer involve managing a workforce transition, for which we have prior episodes of automation to rely on. We will need tools to maintain social organization, income distribution, and democratic stability without the labor market that has historically held these together.
I want to consider a different scenario, one where automation can replicate human production and the commodities that it produces (a big if!!!), but human labor does not disappear. How could this be the case? A lot of analysis takes the economy as given: there is a set of jobs and a set of goods/services produced by the economy. If the same set of goods/services can be produced by cheaper machines, then these machines replace humans and the jobs disappear. But the economics of structural change, combined with deep-seated features of human preferences, suggests something different: as people get richer, they don’t just want more commodities. They want things that aren’t commodities in the standard sense of the word. The social aspects of products such as the relationships, the status, and exclusivity—what Rene Girard called the mimetic properties of desire—become much more relevant once people’s basic needs are satisfied. And the demand for these properties will bring the human element back into the production process, and with it, the jobs.
If this is right, then AI won’t just automate the commodity economy. It will trigger the emergence of something new: a post-commodity economy, where a growing share of expenditure goes toward goods and services whose value is inseparable from the human who provided them. The same economic forces that moved 40% of the American workforce off farms and into factories and offices will move workers out of automatable commodity production and into what I’ll call the relational sector. By this I mean the human-intensive, provenance-rich, sometimes artisanal part of the economy where the human aspect is part of the value of the good or service itself. The economics of scarcity won’t disappear, it’ll just relocate.1
This is not the first time this argument has been made (see here by me, here by Seb Krier, here by Adam Ozimek and here by Philip Trammell). The goal of this post is to make this argument precise. I’ll start with what we know about how economies have historically responded to massive productivity shocks, the economics of structural change. Then I’ll introduce the new ingredient: a behavioral microfoundation, rooted in mimetic preferences that generate a desire for exclusivity and status, that explains why artisanal goods (where the human element is directly tied to value) have especially high income elasticity. I’ll work through a simple model that generates a clean prediction: automated sectors shrink as a share of GDP; relational sectors grow. And I’ll connect this back to the question I raised in a previous post about whether AI could lead to negative economic growth. This framework pushes further against that thesis.
