15 Garage Supplies Worth Always Having On Hand (And Why)






A garage often isn’t just for parking your car; many people actually use it as a space for storing miscellaneous supplies that can’t be kept in the pantry, living area, or other rooms in their home. Although these items are often not suitable for storage inside your house, that does not mean that they aren’t useful to have ready and available at all times.

These won’t be cool gadgets like the ones you can get from Home Depot, so you’d probably never think about these things in your daily life and day-to-day tasks. In fact, you might not even need to use some of them during your entire life, but it’s still a good idea to have them around in case of an emergency. As the popular Franz Kafka quote says, these items are “better to have, and not need, than to need, and not have.” So, we’re picking out items that are worth always having on hand or in stock in your garage.

Fire extinguisher

Most people will probably never have to use a fire extinguisher to fight a fire in their home, but it’s still a good thing to have in your garage in case of an emergency. These small canisters are crucial for dousing small flames before they burn out of control and could mean the difference between a minor inconvenience and a complete disaster.

You need to ensure that you have the right type of fire extinguisher, though, as they come with different symbols that denote what kind of ignition and fuel source they’re designed to work on. Class A extinguishers are designed for ordinary combustible materials such as wood, paper, cloth, rubber, and most plastics, while Class B will douse flammable and combustible liquids, like gasoline, grease, tar, oil-based paint, solvents, lacquer, alcohol, and flammable gases. For electrical fires, a Class C extinguisher is needed to reduce the chance of electrocution.

Most home fire extinguishers are labeled BC or ABC, meaning they can be used on different types of fires to help protect your house. It makes sense to keep one in your garage so that it doesn’t get in the way of your activities around the house — just ensure that it’s stored somewhere within easy reach of everyone in your home.

Matches or a lighter

Most American homes no longer need a match or a lighter for daily use, and you probably don’t think of keeping one ready unless you’re into charcoal grilling. However, it’s still a good idea to have a fire starter available at home for various purposes.

The most common use for a match or lighter is lighting candles — whether for a birthday cake, a romantic dinner, or aromatherapy for relaxation at the end of the day. But aside from these applications, a box of matches or a lighter is useful in case of emergencies, where it can be used for lighting emergency candles or gas lanterns. It’s also great for lighting a gas stovetop or oven in case its built-in electric igniter fails or stops working.

You should also keep matches or a lighter in stock in your garage, especially during winter. That way, in case both power and gas supplies fail, you can still keep warm by starting a fire in your fireplace.

Extension cords

Even though you may feel that you have enough outlets in your home to power all your devices, it’s still a good idea to have an extension cord or two handy in your garage. They’re particularly useful when you’re working on a project and need to set up an additional tool or appliance away from an available outlet, or if you buy a new gadget and don’t have room to plug it in at your nearest outlet.

You shouldn’t use an extension cord as a permanent power solution, though, which is one of the electrical mistakes you don’t want to make in your home. You also have to be mindful not to overload it, especially when you’re plugging in powerful tools like table saws or angle grinders, as they could exceed its capacity.

It’s also a good idea to keep an extension cord available in your garage so you can easily grab one when you’re traveling. It also comes in handy for remote work setups or when you’re using a mini projector for backyard camping at home.

Batteries

Old batteries are some of the things in your garage you probably need to toss out — instead, you should keep a fresh set of batteries in your garage at all times. This is more for convenience, as many remote controls, key fobs, and other smaller gadgets are still powered by AAA, AA, and button batteries. So, if the battery in your car key fob is eventually exhausted, you don’t have to run to a convenience store in the dead of night. Just ensure that you store them properly so you don’t end up with problems like leaking batteries or a short circuit.

Aside from these consumer batteries, it’s also a good idea to have spare rechargeable tool batteries. While the included battery with your cordless tool should be good enough for casual use, having a spare available in your garage means that you don’t have to pause your DIY project if you do run out of power, especially if you forget to recharge it after every use. It will also save you if your main battery finally fails after years of use. That way, you can finish what you’re working on before heading out to your neighborhood hardware store to buy a replacement.

Flashlights

Even though almost every smartphone produced today has a flashlight function, it’s still wise to keep a couple of dedicated flashlights in stock in your garage. These are useful during power outages or if you’re searching for something outdoors at night (for example, if a pet escapes). You can also use them if you need to find something in the dark nooks and crannies of your house, especially as using a phone as a flashlight isn’t as convenient as using an actual flashlight.

One good idea is to have two sets of flashlights — one AA/AAA-powered unit for each family member in your home and several smaller USB-powered flashlights you can place around the house, like this magnetic USB-C Harbor Freight light. That way, each person in your house has their own easy-to-hold personal light source for use both inside and outside the home, while also ensuring that your house has interior USB-C lights to help prevent bumps and bruises.

We recommend AA/AAA-powered handheld flashlights so that in case the power outage is longer than expected, you can easily replace its power source with the batteries you have in stock in your garage. As for the USB-C-powered lights, you can easily top them up with a power bank if they run low — just ensure that you keep your phones charged, too.

Various kinds of tape

Even if you’re not into crafts or DIY projects, it’s still a good idea to keep a roll or two of various kinds of adhesive tape for quick repairs. Some of the types of tape that are useful to keep in your garage include transparent tape (more popularly known as Scotch tape) for light-duty household and office work like repairing paper tears, wrapping gifts, and sealing envelopes; double-sided tape for mounting lightweight items on walls and other surfaces; masking tape for temporary holds, labeling, and paint masking; and packaging tape for more heavy-duty applications.

It’s also useful for homeowners to keep a roll of electrical tape, plumber’s tape, and duct tape handy in their garage. These budget-friendly garage staples are useful for temporary repairs, like when you replace a faucet or seal a leaky window or door. But if you’re unsure about what you’re doing, especially when it comes to electrical work, it’s still best to leave repairs to licensed professionals.

Rope

It’s useful to keep some length of rope available in your garage as it’s particularly useful for securing items in your home and on your car. For example, if you’ve recently unboxed and built some Ikea shelves and other IKEA finds for your garage, you’d probably want to bundle the empty boxes together for easier disposal. While you can use packaging tape to do that, it’s far easier to do so with rope.

Ropes are also great for securing several items — for example, you can use rope to add additional strength to boxes, ensuring that they don’t collapse or give way even if you put heavy items inside. It can also be used on a swing gate to ensure that it doesn’t slam shut against your car door as you back out of your garage when the wind blows.

If you have a pickup truck or plan to carry items on your roof rack, you also need to have some rope to secure your cargo and ensure that it doesn’t go flying off your vehicle while on the road. Aside from ensuring your safety and that of other road users, the U.S. Government Accountability Office (GAO) also says that all 50 states have penalties for vehicles caught carrying an unsecured load.

Super glue

While adhesive tapes are useful for repairing flat or thin objects, you’d need something far stronger if you want to stick two objects together. This is where super glue comes in, and it’s a good idea to keep a bottle in your garage in case you need to make a repair.

Super glue is useful for general household repairs and is particularly effective on materials such as ceramics, glassware, some types of plastics, and metals. This versatility means you can use it for a lot of everyday repairs, although you can also get different types of super glue depending on your intended application. While general-purpose super glue is good enough for most uses, you can also find specially formulated super glue for applications that can withstand higher stress and vibration, as well as formulas designed to work with porous surfaces and certain types of plastics.

While you often have to wait at least 10 minutes for the glue to reach its full bond strength and 24 hours for it to be fully cured, it sticks to different surfaces nearly instantly. This means you can complete a repair in five minutes or less, and you also won’t need special tools and equipment like clamps to ensure that the pieces remain together while the glue sets.

Zip and cable ties

Even though ropes and zip ties or cable ties have technically similar purposes — bundling loose things together — the latter are far more convenient to use, especially in confined spaces. As the name suggests, cable ties are primarily used for securing cables together, and you can use them to manage the cables on your PC gaming setup or office workstation. They’re also much easier to use than rope because you can just twist them together to secure the cable tie instead of tying a tiny knot.

If you want a more permanent solution, consider using a zip tie instead. Unlike cable ties that you still have to twist to secure, you can easily secure your cables and other items with a zip tie in one smooth motion. The only downside is that you usually have to cut it if you want to release the item you’ve tied together, making it difficult to reposition your cables once you’ve set them in place.

Aside from keeping stuff together, zip ties also have several other genius uses. This includes tying them around your bike’s wheels for additional traction, using them as a replacement slider for a zipper, as a decoration hanger, and for anchoring outdoor items to prevent them from flying off in a strong gust of wind. Because of these various uses, it’s best to keep zip and cable ties in your garage so you can easily get to them whether you’re working indoors or outdoors.

Garbage bags and spare boxes

Many people often keep garbage bags in stock for putting waste in, making disposal much easier. But despite their name, these plastic bags are also useful for several other purposes. For example, if you don’t have a washing machine at home, you can use these bags to put your dirty clothes in to make them easier to bring to the laundromat. They’re also great for storing non-fragile items that you can just drop in a plastic bag, like Christmas decorations or kids’ toys.

This is also why it makes sense to buy heavy-duty garbage bags instead of just using ordinary plastic bags. Aside from ensuring that they won’t get ripped when you’re moving trash, they can also help ensure that any sharp or pointy items that you intend to put in the bag for moving or storage won’t puncture and damage it.

If you have more space, it’s also worth keeping a couple of small- or medium-sized collapsed boxes, which are a more suitable storage solution for delicate or breakable items. Although they might not be enough if you plan to move houses (and you’ll probably buy more boxes for that event), keeping some extra garbage bags and boxes stored in your garage will help you keep your things organized if you have to make changes around your home.

WD-40

WD-40 is one of the household chemicals that many people swear by, and it’s a good idea to keep a can in your garage if you don’t have one yet. While it’s no miracle product and you should not use it for some items, it’s still quite a nifty product for protecting metals and other materials from water (hence the name WD, which stands for Water Displacement).

Now, there are a million and one moving parts in nearly every home, and one of these things will eventually start squeaking. You can quickly solve issues like this with a quick spray of WD-40 to get that annoying sound out of the way. It’s also great for protecting metal objects, especially those that are exposed to the elements.

For example, a padlock that’s been sitting in the sun and rain for years would eventually get stuck and become hard to open — but a single squirt of WD-40 would loosen its stuck components, and you just need to maintain it once a year to ensure that the lock operates smoothly through the years. You can even use WD-40 on several parts of your car to help keep it in excellent shape.

Basic tools

If you’re a first-time homeowner or renter, you probably still don’t have a set of tools in your garage. If that’s the case, it’s a good idea to get started on a basic tool kit with the most essential tools to make repairs and maintenance around your home much easier. 

These include screwdrivers (both flathead and Phillips) for assembling things, a tape measure for planning, a box cutter for opening packages, a pair of pliers for working with wires, and a hammer for building stuff. It’s also a good idea to get a cordless drill, as it can make DIY projects much faster and easier, and a set of wrenches for working with nuts and bolts.

You don’t have to buy the most expensive, professional-grade tools if you don’t have much of a budget — after all, you’d probably only use these items occasionally. But if buying new is still not an option, you can purchase some of these used; just ensure that you know what to look for before paying so you know what you’re getting.

Screws and nails

It’s good to keep screws and nails alongside your basic tools, as they’re quite useful for securing wooden items and repairing furniture around your home. For example, if one of the hinges on your cabinet doors comes loose, you can simply go to your garage and pick out an appropriate screw to fix it. You can also do the same with a wobbly chair — instead of waiting for an accident, you can simply pick out a screw of the appropriate length and drive it in to secure the loose joint.

Aside from repairs, you can also use screws and nails to create permanent hanging points on drywall for picture frames and other light objects. You can also use them on concrete walls, but you need to either use a concrete nail or a wall plug or plastic anchor for securing a screw.

Most importantly, these items are cheap. You can get a box of hundreds of nails or screws of different sizes for less than $10 on Amazon, meaning you don’t have to spend much just to keep these in stock in your garage.

Engine oil and other automotive fluids

If you drive a car, especially one that’s an older model, then it’s a good idea to have an unopened can of engine oil readily available in case of emergencies. That way, if your engine springs an oil leak, you can easily top it off before heading to your favorite mechanic to fix the issue.

You shouldn’t just let these containers sit for years on your garage shelf, though. Always check the label to see the expiration or production date of the oil, which usually has a shelf life of five years. They should also be stored in optimal conditions — kept between 40 and 85 degrees F in a cool, dark place. It’s also not a good idea to keep an open container of motor oil in your garage, as it can go bad due to oxidation.

Aside from engine oil, consider stocking other fluids like brake fluid, coolant, and windshield washer fluid, too. However, the exact fluids you should keep depend on the age of your car and the issues you encounter while owning it.





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There’s a popular argument that AI will do to human workers what tractors did to horses. Tractors could do what horses did. Horses became obsolete. AI can do what humans do. Therefore…

Plenty of major AI figures seem to agree. Elon Musk says AI will “replace all jobs.” Anthropic CEO Dario Amodei regularly warns about mass job loss, framing AI as “a general labor substitute.” OpenAI investors talk openly about AI replacing “80% of all jobs by 2030.” These are influential people, not random bloggers. Still, they are not necessarily a representative sample of the world’s most careful economists.

And the fear itself is hardly new. Economist Wassily Leontief—best known for developing input-output analysis, a way of mapping how industries depend on one another—raised similar concerns in the early 1980s. If AI really were a perfect substitute for human labor, the logic would be straightforward. Any cost advantage would eventually drive firms toward 100% AI labor. You do not need a long essay to prove that result.

The problem is that the phrase “AI will eventually be a perfect substitute” does almost all the analytical work. That assumption hides a great deal: differences across tasks, industries, and workers; the many margins along which firms adjust; and the messy heterogeneity that makes the real economy more than a toy model.

How substitutable is AI today? What would need to happen for that substitutability to rise meaningfully? What other conditions would also need to hold? Even the historical analogy—“tractors could do what horses did, therefore horses became obsolete”—compresses several distinct steps into one neat sentence. “AI can do what humans do, therefore humans become obsolete” hides even more.

So let’s unpack those steps.

(This post draws on a new working paper that walks through the math and economics in detail. Really, though, it is mostly basic accounting.)

Before We All Become Horses

For those unfamiliar with the history of horses in the United States, the horse population actually rose for decades alongside industrialization. It increased from 4.3 million in 1840 to 27.3 million in 1920. The collapse came later, as tractors and motor vehicles displaced horses in agriculture and transportation. The number of farm horses and mules then fell to roughly 3 million by 1960.

Horses, in effect, had one main economic role, and that role disappeared. Humans are different. So before jumping from “AI can do tasks” to “humans become obsolete,” we should define carefully what that outcome would actually mean.

To keep things simple, suppose demand for human labor falls to zero. Not “low.” Zero. What would that require?

It would mean that no dollar spent anywhere in the economy passes through human labor at any point in the supply chain. Not the person who made the product. Not the person who shipped it. Not the person who designed it, marketed it, maintained it, or cleaned the building where it was assembled. Zero human labor embodied in final expenditure. That is the benchmark. That is what “humans become horses” would mean, stated precisely.

This is the input-output framework the aforementioned Wassily Leontief built his career on. The idea is straightforward: trace any final purchase backward through its supply chain and add up all the labor that contributed to it, both directly and indirectly. A cup of coffee includes the labor of the barista, but also the roaster, the truck driver, the coffee farmer, and the workers who built the truck. “Embodied labor” means all of it.

For labor demand truly to collapse, every one of those links would need to disappear across every good and service consumers buy. That is a much stronger claim than “AI can do some jobs.” The economy is not a single production function. It is a sprawling network of activities. When AI makes one activity cheaper, consumers do not simply buy more of the same thing forever. They redirect spending elsewhere.

Every dollar lands somewhere. Some spending flows into highly labor-intensive activities, such as restaurants, therapy, or home repair. Other spending flows into activities that require very little labor, such as cloud storage, automated checkout systems, or streaming subscriptions. So the relevant question is not merely: “Can AI do my job?” It is: “When AI makes some things cheaper, where does the saved money go next?”

Aggregate labor demand depends on at least three things: total spending in the economy, the share of spending that goes toward labor-intensive activities, and the amount of labor embodied in each activity. For labor demand to fall to zero, AI cannot merely displace workers in a few sectors. Every dollar of spending, wherever it ultimately lands, must shed all embodied human labor. The “humans become horses” story therefore requires three separate margins to collapse simultaneously.

A useful starting point is the simple observation that firms do not want labor per se. A restaurant does not want waiters because it enjoys employing waiters. It wants orders taken, customers reassured, mistakes fixed, and meals delivered. Labor demand is therefore “derived demand”—firms demand workers because workers help produce something else consumers value.

When AI can perform those underlying tasks more cheaply, two things happen at once. First, firms substitute AI for workers, reducing labor demand per unit of output. Second, lower production costs reduce prices, output expands, and that expansion tends to pull labor demand back upward. Whether total labor demand rises or falls depends on which force dominates.

Economists call this the Hicks-Marshall decomposition of derived demand into substitution effects and scale effects. The terminology sounds forbidding, but the intuition is simple: cheaper production reduces the need for workers in one sense, while expanding the market for output in another. That tension will organize the rest of the discussion.

When a dollar gets saved, where does it go? Into new tasks? New jobs? New industries? The money has to end up somewhere.

Your Job Is Not a Checklist

The case that AI can automate many tasks is not speculative anymore. This is obviously true to some extent, and it has been true for years.

Even early large language models (LLMs) showed substantial potential to affect workplace tasks. One widely cited paper by Tyna Eloundou, Sam Manning, Pamela Mishkin, and Daniel Rock estimated that roughly 80% of the U.S. workforce could see at least 10% of their job tasks affected by LLMs. When paired with complementary software tools, 86% of occupations crossed that 10% exposure threshold.

Since then, the empirical literature has grown rapidly, and the task-level evidence is hard to dismiss. In a large customer-support study, access to generative AI increased the number of issues resolved per hour by roughly 15%. In an experiment involving professional writing tasks, ChatGPT reduced average completion time by 40% while increasing measured output quality by 18%. In a controlled GitHub Copilot study, software developers completed coding tasks 55.8% faster. Those are not rounding errors.

But they are effects on tasks, not necessarily on jobs. That distinction matters. When a task gets automated, the saved dollar does not disappear into the void. Firms and workers often redirect it toward new activities within the same occupation: more client management, more review and verification, more coordination, more judgment calls, more customization.

Just as there is no fixed amount of demand in the economy, there is no fixed bundle of tasks that permanently defines a job. Jobs evolve. They absorb new responsibilities, shed old ones, and reorganize around whatever remains scarce and valuable.

The O-Ring Problem

There is a familiar ritual in AI discourse. Someone posts a demo. The demo performs a task associated with a particular job. People immediately conclude that the job is doomed.

Sometimes they are right. But that inference skips about 15 intermediate steps.

What does it actually cost to deploy the system once error rates are included? Do customers trust it? Can firms reorganize workflows around it? Does management even know how to integrate it effectively? A chatbot demo can appear overnight. A hospital cannot reorganize clinical liability around AI overnight.

That distinction matters because firms are not simply collections of isolated tasks. They are organizations. In many cases, the result will not be pure replacement, but rather a human-AI team producing output together. Economists call this complementarity: two inputs become more valuable when used jointly than separately.

But complementarity is not free. A human-AI pair that produces only marginally more value than the AI alone will not justify paying a full human wage. The human worker must contribute something the AI cannot reproduce cheaply or reliably.

That matters especially in high-stakes settings where errors are extraordinarily costly. Surgery, aviation, structural engineering, fiduciary advice, and many legal services all fall into this category. In these fields, the cost of failure can easily dwarf the savings from cheaper production.

That could eventually change. It probably will change in some areas over time. But it is not likely to change quickly.

This is essentially the “O-ring” logic from economics, named after the tiny rubber seal whose failure destroyed the Space Shuttle Challenger. When the value of the entire system collapses because one component fails, buyers do not focus primarily on sticker price. They focus on the expected cost of a system that actually works.

In those environments, human-supervised production can remain economically efficient even if AI itself becomes extremely cheap.

Horses Had Nowhere Else to Go

Suppose substitution effects really do dominate within most jobs. The saved dollar then escapes the workplace entirely. Where does it go next?

Most standard economic models collapse the economy into a single “final good,” which makes that question disappear by assumption. Real economies do not work that way. They contain many sectors, and every dollar eventually lands somewhere.

Start with software, which serves as a useful microcosm. Software-intensive industries have already undergone decades of automation through digital tools. If automation were going to drive human labor out of a sector entirely, this is where you would expect to see it first. The chart below groups industries according to how much software they purchase relative to value added: low, medium, and high software intensity. The result is striking.

The most software-intensive industries do not merely retain human labor. They actually devote a larger share of income to labor compensation—about 67%—than the least software-intensive industries, which devote roughly 55%. In other words, the industries that automated the most heavily also remained highly labor-intensive.

The same pattern appears in employment projections. The Bureau of Labor Statistics (BLS) projects total U.S. employment to increase by 5.2 million jobs between 2024 and 2034. Employment for software developers—a profession directly exposed to AI tools—is projected to grow 17.9%. BLS could ultimately prove wrong. Forecasting always carries uncertainty. Still, the evidence so far points strongly toward scale effects dominating in software-intensive industries. Automation reduced costs, output expanded, and labor demand remained robust.

Software may be an extreme case, but versions of this pattern appear across the broader economy and over much longer periods. Take the shift from goods to services. In 1929, most consumer spending went toward physical goods. Today, roughly two-thirds of consumer spending flows toward services. As manufacturing became dramatically more efficient, consumers did not respond by purchasing infinite refrigerators and toasters. Instead, spending shifted toward health care, education, restaurants, entertainment, travel, and personal services.

That is the “saved dollar” in action at the economy-wide level. Goods became cheaper. The substitution effect largely won within goods-producing industries. Employment growth in manufacturing did not continue indefinitely. But the freed-up purchasing power migrated elsewhere, and the scale effect emerged across sectors instead.

From a macroeconomic perspective, output expanded overall. Consumers simply redirected spending toward new categories of consumption. But migration alone does not help workers unless the destination sectors still contain substantial human labor. Did they?

Again, the answer appears to be yes.

Services consistently devote a larger share of value added to employee compensation than goods-producing industries do. Spending did not merely migrate. It migrated toward sectors where more of each dollar ends up in someone’s paycheck.

So yes, one could argue that this still resembles the horse story in one respect. The relative importance of goods production declined as productivity increased. The point, though, is that large, diverse economies contain adjustment margins that horses never had. There are escape valves.

Comparative advantage keeps reappearing. When automation makes some activities extremely cheap, spending tends to shift toward the activities that remain relatively expensive. And the activities that remain expensive are often the ones that are hardest to automate. Those are precisely the areas where humans continue to hold a comparative advantage—that is, where human labor remains relatively more productive or valuable than machine substitutes. The saved dollar therefore tends to drift toward areas where humans are still worth paying.

That is not technological optimism. It is simply the logic of comparative advantage.

James Bessen documents this dynamic sector by sector. In early textile manufacturing, power looms sharply reduced labor required per yard of cloth. But cloth became so much cheaper that demand exploded, and total textile employment increased for decades. Similar patterns appeared in steel and automobile production. Eventually, demand saturated. Prices stopped falling rapidly enough to offset labor-saving automation, and employment in those sectors declined.

The key question for AI, then, is not whether automation can destroy jobs. Of course it can. The real question is: Which sectors are in which phase? Where might AI-generated savings flow today?

Health care already accounts for roughly 18% of U.S. GDP, and that share continues to rise. Elder care will likely expand further as populations age. Personalized services, human-intensive care work, and new categories of consumption may absorb growing shares of spending.

Joel Mokyr, Chris Vickers, and Nicolas Ziebarth make this historical argument well in a Journal of Economic Perspectives article. Across prior waves of technological change, new tasks emerged, comparative advantage persisted, and entirely new categories of work appeared that earlier generations could not have anticipated.

Horses had no equivalent adjustment path. They did not move into elder care.

Will Humans Become a Luxury Good?

The saved dollar migrated toward human-intensive sectors last time. The strongest argument for why this time could be different comes from economist Philip Trammell’s paper, “Is Labor a Luxury in the Long Run?

His answer is: probably not. Even if richer consumers initially spend more on human-intensive goods and services—live music, handmade products, personal care, bespoke experiences—four long-run forces may steadily erode that demand.

  1. AI-generated variety keeps expanding. New AI-produced goods compete for every dollar that might otherwise land on a human-made product or service.
  2. Human experiences carry opportunity costs. Time spent at a live concert is time not spent consuming some potentially superior AI-generated alternative.
  3. Labor competes with other scarce goods for consumers’ willingness-to-pay premiums. Beachfront property, status goods, intellectual property, and research-intensive products may all absorb spending that might otherwise flow toward human labor.
  4. Capital goods become cheaper over time. If investment opportunities continue expanding, the share of economic activity devoted to capital accumulation could grow indefinitely.

Trammell’s Coca-Cola analogy captures the intuition cleanly. Original Coke once held roughly 50% of the soda market. Then came Diet Coke, Cherry Coke, Pepsi Max, energy drinks, flavored sparkling water, and endless other varieties. Even with enormous brand loyalty and supply constraints, Coke’s market share fell below 20%.

The implication for AI is straightforward. Even if consumers initially prefer human-made goods, that preference may weaken as AI continuously generates new substitutes and varieties. Human labor does not need to become worthless. Its share can erode through dilution.

That is a serious argument, and I take it seriously. Still, notice what the argument requires. It is not enough for AI-generated variety merely to expand. That will almost certainly happen. The stronger claim is that AI-generated substitutes must expand broadly and rapidly enough to pull spending away from every human-intensive category simultaneously.

The real question is not whether AI competes with some human-produced goods. Of course it will. The question is whether any human-intensive islands survive. Does anyone still spend money on something with a person inside it?

The arithmetic quickly becomes more demanding than many “humans become horses” narratives imply. Suppose AI eventually captures 85% of economic activity. Software, accounting, logistics, medicine, law, management, and much of media production become almost fully automated. Human labor largely disappears from those sectors.

Now suppose the remaining 15% of spending flows toward activities that still contain at least 30% human labor: elder care, live entertainment, skilled trades, therapy, surgery, in-person education, luxury craftsmanship, status goods, and other relational or trust-intensive services.

The aggregate labor share would still equal at least:

S ? 0.15 × 0.30 = 0.045

That leaves labor with at least a 4.5% share of economic output. That may not sound comforting, but remember what this calculation is doing. It is merely establishing a lower bound under extremely aggressive automation assumptions. It is not utopia. It is not full employment. But it is also not zero. And a falling labor share does not necessarily imply falling labor demand if total output grows rapidly enough.

Alex Imas offers another reason to doubt the “humans disappear” story. As AI drives down the cost of commodities, real incomes rise. Historically, richer consumers tend to shift spending toward what Imas calls “relational goods”—goods and services whose value depends partly on human connection, scarcity, or social meaning.

That idea connects to a large economics literature on structural change. Over time, economies tend to shift from agriculture to manufacturing to services as incomes rise. The key debate is why. Do consumers simply buy more of whatever becomes cheaper? Or do rising incomes fundamentally change what people want?

Diego Comin, Danial Lashkari, and Marti Mestieri decompose those effects and conclude that income effects account for more than 75% of the long-run shift toward services. That distinction matters enormously here. If structural change were driven mainly by falling prices, then AI-generated abundance might pull spending overwhelmingly toward AI-produced goods. But if structural change is driven mainly by rising incomes and evolving preferences, then richer consumers may continue demanding more human-intensive experiences and services. Historically, that is exactly what has happened.

Experimental evidence points the same way. In one set of experiments, subjects learned that other people would be excluded from purchasing an otherwise identical product. Willingness to pay roughly doubled. The exclusivity itself created value.

Importantly, the exclusivity premium was stronger for human-made goods than AI-generated ones. Human-created artwork gained roughly 44% in value from exclusivity, compared with about 21% for AI-generated artwork. AI-made goods feel infinitely replicable. Human-made goods feel scarce, even when they technically are not. People value what other people cannot easily obtain. That impulse does not disappear as societies grow wealthier. If anything, it intensifies.

Perhaps AI-generated variety eventually overwhelms even those preferences. Maybe. Still, the structural-change evidence consistently suggests that income effects dominate price effects by roughly three to one. When basic goods become cheaper, humans do not announce that they are finally satisfied and stop developing new wants. They invent new forms of distinction, identity, taste, and status competition. The open question is where those new desires land. So far, the evidence points toward humans retaining an important role.

One final clarification matters here, because popular AI discussions often conflate two distinct claims. A falling labor share is not the same thing as falling labor demand. Labor’s share of national income can decline even while total employment and total wages continue rising, provided the overall economy grows fast enough. In that world, AI appears to “take over” a larger share of production while human workers still earn more in absolute terms because the economic pie itself expands dramatically.

That may well describe the phase we are currently entering. We already observe the basic pattern. Higher-income households consume more services, and service sectors remain relatively labor-intensive. Could that eventually reverse? Of course. But at the moment, this is the evidence we actually have.

The Horse Story Ends Here

Walking through all these layers—from tasks, where we are only beginning to see meaningful substitution, up through firms, sectors, and the macroeconomy—leaves me fairly skeptical of the “humans become horses” outcome. I know I have concealed that conclusion masterfully until now.

AI will absolutely perform many tasks. It will reorganize jobs, sometimes painfully. Some sectors may lose most of their human labor. Spending will often chase automation and lower prices. All of that can happen without driving human labor demand to zero. Because at every stage of the process, there is still a saved dollar looking for somewhere to land. And the same question keeps reappearing: Where does it go next?

For the horse outcome to occur, that saved dollar must eventually fail to find any activity with meaningful human labor embodied in it. Not some activities. All activities.

That is a very specific future. It is logically possible. But it requires substitution to dominate simultaneously across tasks, firms, sectors, and final consumption patterns, with no surviving human-intensive islands anywhere in the economy. The evidence we currently have—structural change, revealed preferences, comparative advantage, and experimental results—keeps pointing the other way.

Horses lost because the economy stopped needing horsepower. Humans are not just horsepower.

 

The post Why Humans Are (Probably) Not Headed for the Glue Factory appeared first on Truth on the Market.



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