Is AI the New Polyester?

Lately, if you spend time online, you'll come across a comparison that keeps showing up: people are saying AI is the new polyester. A synthetic thing that quietly took over, the way plastic and cheap fabric once did. I get why it's caught on so much, polyester is something almost everyone has worn without thinking twice, so it makes AI feel familiar instead of abstract, something we've already lived through once. It made me want to look closer at the comparison, because I think it's onto something real, just aimed at the wrong target.

A fabric nobody wanted, until everybody had it

Polyester wasn't even invented by the company most people associate with it. Two British chemists, Whinfield and Dickson, developed it in the early 1940s. DuPont just bought the US manufacturing rights a few years later and branded it Dacron. When it reached American consumers in 1951, it was marketed as a genuine miracle: a suit you could wear for 68 days straight, no ironing, and it would still look presentable. Housewives were sold on convenience. The fashion industry was sold on durability and low cost.

For about two decades after that, people mostly hated wearing it. It didn't breathe, it held onto heat and odour, and by the late 1970s "polyester" had become shorthand for cheap and try hard, the leisure suit joke rather than the fabric of the future. Double-knit polyester suits became the uniform of an entire decade's discomfort: the disco floor sweat stain, the static cling, the shirt that looked fine in the store and clung to your back an hour into wearing it. It became something people joked about rather than reached for, and manufacturers knew it. So the industry found somewhere else for it to live, somewhere the flaws didn't matter as much.

That somewhere was outdoor and sportswear. Through the 1970s and 80s the industry adopted it seriously, because for that specific use, lightweight, weather resistant, quick drying, it actually beat cotton or wool. DuPont's own moisture wicking fiber, launched in 1986, and Patagonia's fleece the year before, are usually credited with turning polyester from a cheap substitute into a high performance material in people's minds. Nike built on that with Dri-FIT in the 90s, and by the 2000s the flip had fully happened. Polyester wasn't the alternative anymore, it was the default in most clothing, and "100% cotton" had quietly become the label you pay a premium for.

A synthetic version floods a market, gets rejected, finds a use it's actually suited for, and eventually becomes so common that the original material turns into the premium option.

Why I don't think AI fits that same story

It's tempting to slot AI straight into that pattern, and a lot of smart people are doing exactly that right now. I don't think it holds up, and the reason is specific. Polyester's entire ceiling, at every stage of its history, was cheaper and more convenient than the real thing. No version of a polyester shirt ever cured a disease, extended a life, or did something cotton simply couldn't. That ceiling was never on the table for it.

To be fair to the comparison, though, it's not really a claim about what AI could theoretically do. It's a claim about how AI gets used, pushed into everything regardless of fit, while a handful of companies capture most of the profit and the rest of us absorb the downside. I think that's a fair description of a lot of AI deployment right now. Where I think it goes wrong is treating that pattern as proof AI's ceiling is low, when it's really proof of a choice being made well above what the technology is capable of.

AI already has that higher ceiling, and you can see it in two very different fields. Insilico Medicine took an AI discovered drug for a fibrotic lung disease from target identification to Phase II clinical trials in under 30 months, a process that traditionally takes six to eight years. Antibiotic discovery, stagnant for decades because new classes weren't commercially attractive enough, is being revived the same way, deep learning models screening millions of candidate molecules through a field that had been written off as scientifically exhausted. Climate resilience tells a similar story outside medicine. For most of history, accurate flood forecasting at scale simply wasn't possible, the physics were too complex and most of the world's rivers had no gauges to measure them. AI-driven models have since expanded reliable flood forecasting to more than 150 countries, including Bangladesh, where the system now covers 360 million people who previously had no early warning system at all.

Compare that to what polyester's one real strength actually cost people. Performance wear came bundled with a health price, not a benefit. Every wash sheds microplastics, as many as 6.8 million fibres from a single cycle, and the dyes used to colour it are one of the most common causes of textile related skin irritation. Even polyester's one benefit came with a cost attached. AI's tradeoff, in medicine and in climate forecasting, has gone the other direction: it's improving outcomes people actually feel, not quietly taxing them.

So if it's not the technology, what's actually wrong?

My take isn't "AI is good, don't worry about it." We've had artificial intelligence in some form for decades, pattern recognition, recommendation engines, expert systems. What's new is the generative wave, and more specifically, the race that's formed around it. The five biggest US hyperscalers are on track to spend somewhere around $700 billion combined on AI infrastructure in 2026 alone, nearly double what they spent the year before, all chasing dominance in a market that hasn't even proven it can generate returns close to that spend.

That's the environment the hype grows in. When the whole industry is racing to be first, biggest, and most "transformative," the boring, unglamorous problems that actually matter, climate mitigation, treating diseases nobody's chasing, the antibiotic example above, keep losing to whatever version of AI gets attention and funding fastest. A quiet, hard problem solved rarely makes headlines the way a flashy new chatbot launch does. So the industry reaches for the hype word and climbs the ladder, while the harder problems sit there mostly untouched, and the people who need them solved are stuck absorbing the cost.

The real answer to the title

So, is AI the new polyester? I don't think so. Polyester was cheap and synthetic everywhere on purpose, because that was the entire ceiling of what it could ever be, nobody was ever going to find a life-saving use for a leisure suit. AI has no such ceiling. A model that compresses a decade of antibiotic research into something workable again, or gives 360 million people in Bangladesh a flood warning they never had, is doing something that simply wasn't available at any price before now.

Which is why I'd say the polyester comparison is aimed at the wrong culprit rather than the wrong pattern. The critics have a point on all three counts: AI is being deployed carelessly, a handful of companies are capturing most of the value, and the whole thing does look like a synthetic material flooding in before anyone understood the cost. What they're missing is that none of that was inevitable the way polyester's ceiling was. A fabric never got a say in what it became. The people building and selling AI do, every time they choose "impressive and fast" over "good but slow." A fabric can't be held responsible for that choice. The people making it can.