Where are we on the sigmoid curve?

If I could make everyone watch one video about AI, it would be a 15 minute video from February 2023. It was made a couple of months after ChatGPT came out, by someone who just wanted to fix his email backup. It explains the promise of AI, the fear of it and the possible bubble better than anything I have read since.

Tom Scott is a British YouTuber and former web developer. For ten years he put out a video every single week: short, well-researched explainers about places, language, history, science and technology. If you have watched educational YouTube in the last decade, you have probably seen him.

He is about my age. When he says in the video that he was lucky enough to live through the mass adoption of the internet, and that he was on the cutting edge of it, I know exactly what he means, because I lived it too.

The core of the video is one idea. Useful new technologies follow a sigmoid curve, an S shape. There is a slow start while the technology is invented and the worst problems get sorted out. Then growth explodes: people find it useful, it gets better and better, competitors pile in and everyone finds more real uses for it. Then it reaches the limit of what is possible with that technology, and progress flattens out again. That is why very few people camp outside Apple Stores for the new iPhone any more.

For digital things, I have always, a bit stupidly, been at the start of the sigmoid curve. I once had the address marcus@algonet.se. Algonet was Sweden's first internet provider for private people, and Marcus is the most common name of my generation in Sweden. Getting your bare first name at a Swedish provider says less about me being clever and more about my father's interest in new technology, and about how few people cared about the internet when Mosaic was still the go-to browser and Netscape was seen as something disruptive.

Tom picks Napster, 1999, as the moment he should have seen the storm coming. It wasn't the first sign, but it was the first big one: millions of non-technical people using something by choice, the first to get mass-media attention and legal problems. In 1999 about 41% of Swedes were online. It was the start of the steep part, not the start of the curve.

I remember it as a change in what I did every day. This is how getting a new song changed for me, from the record shop to Spotify:

None of those steps felt dramatic while they happened. Each one was just a bit easier than the one before, and then one day the old way was gone. That is what the steep part of the curve feels like from the inside.

Then he says the thing that makes the video so good:

He lays out three options. If we are near the top, programmers and artists get some new tools, but nothing at a human level, and not many jobs change. If we are in the middle, we get very impressive tools soon that still need humans to work them. And if we are at the start, at the Napster point, then everything is about to change, just as fast and just as strangely as it did in the early 2000s, and this time he is on the wrong end of it, like the music executive in 1999.

He ends by saying that at some point he will look back at the video and, with hindsight, easily see where we were on the curve. It has been almost four years, so let me try.

The reason the question is so hard is that "AI" isn't one curve. There is how good the technology is, how many people use it, and how much money is being bet on it. They don't move together, and most arguments about AI are people talking about different curves.

Capability: still climbing

In the video, ChatGPT writes a Google Apps Script that is a bit wrong, Tom fixes it with plain English, and he decides it codes about as well as he does with his out-of-date skills. The next day he gives it a problem that needs a logical leap, and it confidently fails in several obvious ways. So he isn't worried about his job. "Not yet, anyway."

That second problem is the one that has changed the most. In 2026 I don't ask a chatbot for a script, I hand a coding agent a task and it reads the code, runs the tests and fixes its own mistakes. I configured this website that way, and I had an agent document every Drupal 11 module for the module knowledge base. It still fails, sometimes confidently, but at a size of task that was science fiction in February 2023.

My own way of writing code went through the same kind of steps as music did:

There is a measurement for this. METR tracks how long a task, measured in human time, the best models can finish half of the time. In March 2025 that length had doubled about every seven months for six years. Their update from January 2026 puts the doubling since 2024 at about 89 days. A curve that gets steeper is not one that is flattening. Benchmarks only measure what can be measured, and the top of an S always looks like a straight line from below, so I can't promise it keeps going. But I don't see the bend yet.

Adoption: possibly the steep middle

Tom's barber had used ChatGPT to write a formal email. For Tom, that was the Napster moment: not the nerds, but everyone. Pew Research asked Americans in February 2026, and about half of US adults now use AI chatbots (49%), up from a third in 2024. 44% have used ChatGPT, up from 18% in 2023. About a quarter use a chatbot every day.

That is fast, even for a sigmoid curve. Not every new technology spread faster than the one before, but the curves have been getting steeper. Here is how many years it took from launch until half of the US had it:

And the US is not where the enthusiasm is. People in emerging economies are much more positive about AI than people in Europe and the US. In a 2025 study by the University of Melbourne and KPMG of 48,000 people in 47 countries, three in five people in emerging economies trusted AI systems, against two in five in advanced economies. The Stanford AI Index 2025 shows the same split in an Ipsos survey from 2024: 83% in China, 80% in Indonesia and 77% in Thailand say AI products have more benefits than drawbacks, against 40% in Canada, 39% in the US and 36% in the Netherlands. A large part of the world is not hesitating at all.

Then there is Germany, where I live, the country I would pick as the example of always being off the curve on digital things. As Angela Merkel said: "Das Internet ist für uns alle Neuland", the internet is new territory for all of us. #Neuland became a meme. During the pandemic, some health offices still reported COVID cases by fax. And in 2024 only 36.8% of German households could get fibre to the home, against 69.2% in the EU as a whole, according to the EU's Digital Decade report. I had fibre when I left Sweden in 2008... From a digital point of view, I seem to have picked the worst country to settle in. Outside of the red tape, most other parts are fantastic, though.

Half is the middle of an S, and the middle is where it is steepest. For the internet in Sweden, that was around 2000. So for adoption we are past the Napster point. We are in the part Tom was afraid of, where it changes everything, fast and strangely.

This is what that curve looked like for the internet in Sweden, the one I lived through:

Money: running ahead like headless chickens

And then the bubble. According to J.P. Morgan Asset Management in June 2026, analysts expect five US companies to spend about 697 billion dollars on capex this year, 173 billion more than they expected in January. AI capex went from 33% of the big cloud companies' operating cash flow in 2023 to an estimated 93% in 2026. That is a bet that the curve keeps going up, paid for before the revenue is there. And Nvidia's Jensen Huang might have just popped the bubble by breaking another commitment.

The dot-com crash came in 2000 and 2001, right in the middle of the steep part. Companies went bankrupt, the Swedish start-up Boo.com among them, and a lot of people lost a lot of money. And internet use just kept going up. Sweden went from 46% online in 2000 to 79% three years later. The crash was about the money being early and spread over too many bets, not about the internet being useless. Much of the fibre laid by companies that went bust was used later anyway.

That is my answer to the bubble question. It can be a bubble and a sigmoid curve at the same time. The money curve looks to me like it is ahead of the other two, the way it was in 1999, and it may well have to wait for them in a painful way. But a correction in the money would not move the capability or the adoption back to 2023. Nobody uninstalled the internet in 2001. Just don't forget how to develop applications yourself: Claude Code subscriptions will not last forever.

Using Tom's three options: not near the top, because the capability curve isn't bending yet. For adoption, we are in the middle, at the steepest point. And the Napster moment he was afraid of was already behind us when he made the video. ChatGPT was the Napster, the barber was the sign, and we are now somewhere around 2000 in internet years: the steep part, maybe with a crash in the money ahead, and with the strange changes still to come.

So my summary is that I still feel the way I did when that video came out. It is impossible to say where this ends, but we know that 2023 was not the end, at least. If the curve flattens soon, I think it will be because of electricity rather than the models: data centres need power, and power grids take decades to build, not months. I'm as excited and as scared as I was back then.

If you want one very tangible proof that we have moved somewhere between 2023 and 2026, look at Will Smith eating spaghetti. The first one is from 2023, the second from 2026:

And the more that gets released in AI, the more I'm convinced that trying to figure out the future is impossible. One could hope for better people or governments leading this revolution, but the revolution won't stop.