Twelve seconds, sixty-six years
On 17 December 1903, at Kitty Hawk, the Wright brothers' Flyer stayed in the air for twelve seconds. Sixty-six years later a man walked on the Moon.1 A single human lifetime separates the first powered flight from the landing: a child watching that day could have seen both.
I often tell this story because it describes how the future shows up. First as a curiosity, then as news, and finally as a habit nobody notices any more. None of the witnesses at Kitty Hawk thought they were watching the beginning of mass air travel. They saw a fragile machine struggling to leave the sand.
Why we notice late
The American researcher Roy Amara summed it up in a sentence that became a law: we tend to overestimate the effect of a technology in the short run and underestimate it in the long run. Artificial intelligence is its clearest example. In 1955 the organisers of the Dartmouth workshop, which gave the field its name, expected significant progress within a single summer.2 Decades of broken promises followed, the "AI winters".
Then data, computing power and algorithms matured together, and everything sped up. In 2016 AlphaGo beat Lee Sedol at Go, a milestone many experts placed at least ten years away.3 In November 2022 ChatGPT arrived: according to UBS estimates reported by Reuters, it reached 100 million monthly users in about two months. TikTok had taken nine months, Instagram two and a half years.4
The lesson of the dynamo
There is another half to Amara's law, the one about the long run, and it is the most useful for anyone at work. By the end of the nineteenth century electricity was already a mature technology: light bulbs and power stations had existed since the early 1880s. Yet for decades factories did not become more productive.
The economic historian Paul David explained why in a 1990 essay that became a classic.5 At first, industrialists simply replaced the big steam engine with a big electric motor and left everything else as it was: the same line shaft, the same belts, the same multi-storey buildings. The gains came only when factories were redesigned around the new technology, with a small motor for each machine, production lines on a single floor and workers trained to take more decisions.
With artificial intelligence I see the same pattern. Many companies are bolting an assistant onto yesterday's processes, like an electric motor on the old line shaft. It works, but it changes little. The real value will come when work is rethought around what the machine can do, and around what people do better than it.
What I see from the inside
In my work I watch this pattern every week. A tool that looks like an experiment in January is part of a company's processes by June. The gap that matters separates those who have understood the direction from those waiting for the novelty to settle. Usually, by the time it settles, others have already seized the advantage.
Noticing in time does not mean chasing every announcement. It means telling noise from signal: a technology becomes an innovation when it meets a real problem and someone who uses it. It is the formula I built my children's book on, and it holds for a company as much as for a three-year-old.
…the future is still open, and it will be written by people who are three years old today.
From Un perché alla volta (translated)
Three signals to watch
When I need to tell whether something new is noise or the start of a change, I look at three things.
- The cost collapses. When an activity that took days of work becomes almost free, the products and services built on top of it change. It happened with digital photography, and it is happening with text, images and code.
- Non-specialists use it. A technology leaves the lab when it is adopted by people who do not know, and do not need to know, how it works.
- Someone reorganises the work. The strongest signal is not an announcement but a competitor that changes processes, roles and timing thanks to the new tool. From that moment, waiting has a cost.
The question to ask now
What artificial intelligence can do today will change within months, so a different question is more useful: what becomes possible when what costs effort today costs almost nothing tomorrow? Those who ask early have time to rethink products, skills and organisation. Those who wait can only adapt.
The future always arrives sooner than expected. Not always in the expected shape, but almost always sooner.