{"id":8964,"date":"2026-09-27T12:27:25","date_gmt":"2026-09-27T10:27:25","guid":{"rendered":"https:\/\/www.creativejuiz.fr\/blog?p=8964"},"modified":"2026-09-27T12:27:55","modified_gmt":"2026-09-27T10:27:55","slug":"ai-saves-us-time-who-pockets-the-difference","status":"publish","type":"post","link":"https:\/\/www.creativejuiz.fr\/blog\/en\/the-blog\/ai-saves-us-time-who-pockets-the-difference","title":{"rendered":"AI saves us time. Who pockets the difference?"},"content":{"rendered":"\n

For almost four years now, we’ve been told that AI will make us more productive. For once, the promise isn’t completely hollow: the time saved is very real. What’s missing is the rest of the sentence. Time saved\u2026 for whom?<\/p>\n\n\n\n\n\n\n\n

Before we start.<\/strong> This text is a reflection, not a settling of scores with any particular employer. I’m writing it wearing two hats: that of an employed designer, and that of the manager of a very small company. In other words, I’m on both sides of the table. My goal is above all to question organizational choices, never people.<\/p>\n\n\n\n

I’ll go back in time a little, to the industrial era, or rather to that period when factory work was the norm. Then I’ll look at where productivity gains are going today, before suggesting a few fairer options. The lens is necessarily mine: that of someone who spends his days studying AI tools to put them at the service of others, and who wonders who is actually benefiting from our productivity gains.<\/p>\n\n\n\n

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Contents<\/strong><\/h2>\n\n\n\n
    \n
  1. Back to the factory<\/a><\/li>\n\n\n\n
  2. Let’s look at the curve<\/a><\/li>\n\n\n\n
  3. Let’s look for the time saved<\/a><\/li>\n\n\n\n
  4. Let’s be wary of perceived productivity<\/a><\/li>\n\n\n\n
  5. Let’s refuse to let the gain become a faster pace<\/a><\/li>\n\n\n\n
  6. Let’s share the dividend<\/a><\/li>\n\n\n\n
  7. So, what’s the conclusion?<\/a><\/li>\n<\/ol>\n<\/div>\n\n\n\n

    Back to the factory \u2022 The industrial era<\/h2>\n\n\n\n

    In the industrial era, the deal was simple. Want to earn more? You’d work a second eight-hour shift. Sixteen hours at the factory brought the company much more than eight, and part of it ended up on your paycheck. Logical, simple, effective.<\/p>\n\n\n\n

    \"Image,<\/figure>\n\n\n\n

    This deal came at an enormous human cost. In France, before the law of April 23, 1919, working days often lasted 10 to 12 hours. The eight-hour day was a long-standing workers’ demand, championed by unions and several bills<\/a> (in French). Today, European law<\/a> caps the working week at 48 hours on average, overtime included.<\/p>\n\n\n\n

    Good. But as a result, the \u201cwork more\u201d lever got stuck.<\/p>\n\n\n\n

    Work more to earn more<\/h3>\n\n\n\n

    Nicolas Sarkozy did try to reopen it. In October 2006, he coined the slogan \u201cTravailler plus pour gagner plus<\/a>\u201d (\u201cWork more to earn more\u201d), and the TEPA law of August 21, 2007<\/a> encouraged overtime. Four years later, two members of the French Parliament, one from the majority and one from the opposition, assessed its results for the National Assembly.<\/p>\n\n\n\n

    The \u201cearn more\u201d part did happen: more than nine million employees benefited, with an average gain of about \u20ac500 a year. The \u201cwork more\u201d part, however, is nowhere to be found: the number of overtime hours did not increase significantly. Cost of the operation: more than \u20ac4.5 billion.<\/p>\n\n\n\n

    Strange.<\/p>\n\n\n\n

    From the factory to the service sector<\/h3>\n\n\n\n

    Meanwhile, our jobs have changed in nature. In the European Union, industry’s share of employment fell from 20.7% in 1996 to 15.3% in 2016<\/a>. Nearly half of all jobs are now concentrated in two major groups of service activities.<\/p>\n\n\n\n

    So in a service job, what is an hour worth?<\/p>\n\n\n\n

    Take a plumber. Yesterday, it took him an hour to unclog your sink. Today, with a better tool, he does it in twenty minutes. Yet no one would suggest you pay only a third of the bill, because what you’re paying for is the result.<\/p>\n\n\n\n

    Office work runs the other way around. We pay for seven or eight hours of presence, and pretend it measures the value produced.<\/p>\n\n\n\n

    An hour no longer says anything specific. And no matter what you do during that hour, the paycheck \u201clands\u201d at the end of the month.<\/p>\n\n\n\n

    Let’s look at the curve<\/h2>\n\n\n\n

    This disconnect between time, value and pay didn’t start with ChatGPT. In the United States, the Economic Policy Institute (EPI) has long compared<\/a> productivity with the pay of \u201ctypical\u201d workers. Between late 1979 and mid-2026, productivity grew by 93.7% and hourly compensation by 32.7%.<\/p>\n\n\n\n

    Almost three times faster, then.<\/p>\n\n\n\n

    \"Humans<\/figure>\n\n\n\n

    You’ll tell me these are American figures. And you’d be right. Except that the OECD has observed the same phenomenon<\/a> in most of its member countries: raising productivity is no longer enough to raise the typical worker’s real wage. (Yes, the report dates from 2017. I doubt the trend has miraculously reversed since then, but I’ll let you check.)<\/p>\n\n\n\n

    The most ironic part? In 1930, John Maynard Keynes imagined<\/a> that a century later, a fifteen-hour week would be enough. His idea in a nutshell? If we want to keep as many people as possible in work while creating value for everyone, rising productivity per person would let us easily cut working time by 60%.<\/p>\n\n\n\n

    We are infinitely richer than in 1930. The fifteen hours, on the other hand\u2026<\/p>\n\n\n\n

    Incidentally, his horizon was 2030. We have four years left to prove the man right \ud83d\ude09<\/p>\n\n\n\n

    Right, now add AI to that curve.<\/p>\n\n\n\n

    Let’s look for the time saved<\/h2>\n\n\n\n

    Let’s start with the good news: time savings aren’t a sales pitch. According to a survey<\/a> by the European Central Bank (ECB), the share of euro area employees using AI at work rose from 26% in 2024 to 52% in 2026. The median user reports saving three hours a week, about 7.7% of their working time.<\/p>\n\n\n\n

    Three hours. Almost half a day. So where did those hours go?<\/p>\n\n\n\n

    Where do those hours go?<\/h3>\n\n\n\n

    A Danish study<\/a> gives a fairly clear answer. It combines surveys of 25,000 people with the country’s administrative records. The result: 85% of chatbot users reallocate the time saved to other tasks. Fewer than 10% use it to take more breaks or enjoy more free time.<\/p>\n\n\n\n

    And what about pay? Two years after ChatGPT arrived, the researchers, Anders Humlum and Emilie Vestergaard, find no effect on earnings or on reported hours, including among daily users. In fact, 97.7% of users themselves say it has changed nothing on their paycheck.<\/p>\n\n\n\n

    Where does the money go?<\/h3>\n\n\n\n

    The time saved hasn’t disappeared. It has just changed pockets \ud83d\ude09<\/p>\n\n\n\n

    And it’s not me saying this, it’s\u2026 OpenAI. In a public policy document<\/a> published in April 2026, the company acknowledges that people can recognize a productivity gain without feeling they see the benefits. When the company selling the tool writes it in black and white, I think the question deserves to be asked out loud. (Still, keep in mind that OpenAI has every interest in appearing responsible on this topic.)<\/p>\n\n\n\n

    So I’ll ask it. Are you better paid since you started using AI, with what you’d consider a direct, logical link? Have you been given a day off, a bonus, any perk at all?<\/p>\n\n\n\n

    A personal note: my professional circle has always rated me as more productive than average. I sincerely thank them for that. But looking back, I know three things:<\/p>\n\n\n\n

      \n
    1. it isn’t necessarily rewarded, or even useful, in a company. Maybe I’m a bit foolish to keep at it;<\/li>\n\n\n\n
    2. it won’t get any better with AI;<\/li>\n\n\n\n
    3. what can’t be measured can’t be negotiated.<\/li>\n<\/ol>\n\n\n\n

      That third point is the heart of the problem. \u201cWhat can’t be measured can’t be negotiated.\u201d And when a difference can’t be negotiated, it ends up as silent discrimination: same salary, not the same contribution, and no clean way to talk about it without coming across as arrogant.<\/p>\n\n\n\n

      AI only amplifies this unease. It potentially helps all of us go faster on low-value tasks. Some people will save 10% of their time, others will multiply their output by 2 or 3. In the end, we’ll still be paid for 35 to 40 hours a week.<\/p>\n\n\n\n

      The profit, meanwhile, flows to the company.<\/p>\n\n\n\n

      Let’s be wary of perceived productivity<\/h2>\n\n\n\n

      Before claiming our share, a bit of humility all the same. The productivity we feel isn’t necessarily the productivity we produce.<\/p>\n\n\n\n

      In 2025, the METR organization ran a randomized trial<\/a> with 16 experienced developers on 246 real tasks. With AI, they took 19% longer. The most troubling part? Afterwards, they believed they had been 20% faster.<\/p>\n\n\n\n

      Ouch. Quite a gap. Quite a perception bias.<\/p>\n\n\n\n

      Important note<\/strong>: METR has since relaunched the experiment<\/a>, but considers its new data unreliable. Too many people now refuse to work without AI in order to take part. This result therefore mostly reflects a moment in time, and a significant perception bias. And the fact that this second randomized trial was undermined by changing work habits is far more revealing.<\/p>\n\n\n\n

      Another nuance, this time in customer support. A study of more than 5,000 agents<\/a> measures an average gain of 15%, with large differences from one person to the next. The least experienced improve markedly, the most experienced barely at all. The ECB also observes<\/a> a highly skewed distribution: most gain a little, a few gain enormously.<\/p>\n\n\n\n

      Within a company, I roughly see two families of use:<\/p>\n\n\n\n