AI Was Supposed to Save Us Time. It Didn't

It's Monday, February twenty-third, and welcome to HigherIQ. Quick note: we've been covering a lot of AI and tech lately. We know. It'll cool off — but right now, this stuff is moving fast and we think it matters. Today's story especially, because it's not really about AI at all. It's about us. AI was supposed to give us our time back. Work less, produce more, maybe finally leave the office at five. Instead, something strange is happening: everyone's busier than ever. Today: why the most powerful productivity tools in history might be making us less productive — and what that reveals about how we're wired. Researchers at UC Berkeley just spent eight months embedded inside a two-hundred-person tech company, watching what happens when workers actually adopt AI tools. Not theoretically. Not in a lab. In the wild, with real deadlines and real pressure. What they found wasn't what anyone expected. Employees became more productive. That part worked. They could write code faster, generate reports in minutes, tackle tasks that used to take hours. But here's the twist: they didn't work less. They worked more. They took on additional projects. They expanded into tasks outside their job descriptions. Product managers started writing code. Designers took on engineering work. The boundaries that used to define roles started dissolving. And breaks disappeared. Workers described sending "one last prompt" before lunch, then during lunch, then after hours. AI made starting a task so easy that people kept starting more tasks. The researchers called it "workload creep" — this quiet, invisible expansion of what's expected, driven not by managers demanding more, but by employees who suddenly felt like they could handle more. One engineer put it perfectly: "You had thought that maybe, oh, because you could be more productive with AI, then you save some time, you can work less. But then really, you don't work less. You just work the same amount or even more." This isn't an isolated finding. A survey of fifteen hundred corporate professionals found eighty-three percent experiencing burnout, with overwhelming workloads as the top cause. Another study found seventy-seven percent of employees using AI said it had actually increased their workload. The technology works. That's not the problem. The problem is what we're doing with the gains. Here's the thing: we've seen this movie before. In the nineteen twenties, the electric washing machine was going to liberate housewives from backbreaking labor. No more scrubbing clothes on a washboard for hours. No more heating water over a fire. The technology worked exactly as promised — what used to take a full day could now be done in a couple of hours. So what happened to all that freed-up time? It vanished. In nineteen twenty-four, the average American housewife spent about fifty-two hours a week on housework. By the nineteen sixties — after washing machines, vacuum cleaners, dishwashers, and every other labor-saving device had become standard — she was spending fifty-five hours. More time, not less. The technology didn't reduce work. It raised standards. Monthly laundry became weekly laundry. Weekly became twice-weekly. Clothes that used to be acceptable for days now needed to be fresh every morning. Basic cleanliness became spotless homes. The goalposts moved exactly as fast as the tools improved. This is sometimes called Parkinson's Law: work expands to fill the time available. But it's actually something deeper. When you make a task easier, you don't eliminate the task. You raise expectations for what "good enough" looks like. Think about email. It was supposed to replace memos and phone tag — faster, more efficient, done. Instead, we now send and receive a hundred times more messages than we ever did on paper. The tool worked. The workload exploded. Or spreadsheets. When accountants did calculations by hand, a financial model might have ten scenarios. Now that Excel can run a thousand scenarios in seconds, guess how many scenarios your boss expects? The tool worked. The expectations expanded. Or smartphones. They were supposed to free us from our desks. Instead, the office follows us everywhere. The tool worked. The boundary between work and life dissolved. This is the pattern. Every time we get more efficient, we don't rest. We raise the bar. And AI is following the same trajectory, only faster. There's another cost nobody's measuring. Researchers at Stanford and BetterUp recently coined a term for something that's been quietly spreading through offices everywhere: workslop. That's AI-generated work that looks polished on the surface — nice formatting, professional language, complete sentences — but is actually hollow. Generic summaries that miss the point. Reports padded with filler. Code that technically runs but solves the wrong problem. Forty percent of workers say they've received workslop from a colleague in the past month. Each instance takes an average of two hours to untangle — figuring out what's missing, what's wrong, what the person actually meant to say underneath all the AI-generated fluff. The math is brutal. That works out to about a hundred and eighty-six dollars per employee per month in lost productivity. For a ten-thousand-person company, that's over nine million dollars a year — not on AI tools, but on cleaning up after them. And the damage isn't just financial. Half of workers who received workslop said they now view the sender as less creative, less capable, less trustworthy. The AI did the work. The human got the blame. Here's what's happening: AI makes it trivially easy to produce something that looks like work. Three paragraphs of professional prose when one bullet point would do. A ten-page report when a two-sentence answer would suffice. The effort disappears, but so does the thinking. And someone downstream has to do the thinking anyway — they just have to do it while wading through a swamp of polished-looking nonsense first. One Stanford researcher put it bluntly: "For me to produce sloppy work, I still have to put in a fair bit of effort. Now that the effort piece is gone, I can generate a lot of useless content very easily." So what do we do with this? The honest answer is: we don't know yet. Every transformational technology goes through this phase. Personal computers created more paperwork before they reduced it. The internet made information overwhelming before it became searchable. There's a J-curve to these things — it gets worse before it gets better. But here's what we keep thinking about. This isn't really a technology story. It's a story about what we do when things get easier. We don't rest. We raise the bar. Think about your own life. When you get a task done early, do you take a break? Or do you start the next thing? When you finish a project under budget, do you pocket the savings? Or do you expand the scope? When you have a free Saturday, do you actually rest? Or do you fill it with "productive" things you've been meaning to do? We've built entire identities around being busy. Entire cultures around optimization. We measure our worth in output. And when a tool comes along that makes output easier, we don't say "great, we can relax now." We say "great, we can do more." The washing machine wasn't the problem. The vacuum cleaner wasn't the problem. AI isn't the problem. The problem is that we've forgotten — or maybe never learned — what "enough" looks like. The Berkeley researchers had a phrase for what's missing: "intentional pauses." Not more productivity hacks. Not better prompts. Just... stopping. Deciding what's actually worth doing before you do more of it. AI can write your emails in seconds. The question is whether you'll use that to send more emails, or to send fewer, better ones. AI can generate a report in minutes. The question is whether you'll use that to produce more reports, or to spend the extra time actually thinking about what the data means. Or — and here's the radical option — to just not fill that time with more work at all. The washing machine was supposed to give housewives their afternoons back. It didn't, because nobody decided that clean enough was clean enough. AI is supposed to give knowledge workers their time back. Whether it does depends entirely on whether we can do something our great-grandmothers couldn't, something that might be the hardest thing of all: take the win. Keep the gains. Actually stop. The technology works. It's always worked. The question is whether we will. Stay informed, stay curious, and we'll see you tomorrow.