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I have a simple question for you.
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Let's say you figure out how to do your job in half the time.
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Well, who gets the other half?
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This is not a philosophy question.
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This is a legitimate question that a lot of leaders, a lot of employees are now starting to ask, especially as we start to use more AI in the workplace.
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If I can be more productive, more efficient, and get my job done in half the time, then what happens to the other half of my time?
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This is, I think, a big debate that we're going to continue to have, not just inside of our organizations, but on big political stages in the upcoming elections as well.
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So there are three stories today that I want to get to.
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Number one, more than a third of U.S. employers handed out flat across the board raises this year, known as peanut butter raises.
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Story two, workers' share of U.S. economic output just hit the lowest record in the
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the lowest level ever recorded.
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And the last story of the day, LinkedIn is telling its users to lean less on AI.
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So those are gonna be the top three of the day.
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It is Thursday, August 6th, 2026.
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And welcome to Future Ready Today.
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If you like this kind of content on the future of work, please consider subscribing to the show on Apple, on Spotify, whatever your preferred platform is.
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So the first story of the day, the peanut butter raise.
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Fortune reports today that around 36% of U.S. companies gave out standard across-the-board pay increases this year, according to a new pay scale report.
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These are, of course, called peanut butter raises spread evenly across all of your employees across the entire workforce, regardless of performance.
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Now, the report notes they're most common in sectors with very large workforces, hourly staff and step structures, government and education being among them.
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According to the same pay scale report, about 25% of companies admitted they were losing talent in 2026 because their pay increases were not sufficient.
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Looking ahead, about 32% of employers still plan to distribute flat raises next year, but the report found merit increases will account for 3% of a 3.5% total payroll budget for 2027, which is the largest single chunk.
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Now, the reason why this is happening, according to the report, pay scale points to economic uncertainty and dwindling budgets and notes that flat raises reduce administrative burden.
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Fortune also cites a Willis Towers Watson report, finding roughly a third of businesses planned to lower their pay increase budgets this year compared to 2025, with employers citing a looming recession, weaker financial performance, and a desire for more cost control.
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Now, the futurist lens here.
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This is also a little bit ironic because the CEO of Anthropic, Dario Amadei, recently came out and he said that he's concerned
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that people are mainly wanting to work for Anthropic and stay at Anthropic because of the massive, massive salaries and compensation and equity packages that people are getting.
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I mean, first of all, are we really surprised that that's why somebody wants to go work for Anthropic?
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Is Dario really that naive to think that people want to go work at the company because they're trying to do good?
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Or
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Is it perhaps because they want to be multi-millionaires and get a piece of Anthropic before it goes public, likely sometime next year?
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So again, the futurist lens here is all going to be very upfront about this.
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Pay your best people more.
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Pay your best people a lot more.
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I think if there's a reason why somebody is considered a top performer or you label them as a best employee at your company,
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There's a reason for that.
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Reward them for that.
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Compensate them for that.
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I think that makes sense.
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And even if they are using AI, that still counts.
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That's not cheating.
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That's part of the job.
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How do you use the tools that we give you to become more productive, more efficient, make a bigger impact on the bottom line, impact the team, the business, et cetera?
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It's not cheating.
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This is the goal.
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This is why you were hired.
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Figure out how do I make a bigger impact on the business?
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Now, the pushback that managers will frequently cite here, they'll say something along the lines of, well, somebody on my team tripled their output, and I don't know if they got better or if the tools got better.
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Am I rewarding the person or am I rewarding a subscription that they have to clod or to chat GPT?
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We've seen these same arguments before.
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This is not new.
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We had this about spreadsheets.
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We talked about this about CAD, about CNC machines, about the surgeon who learned to operate through a camera instead of a big incision.
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These are not new topics to debate.
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But every time somebody said the tool did the work, every time they were wrong.
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There's no such thing as a carpenter minus the saw.
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There's no such thing as an electrician minus the tools that they use.
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I mean, the tools are a part of the trade.
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It's part of what you need to do to be good at your job.
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Now, everybody on your team has the same tools.
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Usually everybody has the same tools, the same resources, the same models, the same price sitting right there.
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Now there are some people at your company who are willing to use those tools, embrace those tools, figure out how to do a better job.
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There are other people at your company who are saying, nah, that's not for me.
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I'm not going to go near it.
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Well, if that's your choice and you're getting eclipsed by the people who are using the tools, well, whose fault is that?
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If you are an electrician.
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and you're using the newest tools, the newest voltmeters, the newest amp meters, whatever it is, and your peers are not, and you're able to get your work done quicker, well, whose fault is that?
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If you're a plumber and you're using some sort of cool AI contraption and software to find leaks inside of a house while somebody else is still kind of manually going by and listening to the pipes, and you're able to service four homes in the time that it takes him to serve one home, whose fault is that?
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Obviously, the person who's able to serve more homes and do a good job is going to get more money, more business.
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They're going to grow and expand.
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This is just how things go.
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So I don't buy that argument.
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I don't think it's a good argument to have.
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When the tool is the same for everyone, the difference in what people produce is human.
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You have to know how to use the tools, right?
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You have to know how to check, how to verify, how to get the most out of these things.
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And this is judgment.
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This is taste, discernment, creativity.
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That's where it goes into unlocking the potential of the tool so that it can make you better.
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And so I think what a lot of companies are doing, whether they intend to do this or not, is, you know, they're just, I don't know, they're just ignoring that.
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If somebody cuts 20 hours a week out of a process, what do they get?
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20 more hours of work, the same as everybody else.
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Do that twice, and basically you taught your entire company something that they're never going to unlearn.
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And that is, if you are better, we're just going to throw more work at you.
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This is going to be another story.
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I'm going to talk about this in a bit.
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Frederick Winslow Taylor, in 1911, he had this concept called soldiering.
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Workers on the factory floor knew exactly how fast a job could be done, and they hid it.
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They hit it because every time management found out, the rate got cut and the reward was, well, you did it quicker and better.
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Now we're going to give you even more work to do.
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And so Taylor got a lot of things wrong.
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But what he was right is that this was not about laziness.
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This was about people who are responsibly sensing a bad deal.
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And the deal is that if I can be more productive and more efficient, that you are going to reward me by simply putting more things on my plate.
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It doesn't make sense.
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Every survey out there, actually a lot of surveys out there, have been showing that a lot of employees are now hiding their AI use.
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Or they're trying to purposely get the wrong answers from AI.
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So the honest case is for a flat raise, I get it.
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It's simple, it's fast, it doesn't require a manager to defend anything, but the easiest corrections and the best things that you should be doing are not the same thing.
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If you have people at your company who are doing a good job, reward them.
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Pay them well, give them the tools and resources that they need.
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Don't simply slam more work on top of their heads.
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That's a bad deal.
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Doesn't make any sense.
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Story number two, kind of building on that, and this is where there's going to be a lot of debate.
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And I myself am not entirely sure what the right answer to this is going to be because there are a lot of variables at play.
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And the second story is that Reuters reports this morning
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That workers' share of U.S. economic output has fallen to a fresh record low.
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According to the Bureau of Labor Statistics, the labor share, which is the percentage of output that accrues to workers in the form of compensation, hit a record low of 52.9% last quarter.
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Reuters notes the BLS labor shares series go back to 1947.
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So the same BLS report showed non-farm productivity, which measures hourly output per worker, increased at a 1.4% annualized rate in the second quarter after an upwardly revised 0.8% pace in the January-March quarter.
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Economists forecasted 0.6%.
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So productivity grew at a 2.2% rate from a year ago and has grown at a 2.1% rate from the fourth quarter of 2019 through the second quarter of 2026.
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There's some cost numbers that were reported in here as well.
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I'm not going to go through all the cost numbers because I don't want to smack you over the head with percentages.
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But Reuters is reporting that
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That economists said there were some signs that business adoption of artificial intelligence was raising productivity last quarter.
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This is the big debate.
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Is it doing it or not?
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Oliver Allen, senior U.S. economist at Pantheon Macroeconomics, said weak growth in the labor force is likely pushing companies to squeeze a bit more from their existing workforce.
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Reuters notes economists and policymakers are anticipating an AI build-out will boost productivity and curb inflation through a reduction in labor costs.
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On the broader picture, initial jobless claims rose by 1,000 to 199,000 for the week ended August 1st, against a forecast of 202,000.
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So reported planned job cuts by U.S. employers actually dropped 27% to 33,429 in July, the lowest level since July 2024.
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So this is the big debate.
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Unemployment rate, relatively low.
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We see a lot of people who are obviously in the workforce.
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We're trying to figure out, are we seeing productivity gains from AI or not?
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Will we see them from AI or not?
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So it's very hard to try to figure out what to do here from a business perspective, from an economy perspective, from a political perspective.
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So the futurist lens here is that
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52.9%, that is the smallest slice of the economy that workers have taken home since we started keeping track in 1947.
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So productivity is up 2.2% over the year.
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The cost of an hour of labor is up 1.4%.
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So when what a worker produces climbs faster than what a worker costs, the extra goes somewhere.
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And right now, it's going to whoever owns the company where that person works.
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So again, the productivity is up 2.2%.
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The cost of an hour of labor is up 1.4%.
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So it's not a huge gap, but it's a gap of almost one percentage points between the level of productivity versus how much more somebody is making.
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And so the argument is that extra roughly 1%, 0.8% is going back to the company's.
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And I mean, to be honest, this is how business has always worked, right?
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This is not new.
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Someone has to build the thing first.
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And companies are spending enormous sums on AI infrastructure right now.
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Enormous, staggering numbers, hundreds of billions of dollars, trillions of dollars.
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And so returns to capital are what pull investment forward in the first place.
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Nobody funds a data center out of goodwill or because they're being altruistic or because it's, you know, cool.
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But there is a difference between capital earning a return and workers being left out of the deal entirely.
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And the interesting question that I think is going to be much more front and center is not just going to be whether workers should get a slice, but it is what does a slice actually look like?
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I believe the Trump administration was recently having these types of conversations where they were talking about maybe taking a partial ownership stake in something like OpenAI or putting it as a part of Trump accounts, where maybe a small percentage of OpenAI goes into these Trump accounts.
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Again, early stage conversations.
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But this is going to be a big topic of discussion.
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You see the big...
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backlash against AI.
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And the reason why this is such a very hard thing to figure out right now is because depending on who you ask and depending on the data that you look at, it's not entirely clear what impact AI is having on productivity and efficiency.
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I mean, you see some companies out there who say things like, well, our entire code is now being written by Claude.
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you see other companies out there who say, well, we're spending actually a lot more.
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Our token costs are going through the roof.
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We're cutting back on AI spend.
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You see companies who are saying, well, we're going to let go of employees as a result of AI, and then shortly after they hire them back.
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So we're in this kind of playground phase.
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where we're still trying to figure out, are these things productive or not?
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Are these things going to make a genuine impact on the economy or not?
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I mean, I think they will.
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But how do we measure it?
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And let's say we do measure it and we determine there is more productivity.
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What do we do?
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Would that extra productivity?
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How, if we all agreed that employees should get a slice of AI productivity gains, what is that going to look like?
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Are we going to tax robots like Optimus?
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Are we going to get a potential equity stake in these companies like Anthropic and OpenAI?
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Or is the government going to take a slice?
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Is it going to go into Trump accounts?
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Are we going to get dividend checks?
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What is that actually going to look like?
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And it's obviously a form of profit sharing, but there has to be profit there first.
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And it's not entirely clear and nobody is entirely sure if we're even going to get there.
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Right?
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I mean, you see lots of arguments now.
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Oh, it's an AI bubble.
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It's going to burst.
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It's not that fabulous.
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It's not that great.
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It's causing lots of problems.
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It's hallucinating.
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We're spending more than it's able to generate.
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You see those conversations happening everywhere.
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So I'm not opposed to the idea that.
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that if we're seeing these massive productivity gains and efficiency gains, that there should be some sort of a slice given to people.
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But what is that going to look like?
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How do we do it?
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How are we going to measure things so exactly and precisely to determine how much is specifically being generated from AI?
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How do we know it's not from interest rates, from macroeconomic factors, from tariffs, from imports?
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There could be so many factors out there.
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How are we going to determine exactly what amount comes from AI and how to give it to employees?
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That's going to be a very, very difficult thing to figure out.
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And now, obviously, the objection to this.
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In a bad year, for example, variable pay fails.
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So if these companies don't do well, right, a family with a mortgage may want a steady paycheck more than they want an upside.
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So if you're doing some sort of profit sharing, what happens when these companies don't do well?
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You still take profit from them?
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What does that look like?
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Or is it just going to be kind of 1% equity goes into here and it gets distributed among everybody?
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Everyone gets a $100 check every month.
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I don't know.
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I don't know exactly what's going to happen.
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again, the other stat that I want to put, layoffs just hit a two-year low.
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Announced cuts are down 46% from a year ago.
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No jobs apocalypse.
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In this report from the BLS, Vanguard came out.
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They also said no jobs apocalypse.
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So this will be the big debate.
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I do not know what the answer to this question is going to be.
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But it will be a very interesting one to watch, and it's also one that a lot of people are concerned about.
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Because if employees are getting the lowest percentage of output going to compensation since 1947, and it's all going to the companies that are supposedly building these tools and products and services and using AI, that's obviously something a lot of people are worried about.
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Why am I working so hard in doing all these things and the company's just making all the profits?
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So again, big debate.
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Expect to see much more of this in the coming, I think, one to five years.
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Last story of the day, LinkedIn pumps the brakes on AI.
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So the Wall Street Journal reports that LinkedIn wants its users to lean less on AI and the changes that the company has announced go considerably further than just suggesting that.
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So per LinkedIn's chief product officer,
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Users now get a seems like AI slop reporting option in the ellipsis menu.
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Okay, I have not tested this out yet.
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This is available on both posts and comments.
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Their chief product officer said, slop is hard to define and the definition keeps shifting and the user reports let the company tune its models to make better feeds.
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LinkedIn is also rolling out a new and improved classifiers to identify posts that are AI slop or generally low quality.
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Content those systems flag get recommended less often, particularly in suggested posts from outside of a user's network.
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The company is removing its enhance your post feature, which was a tool that AI or AI rewrote your wording and replaced it with an option.
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LinkedIn is also testing private notifications that are gonna go to creators in their analytics dashboard, which is gonna basically tell them that members have flagged your post
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as inauthentic or being heavy-handed on AI so that people know people don't like your content.
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Now, the futurist lens here is I think this is the first of many signals that we're going to see.
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Everyone is just reading this as LinkedIn is cracking down on AI.
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That's maybe part of it, but I think LinkedIn also publicly is admitting that they don't know the difference between a real person and a machine.
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If a machine is wearing a person's name like Bob, how do you know the difference?
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And so this button that they've created where employee or people can kind of just report something that sounds like AI content, to me it sounds like LinkedIn is just handing it over to the users now because they themselves can't even figure out everything that's AI generated.
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Because remember, LinkedIn actually built their enhance your post option themselves.
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They shipped it, they pushed it, and now they've deleted it.
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Now, I think this matters a lot more beyond than LinkedIn as a social platform.
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Now, I've certainly used a lot of AI for things on LinkedIn.
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Like I'll write a post, for example, or I'll type something up.
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And I'll realize it's not quite phrased the way that I want it to go.
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I wish there was an example, but I can't think of one, or like a cool stat or something that I can put into this post.
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And so I'll frequently type up a post.
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I'll put it in the chat, GPT, or Claude, and I'll say, hey, can you find like a...
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a stat, or can you word this better?
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Because I can't, you know, I can explain the concept, but I can't get the words out the way that I want.
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And so it'll help me put my sentences and my paragraphs better together.
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I mean, it's not AI generated.
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It's my thoughts and my ideas, but kind of put together in a more cohesive and structured way than what I would be able to do.
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And I don't think that's the same as AI-generated content.
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Somebody going to LinkedIn and say, write me a post about the future of SpaceX.
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Copy, paste.
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Now, I think for years, writing something decent about your field was a real signal.
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I mean, I try to do this on a regular basis through my newsletter, futureofworknewsletter.com.
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I try to do this on LinkedIn, through my social channels.
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It costs time.
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It makes you have to actually understand something.
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You have to be involved in a particular field.
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And that's why it worked, because it was really hard to fake this kind of information.
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And now the cost went to almost nothing.
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And anybody can do it.
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This is going to be a workplace problem.
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And it's going to come for you faster than you think.
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Because think about what your organization uses to evaluate people.
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It uses the polished presentation that you might make, the well-written strategy memo, the client proposal, the thoughtful email, the one-pager, the PDF, client deliverables.
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Anything that you put together is usually a very good proxy
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for what an organization uses to evaluate you.
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That's how your leader might say, oh, Jacob is so sharp.
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His arguments are so cogent and cohesive, and he really knows his stuff.
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Every one of these things can now be generated by AI with no particular insight on my behalf in about 90 seconds.
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So managers are already, I think, sitting in reviews, looking at work that appears to be excellent and quietly wondering, what are they actually reading here?
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Is this human or not?
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I've shared many stories from professors, from companies where people are seemingly submitting AI-generated work.
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It looks amazing and fantastic, but then when it comes time to having an in-person discussion about it, they fall apart.
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So I think this is coming into the workplace as well.
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This is why I think the concept of human prompting is so crucial.
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Human prompting is the idea of, and I have a whole post on this on Substack, pulling out the human insights, discernment, the decision-making from your employees.
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because you have to assume that everyone is using AI.
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So how do you get the human insights out of them?
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That's exactly what human prompting is.
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So even though LinkedIn is making this change first, it's going to come to your company.
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I can promise you it's going to come to your company.
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They're going to want to know what insights are yours and what insights are not.
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You might see situations where certain work that you do, you're not allowed to use AI for it, or you're going to be pressure tested.
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You're going to be human prompted on these things.
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This is coming.
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Because in a world where everybody's using these AI tools, how do you stand out?
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So the polish is going to be free.
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The presentation is going to be free.
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The aura of intelligence and wisdom, all that stuff is going to be free.
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What's going to be scarce now is the person.
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It's going to be the human aspect of work.
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So that is my show for today.
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Thank you for tuning in, for watching, and for listening.
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Remember to subscribe to the show if you are interested in more content just like this.
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And the CHRO group is futureofworkleaders.com.
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Thank you, and I will be back tomorrow.
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I have a simple question for you.
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Let's say you figure out how to do your job in half the time.
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Well, who gets the other half?
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This is not a philosophy question.
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This is a legitimate question that a lot of leaders, a lot of employees are now starting to ask, especially as we start to use more AI in the workplace.
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If I can be more productive, more efficient, and get my job done in half the time, then what happens to the other half of my time?
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This is, I think, a big debate that we're going to continue to have, not just inside of our organizations, but on big political stages in the upcoming elections as well.
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So there are three stories today that I want to get to.
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Number one, more than a third of U.S. employers handed out flat across the board raises this year, known as peanut butter raises.
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Story two, workers' share of U.S. economic output just hit the lowest record in the
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the lowest level ever recorded.
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And the last story of the day, LinkedIn is telling its users to lean less on AI.
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So those are gonna be the top three of the day.
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It is Thursday, August 6th, 2026.
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And welcome to Future Ready Today.
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If you like this kind of content on the future of work, please consider subscribing to the show on Apple, on Spotify, whatever your preferred platform is.
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So the first story of the day, the peanut butter raise.
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Fortune reports today that around 36% of U.S. companies gave out standard across-the-board pay increases this year, according to a new pay scale report.
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These are, of course, called peanut butter raises spread evenly across all of your employees across the entire workforce, regardless of performance.
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Now, the report notes they're most common in sectors with very large workforces, hourly staff and step structures, government and education being among them.
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According to the same pay scale report, about 25% of companies admitted they were losing talent in 2026 because their pay increases were not sufficient.
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Looking ahead, about 32% of employers still plan to distribute flat raises next year, but the report found merit increases will account for 3% of a 3.5% total payroll budget for 2027, which is the largest single chunk.
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Now, the reason why this is happening, according to the report, pay scale points to economic uncertainty and dwindling budgets and notes that flat raises reduce administrative burden.
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Fortune also cites a Willis Towers Watson report, finding roughly a third of businesses planned to lower their pay increase budgets this year compared to 2025, with employers citing a looming recession, weaker financial performance, and a desire for more cost control.
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Now, the futurist lens here.
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This is also a little bit ironic because the CEO of Anthropic, Dario Amadei, recently came out and he said that he's concerned
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that people are mainly wanting to work for Anthropic and stay at Anthropic because of the massive, massive salaries and compensation and equity packages that people are getting.
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I mean, first of all, are we really surprised that that's why somebody wants to go work for Anthropic?
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Is Dario really that naive to think that people want to go work at the company because they're trying to do good?
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Or
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Is it perhaps because they want to be multi-millionaires and get a piece of Anthropic before it goes public, likely sometime next year?
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So again, the futurist lens here is all going to be very upfront about this.
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Pay your best people more.
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Pay your best people a lot more.
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I think if there's a reason why somebody is considered a top performer or you label them as a best employee at your company,
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There's a reason for that.
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Reward them for that.
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Compensate them for that.
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I think that makes sense.
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And even if they are using AI, that still counts.
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That's not cheating.
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That's part of the job.
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How do you use the tools that we give you to become more productive, more efficient, make a bigger impact on the bottom line, impact the team, the business, et cetera?
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It's not cheating.
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This is the goal.
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This is why you were hired.
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Figure out how do I make a bigger impact on the business?
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Now, the pushback that managers will frequently cite here, they'll say something along the lines of, well, somebody on my team tripled their output, and I don't know if they got better or if the tools got better.
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Am I rewarding the person or am I rewarding a subscription that they have to clod or to chat GPT?
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We've seen these same arguments before.
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This is not new.
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We had this about spreadsheets.
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We talked about this about CAD, about CNC machines, about the surgeon who learned to operate through a camera instead of a big incision.
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These are not new topics to debate.
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But every time somebody said the tool did the work, every time they were wrong.
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There's no such thing as a carpenter minus the saw.
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There's no such thing as an electrician minus the tools that they use.
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I mean, the tools are a part of the trade.
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It's part of what you need to do to be good at your job.
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Now, everybody on your team has the same tools.
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Usually everybody has the same tools, the same resources, the same models, the same price sitting right there.
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Now there are some people at your company who are willing to use those tools, embrace those tools, figure out how to do a better job.
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There are other people at your company who are saying, nah, that's not for me.
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I'm not going to go near it.
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Well, if that's your choice and you're getting eclipsed by the people who are using the tools, well, whose fault is that?
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If you are an electrician.
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and you're using the newest tools, the newest voltmeters, the newest amp meters, whatever it is, and your peers are not, and you're able to get your work done quicker, well, whose fault is that?
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If you're a plumber and you're using some sort of cool AI contraption and software to find leaks inside of a house while somebody else is still kind of manually going by and listening to the pipes, and you're able to service four homes in the time that it takes him to serve one home, whose fault is that?
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Obviously, the person who's able to serve more homes and do a good job is going to get more money, more business.
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They're going to grow and expand.
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This is just how things go.
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So I don't buy that argument.
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I don't think it's a good argument to have.
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When the tool is the same for everyone, the difference in what people produce is human.
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You have to know how to use the tools, right?
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You have to know how to check, how to verify, how to get the most out of these things.
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And this is judgment.
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This is taste, discernment, creativity.
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That's where it goes into unlocking the potential of the tool so that it can make you better.
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And so I think what a lot of companies are doing, whether they intend to do this or not, is, you know, they're just, I don't know, they're just ignoring that.
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If somebody cuts 20 hours a week out of a process, what do they get?
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20 more hours of work, the same as everybody else.
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Do that twice, and basically you taught your entire company something that they're never going to unlearn.
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And that is, if you are better, we're just going to throw more work at you.
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This is going to be another story.
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I'm going to talk about this in a bit.
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Frederick Winslow Taylor, in 1911, he had this concept called soldiering.
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Workers on the factory floor knew exactly how fast a job could be done, and they hid it.
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They hit it because every time management found out, the rate got cut and the reward was, well, you did it quicker and better.
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Now we're going to give you even more work to do.
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And so Taylor got a lot of things wrong.
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But what he was right is that this was not about laziness.
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This was about people who are responsibly sensing a bad deal.
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And the deal is that if I can be more productive and more efficient, that you are going to reward me by simply putting more things on my plate.
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It doesn't make sense.
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Every survey out there, actually a lot of surveys out there, have been showing that a lot of employees are now hiding their AI use.
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Or they're trying to purposely get the wrong answers from AI.
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So the honest case is for a flat raise, I get it.
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It's simple, it's fast, it doesn't require a manager to defend anything, but the easiest corrections and the best things that you should be doing are not the same thing.
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If you have people at your company who are doing a good job, reward them.
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Pay them well, give them the tools and resources that they need.
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Don't simply slam more work on top of their heads.
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That's a bad deal.
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Doesn't make any sense.
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Story number two, kind of building on that, and this is where there's going to be a lot of debate.
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And I myself am not entirely sure what the right answer to this is going to be because there are a lot of variables at play.
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And the second story is that Reuters reports this morning
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That workers' share of U.S. economic output has fallen to a fresh record low.
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According to the Bureau of Labor Statistics, the labor share, which is the percentage of output that accrues to workers in the form of compensation, hit a record low of 52.9% last quarter.
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Reuters notes the BLS labor shares series go back to 1947.
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So the same BLS report showed non-farm productivity, which measures hourly output per worker, increased at a 1.4% annualized rate in the second quarter after an upwardly revised 0.8% pace in the January-March quarter.
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Economists forecasted 0.6%.
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So productivity grew at a 2.2% rate from a year ago and has grown at a 2.1% rate from the fourth quarter of 2019 through the second quarter of 2026.
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There's some cost numbers that were reported in here as well.
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I'm not going to go through all the cost numbers because I don't want to smack you over the head with percentages.
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But Reuters is reporting that
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That economists said there were some signs that business adoption of artificial intelligence was raising productivity last quarter.
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This is the big debate.
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Is it doing it or not?
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Oliver Allen, senior U.S. economist at Pantheon Macroeconomics, said weak growth in the labor force is likely pushing companies to squeeze a bit more from their existing workforce.
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Reuters notes economists and policymakers are anticipating an AI build-out will boost productivity and curb inflation through a reduction in labor costs.
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On the broader picture, initial jobless claims rose by 1,000 to 199,000 for the week ended August 1st, against a forecast of 202,000.
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So reported planned job cuts by U.S. employers actually dropped 27% to 33,429 in July, the lowest level since July 2024.
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So this is the big debate.
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Unemployment rate, relatively low.
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We see a lot of people who are obviously in the workforce.
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We're trying to figure out, are we seeing productivity gains from AI or not?
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Will we see them from AI or not?
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So it's very hard to try to figure out what to do here from a business perspective, from an economy perspective, from a political perspective.
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So the futurist lens here is that
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52.9%, that is the smallest slice of the economy that workers have taken home since we started keeping track in 1947.
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So productivity is up 2.2% over the year.
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The cost of an hour of labor is up 1.4%.
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So when what a worker produces climbs faster than what a worker costs, the extra goes somewhere.
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And right now, it's going to whoever owns the company where that person works.
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So again, the productivity is up 2.2%.
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The cost of an hour of labor is up 1.4%.
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So it's not a huge gap, but it's a gap of almost one percentage points between the level of productivity versus how much more somebody is making.
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And so the argument is that extra roughly 1%, 0.8% is going back to the company's.
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And I mean, to be honest, this is how business has always worked, right?
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This is not new.
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Someone has to build the thing first.
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And companies are spending enormous sums on AI infrastructure right now.
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Enormous, staggering numbers, hundreds of billions of dollars, trillions of dollars.
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And so returns to capital are what pull investment forward in the first place.
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Nobody funds a data center out of goodwill or because they're being altruistic or because it's, you know, cool.
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But there is a difference between capital earning a return and workers being left out of the deal entirely.
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And the interesting question that I think is going to be much more front and center is not just going to be whether workers should get a slice, but it is what does a slice actually look like?
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I believe the Trump administration was recently having these types of conversations where they were talking about maybe taking a partial ownership stake in something like OpenAI or putting it as a part of Trump accounts, where maybe a small percentage of OpenAI goes into these Trump accounts.
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Again, early stage conversations.
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But this is going to be a big topic of discussion.
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You see the big...
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backlash against AI.
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And the reason why this is such a very hard thing to figure out right now is because depending on who you ask and depending on the data that you look at, it's not entirely clear what impact AI is having on productivity and efficiency.
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I mean, you see some companies out there who say things like, well, our entire code is now being written by Claude.
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you see other companies out there who say, well, we're spending actually a lot more.
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Our token costs are going through the roof.
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We're cutting back on AI spend.
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You see companies who are saying, well, we're going to let go of employees as a result of AI, and then shortly after they hire them back.
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So we're in this kind of playground phase.
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where we're still trying to figure out, are these things productive or not?
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Are these things going to make a genuine impact on the economy or not?
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I mean, I think they will.
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But how do we measure it?
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And let's say we do measure it and we determine there is more productivity.
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What do we do?
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Would that extra productivity?
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How, if we all agreed that employees should get a slice of AI productivity gains, what is that going to look like?
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Are we going to tax robots like Optimus?
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Are we going to get a potential equity stake in these companies like Anthropic and OpenAI?
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Or is the government going to take a slice?
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Is it going to go into Trump accounts?
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Are we going to get dividend checks?
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What is that actually going to look like?
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And it's obviously a form of profit sharing, but there has to be profit there first.
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And it's not entirely clear and nobody is entirely sure if we're even going to get there.
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Right?
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I mean, you see lots of arguments now.
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Oh, it's an AI bubble.
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It's going to burst.
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It's not that fabulous.
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It's not that great.
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It's causing lots of problems.
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It's hallucinating.
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We're spending more than it's able to generate.
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You see those conversations happening everywhere.
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So I'm not opposed to the idea that.
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that if we're seeing these massive productivity gains and efficiency gains, that there should be some sort of a slice given to people.
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But what is that going to look like?
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How do we do it?
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How are we going to measure things so exactly and precisely to determine how much is specifically being generated from AI?
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How do we know it's not from interest rates, from macroeconomic factors, from tariffs, from imports?
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There could be so many factors out there.
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How are we going to determine exactly what amount comes from AI and how to give it to employees?
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That's going to be a very, very difficult thing to figure out.
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And now, obviously, the objection to this.
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In a bad year, for example, variable pay fails.
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So if these companies don't do well, right, a family with a mortgage may want a steady paycheck more than they want an upside.
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So if you're doing some sort of profit sharing, what happens when these companies don't do well?
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You still take profit from them?
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What does that look like?
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Or is it just going to be kind of 1% equity goes into here and it gets distributed among everybody?
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Everyone gets a $100 check every month.
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I don't know.
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I don't know exactly what's going to happen.
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again, the other stat that I want to put, layoffs just hit a two-year low.
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Announced cuts are down 46% from a year ago.
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No jobs apocalypse.
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In this report from the BLS, Vanguard came out.
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They also said no jobs apocalypse.
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So this will be the big debate.
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I do not know what the answer to this question is going to be.
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But it will be a very interesting one to watch, and it's also one that a lot of people are concerned about.
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Because if employees are getting the lowest percentage of output going to compensation since 1947, and it's all going to the companies that are supposedly building these tools and products and services and using AI, that's obviously something a lot of people are worried about.
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Why am I working so hard in doing all these things and the company's just making all the profits?
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So again, big debate.
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Expect to see much more of this in the coming, I think, one to five years.
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Last story of the day, LinkedIn pumps the brakes on AI.
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So the Wall Street Journal reports that LinkedIn wants its users to lean less on AI and the changes that the company has announced go considerably further than just suggesting that.
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So per LinkedIn's chief product officer,
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Users now get a seems like AI slop reporting option in the ellipsis menu.
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Okay, I have not tested this out yet.
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This is available on both posts and comments.
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Their chief product officer said, slop is hard to define and the definition keeps shifting and the user reports let the company tune its models to make better feeds.
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LinkedIn is also rolling out a new and improved classifiers to identify posts that are AI slop or generally low quality.
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Content those systems flag get recommended less often, particularly in suggested posts from outside of a user's network.
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The company is removing its enhance your post feature, which was a tool that AI or AI rewrote your wording and replaced it with an option.
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LinkedIn is also testing private notifications that are gonna go to creators in their analytics dashboard, which is gonna basically tell them that members have flagged your post
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as inauthentic or being heavy-handed on AI so that people know people don't like your content.
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Now, the futurist lens here is I think this is the first of many signals that we're going to see.
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Everyone is just reading this as LinkedIn is cracking down on AI.
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That's maybe part of it, but I think LinkedIn also publicly is admitting that they don't know the difference between a real person and a machine.
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If a machine is wearing a person's name like Bob, how do you know the difference?
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And so this button that they've created where employee or people can kind of just report something that sounds like AI content, to me it sounds like LinkedIn is just handing it over to the users now because they themselves can't even figure out everything that's AI generated.
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Because remember, LinkedIn actually built their enhance your post option themselves.
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They shipped it, they pushed it, and now they've deleted it.
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Now, I think this matters a lot more beyond than LinkedIn as a social platform.
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Now, I've certainly used a lot of AI for things on LinkedIn.
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Like I'll write a post, for example, or I'll type something up.
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And I'll realize it's not quite phrased the way that I want it to go.
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I wish there was an example, but I can't think of one, or like a cool stat or something that I can put into this post.
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And so I'll frequently type up a post.
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I'll put it in the chat, GPT, or Claude, and I'll say, hey, can you find like a...
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a stat, or can you word this better?
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Because I can't, you know, I can explain the concept, but I can't get the words out the way that I want.
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And so it'll help me put my sentences and my paragraphs better together.
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I mean, it's not AI generated.
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It's my thoughts and my ideas, but kind of put together in a more cohesive and structured way than what I would be able to do.
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And I don't think that's the same as AI-generated content.
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Somebody going to LinkedIn and say, write me a post about the future of SpaceX.
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Copy, paste.
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Now, I think for years, writing something decent about your field was a real signal.
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I mean, I try to do this on a regular basis through my newsletter, futureofworknewsletter.com.
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I try to do this on LinkedIn, through my social channels.
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It costs time.
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It makes you have to actually understand something.
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You have to be involved in a particular field.
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And that's why it worked, because it was really hard to fake this kind of information.
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And now the cost went to almost nothing.
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And anybody can do it.
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This is going to be a workplace problem.
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And it's going to come for you faster than you think.
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Because think about what your organization uses to evaluate people.
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It uses the polished presentation that you might make, the well-written strategy memo, the client proposal, the thoughtful email, the one-pager, the PDF, client deliverables.
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Anything that you put together is usually a very good proxy
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for what an organization uses to evaluate you.
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That's how your leader might say, oh, Jacob is so sharp.
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His arguments are so cogent and cohesive, and he really knows his stuff.
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Every one of these things can now be generated by AI with no particular insight on my behalf in about 90 seconds.
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So managers are already, I think, sitting in reviews, looking at work that appears to be excellent and quietly wondering, what are they actually reading here?
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Is this human or not?
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I've shared many stories from professors, from companies where people are seemingly submitting AI-generated work.
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It looks amazing and fantastic, but then when it comes time to having an in-person discussion about it, they fall apart.
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So I think this is coming into the workplace as well.
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This is why I think the concept of human prompting is so crucial.
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Human prompting is the idea of, and I have a whole post on this on Substack, pulling out the human insights, discernment, the decision-making from your employees.
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because you have to assume that everyone is using AI.
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So how do you get the human insights out of them?
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That's exactly what human prompting is.
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So even though LinkedIn is making this change first, it's going to come to your company.
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I can promise you it's going to come to your company.
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They're going to want to know what insights are yours and what insights are not.
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You might see situations where certain work that you do, you're not allowed to use AI for it, or you're going to be pressure tested.
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You're going to be human prompted on these things.
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This is coming.
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Because in a world where everybody's using these AI tools, how do you stand out?
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So the polish is going to be free.
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The presentation is going to be free.
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The aura of intelligence and wisdom, all that stuff is going to be free.
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What's going to be scarce now is the person.
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It's going to be the human aspect of work.
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So that is my show for today.
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Thank you for tuning in, for watching, and for listening.
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Remember to subscribe to the show if you are interested in more content just like this.
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And the CHRO group is futureofworkleaders.com.
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Thank you, and I will be back tomorrow.
