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AI Isn't Causing Mass Layoffs—It's Being Scapegoated · In The Loop

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  In today's episode we're going to talk about something that's
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  been bugging me for days. It's the increasing gap between
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  revenue and jobs. As you may already know, some of
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  the biggest companies in the entire world in the past week
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  have let go of thousands of employees whilst reporting on
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  record profits. I felt the need to have a bit of
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  a nosy and chat your BT search and see what social media is
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  saying because something doesn't add up because Amazon and many
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  other companies have said this is all because of AI.
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  So yeah, I love history. I can already see big historical
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  analogies throughout time. And this question feels really
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  important to answer, whether we're truly seeing the impact of
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  AI in job losses or whether companies are using it as a
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  scapegoat. This is in the loop with Jack
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  Horton. I hope you enjoy the show.
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  Now, if we start with the main contradiction, so last week on
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  the 20th of October and Amazon announced 14,000 layoffs across
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  the company and the head of people experience in technology,
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  Amazon said basically we're at this new era of AI
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  transformation and we think we have to reorganize to be more
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  efficient and effective. For me, that's quite a clear
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  message. AI means fewer people.
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  However, two days later, the CEO, Andy Jassy had then said
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  that it's not to do with AI and that it's not financially
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  driven. And actually it's just a culture
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  change they're looking for. So you may be wondering which
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  one's the truth. Is it AI?
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  Is it not AI? What?
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  What's going on here? And that's the contradiction
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  that a lot of people on Twitter and a lot of people online drew
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  attention to. Now, here's where it gets quite
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  interesting because a very quick GPT search finds that over the
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  space of a few months, there's been a number of those
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  contradictions from Amazon. So this is what the CEO also
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  said in a memo just a few months ago.
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  He said as we roll out more generative AI and agent, it
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  should change the way our work is done.
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  We need fewer people doing some of the jobs that are being done
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  today and more people doing other types of jobs.
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  It's hard to know exactly where this Nets out over time, but in
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  the next few years we expect that that we will reduce our
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  overall headcount. So, you know, again, Due Memo
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  says we're going to cut people. Basically the head of people and
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  experience technology says we've cut people because of AI, and
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  the CEO says it's not actually AI are financially driven.
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  So yeah, there's a lot of contradictions going on.
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  But obviously at the same time, it's important to say that
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  Amazon's profits jumped 38%. So they're basically printing
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  money whilst also just laying off people up scale.
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  Now this isn't just Amazon. Meta also cut 600 job roles.
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  Applied Materials cut 1400 job roles and they all put it down
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  to automation and digitalization.
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  So yeah, there's there's a bunch of research I want to tell you
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  about that I found over the weekend that's really
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  interesting. But before we actually jump into
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  that, I think it's really important to understand why this
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  matters and why I'm so interested.
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  So First off, we've been here before and it didn't go very
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  well in the past. Now this isn't a politics
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  podcast, but if it were, I would ask us all to I guess reflect on
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  the state of politics right now with trade wars happening, with
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  partisan politics going on, with lots of anti immigration
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  headlines and narratives across the world.
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  And I guess what I want to chat about may shine a light on the
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  realities of technology, automation, and generally big
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  business in how it impacts everyday people.
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  So in 1979, US manufacturers employed 19.6 million people and
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  now today it's only 12.7 million.
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  So it's about 7 million job roles gone, which is a 35%
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  decline. That's huge.
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  That's entire communities almost vanishing.
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  But here's what's very important.
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  Manufacturing output during that same period increased 80%.
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  So with 7 million less people increased 80%.
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  Now these impacts are rarely just economic.
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  They end up being cultural. They end up impacting politics.
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  They increase mortality rates, drug problems in in communities
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  that often aren't that well off already.
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  And as I said, it's very easy to understand the impact of these
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  massive changes of, I guess automation in, you know, the
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  70's, the 80's, the 60s to what our world looks like today.
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  Now, if you look at what's happening today, the S&P 500
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  increased by 77% since 2022. Yeah, unemployment's gone up by
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  3 1/2%. So yeah, there's, there's a lot
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  of analogies that you can draw from automation of, you know,
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  the 80s and the 90s and the 70s to maybe what's happening now.
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  So it is a really important question of whether we
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  understand, is this because of AI and automation or is it just
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  being used as a scapegoat? I think it's a latter and I'll
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  explain why now through a lot of research this weekend.
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  There are typically 4 good questions we can ask ourselves
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  when trying to answer that question.
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  Now question one is, are these companies losing competitive
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  ground? So are they are they losing to
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  their big competitors? So let's take AWS as a good
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  example. So Microsoft is yours.
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  So the equivalent of Microsoft's main product that competes with
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  AWS is growing at 31% every year.
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  And 12% of that growth comes from just their AI services,
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  whereas AWS, so Amazon's AWS is growing at 17% every year.
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  That's a huge gap. You know, Microsoft clearly is
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  stealing huge market share right now.
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  And a big part of that is the fact that they've got massive
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  amounts of AI capabilities that are way out in front of AWS.
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  So when I look at the fact that Amazon have cut 14,000 corporate
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  jobs and the CEO says it's about culture, not AI.
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  For me, what I think is actually happening is their restriction
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  because they're losing the US is watching Microsoft Azure grow
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  twice as fast, specifically from AI services that Amazon just
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  doesn't have competitive parity with.
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  They over hired during the pandemic.
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  Amazon more than doubled its corporate staff during 2019 to
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  2022. And now they need to improve
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  margins while trying to catch up with Microsoft's AI
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  capabilities. And I think saying that you're
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  reorganising in an AI era sounds a lot more strategic and
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  exciting than we're getting battered by Microsoft.
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  So because we over hired and so we're going to try and fix all
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  these problems at once. Now both statements can be true.
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  AI can enable them to operate with fewer layers and fewer team
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  members. That restructuring probably will
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  help with some of the competitive pressure, but the
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  primary driver isn't AI, it's the fact that they're losing.
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  You could call this forward-looking theatre that
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  basically hides present pressures because it's not lying
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  exactly, it's choosing which truth to emphasize more to
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  everybody that's listening. And so another question we
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  should always ask ourselves when these big companies are making
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  these big claims is what's their revenue per employee?
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  So this is where you can start. You can kind of see real
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  productivity from them trying to spin PR.
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  So NVIDIA has a revenue per employee of 3.6 million.
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  Like yes, you heard that number right, Crazy number, which is up
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  to 76% in just a year. Apple has 2.38 million per
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  employee, Meta has 2.19 million per employee.
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  So these companies are generating ridiculous output,
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  economic output per person, whereas Amazon has $410,000
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  revenue per employee. Now, yes, they have a massive
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  warehouse operation that will probably pull a lot of those
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  numbers down, but that gap tells us something quite important
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  that the companies with the highest revenue per employee is
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  often where AI productivity gains are more real.
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  And I mean, we're seeing this first hand building mindset.
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  It is insane what happens when you build an entire process and
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  systems around AI, around accelerating the key things you
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  should be accelerating and having a process that has really
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  good human checks in it. We are going faster than we've
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  ever been able to go before. And I mean, we're kind of like
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  this AI particularly clawed at the moment.
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  It is a drug. It literally cannot take our
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  money fast enough because we use it so much across the business.
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  So yeah, if you're seeing companies with flat or declining
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  revenue per employee and they're then citing AI transformation as
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  the reason for layoffs, well, it's time to start asking
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  serious questions. Then if we go to question #3 is
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  what are they actually cutting? So Meta cut 600 AI roles and
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  I've you really think about it, especially what they did in the
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  news recently. Why would you cut so many
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  researchers or people if they're driving huge amount of return on
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  investment? And I think the probable reason
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  is that you have organizational bloat and you're tidying it up
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  because if you were doing really, really well in that
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  business unit, you'd be scaling the number of team members you
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  have, not cutting them. Because if you're cutting team
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  members that are apparently key to your transformation, then,
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  well, something doesn't add up. And if you contrast that with a
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  company that's doing really, really well, which is Microsoft,
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  they're not cutting AI teams. They're scaling them
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  aggressively. And I keep saying this over and
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  over and over again, as companies start winning with
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  their big bets in AI, they're going to hire more people for
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  more of those big bets, not less.
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  So yes, there will be some job cuts in some areas, but it'll go
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  through the roof in others. And finally, question 4.
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  It's really interesting if you then look at the statistics on
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  rehiring. So this one really shocked me,
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  to be honest, when I saw it. So a survey of over 1100
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  business leaders said that 39% of people made employees
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  redundant because of apparently excitability about AI
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  deployments. And of those, of those 39% of
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  1100 people, 55% have then admitted that they made the
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  wrong decisions about some of those redundancies.
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  So more than half of the people making those big redundancies
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  straight away regret it. See, I think a lot of companies
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  see the hype cycle, try the few things they think it's going to
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  work. They don't really focus on
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  reading and rebuilding process or culture around these tools.
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  They get so caught up in the hype cycle, they maybe see their
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  competitors talking about big AI transformation, and then they
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  made drastic workforce decisions before anything was really
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  embedded into the business. You saw this with Klarna.
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  They got rid of 700 customer support staff and then had to
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  reverse the decision. So yeah, what worries me about
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  all these big pieces of data, research, these questions is
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  that showing that people are making big workforce decisions
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  with very little information or experience and basing it too
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  much on hype. And I think the gap between
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  rhetoric and reality is just growing wider and wider and
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  wider. So yeah, I guess let's to
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  conclude, I think there are multiple stories here at the
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  Frontier. You've got the Microsoft, the
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  Nvidias, those type of AI native companies that are seeing huge
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  productivity gains and their revenue per employee numbers is
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  out of this world. Their margins are incredible and
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  they're investing more money into those business units.
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  But many other companies are just using this AI
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  transformation narrative as a complete scapegoat to escape the
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  fact that they're not adapting that well and they've not yet
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  launched truly effective AI products.
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  And letting people go because you need to increase margins or
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  and decrease cost or reorganize for certain big initiatives is
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  very fair business reasons. But don't lie and say it's
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  because of AI. And I think the numbers that are
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  really important to look out for is constant increase in company
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  profits, but decreasing employment in the economy,
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  because that usually spells the start of a period in which
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  corporate profits go through the roof and individual income
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  starts to collapse. Anyway, that's it for this week.
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  It was a quick episode. I hope you enjoyed it and I'll
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  see you next week.