I've Got Questions with Sinead Bovell - Is AI Impacting Jobs or Not? (The Automation Timeline)

Episode Date: June 9, 2026

Is AI’s impact on the job market overhyped? For the last two years, we’ve seen headline after headline warning about AI’s potential impact on jobs. And yet, when you look at the job market today, things still appear relatively stable. So if AI is going to reshape work, why hasn’t it shown up more dramatically yet? And when should we expect that to change? In the latest episode of I’ve Got Questions, we’re sharing a moment from Sinead’s recent interview on the Mighty Pursuit Podcast, where she explains the job market paradox: why we keep hearing about a looming “jobpocalypse,” while the labor market still looks mostly fine. Sinead also explores why the era of the 9-to-5 may be coming to a close, what the workforce could look like next, and the skills we should all be building now. Follow my work here: Website: https://www.sineadbovell.com Substack: https://sineadbovell.substack.com Instagram: / sineadbovell  LinkedIn: / sineadbovell  Twitter / X: / sineadbovell  YouTube: / sineadbovell  TikTok: / sineadbovell Watch the Mighty Pursuit Episode here: https://www.youtube.com/watch?v=tBiO8A4tj9I&t=952s

For the last two years, we've been hearing all about the impact artificial intelligence is going to have on the workforce. Yet when you look at the actual labor market, things look fine. The labor market looks really stable. In fact, in many job categories, we're actually seeing growth. What is happening? Is AI impacting jobs? Or is it not? For this week's episode of I've Got Questions, we wanted to bring you a moment from an interview I just did with the Mighty Pursuit podcast where we dive into this paradox.

Is artificial intelligence overhyped when it comes to the job market? And if not, when is its impact going to be felt? I also dive into the end of the 9 to 5 era and where the workforce could be going next. I'm Sinebeauvel and this is I've got questions. So I want you to imagine someone. Let's call her Sarah. She spent all of 2025 hearing that AI was going to wipe out jobs, the white-collar work, collapse, the entire industries would disappear. And so now it's 2026. She still has her job.

None of her friends have been replaced, at least not yet. And so her life mostly looks the same. And she's starting to wonder if it was all overhyped. What would you say to her? What would I say to Sarah? I would say that we are definitely overestimating the impact that we'll see with AI in jobs and change in the short run. So I think over the long term, a lot of the jobs that Sarah is hearing about in 2025, that will eventually go away or be radically transformed and become unrecognizable, that will be true. Over the 18-month or 24-month convenient timeline that also happens to coincide with a lot of funding cycles and raising cycles, probably not. We're starting to see some changes in the data with respect to labor and skill composition within workflows. But this idea, and I know I've heard the stats too, 50% of white

collar jobs could be obsolete by maybe now it's been pushed to 2027, 2028. That might not be the case over the short term. But over the long term, depending on what Sarah does, I would say that she could bet that her job will look really different or maybe not exist at all. That workflow might not make sense. When you say short term and long term, how do you define those? That's a great question. And I know the pendulum keeps swinging and moving. I would say short term for me is three years, which is interesting because that tends to be companies' longer term strategic plans, which is just tragic.

if you're thinking three years into the future and that's where it ends, you're probably going to get disrupted. In longer term, I would say, looking seven to ten years. And so there, the forecast seemed to be, and it's funny, the further out you go into the future, the less you can predict or see. But when it comes to these general purpose technologies that behave in a certain way, your estimates of change tend to be a little bit more, not accurate, but closer to the forecast. When you think about technology change throughout history, I mean seven to ten years is seven to ten years. still pretty short term. I mean, if you think about the fact that, I mean, however many thousands years of history it took to get to the internet in like the 1990s and then even from then to social media to now, I mean, seven to ten years is like not that long time. Well, I guess we could

count. I mean, AI has been around for a while, but if we could count from the end of 2022, where Tad GBT really came on the scene and then if we're looking 10 years from, now. So we're looking around 13 years in this latest era of transformers architecture lifespan. What type of change could we see? And it's not actually that unforeseeable. I mean, if you look at about 80 years, 60% of the occupations that exist today didn't exist 80 years ago. And if we're to go back to the industrial revolution, moving from agriculture to mechanized work and in the rise of factory labor, you're looking at about 70% of people doing something radically different over 100 years. So the question that's in front of us is what would that look like to have 70% of the population do something different, but not on an industrial scale or an industrial timeline, but closer to that 10 to 15 to 20 years. And that's where you could see it as alarm bells or maybe that's reassuring for a lot of people, but that's where the time scale tends to start making a little bit more sense.

So when you hear figures like Elon Musk and Sam Altman say that like AI is going to replace most jobs, do you feel like people should believe those sorts of statements? I would say it's what is the part two to that statement. So a lot of the different tech leaders will say, and there's different economists depending on where you fall, that sure, maybe a lot of, a lot of, of the jobs that they're currently building AI systems for could maybe be done by AI systems. And this would be specifically knowledge work. So things that are happening on a computer, maybe financial analysts or tax returns or paralegals, that type of role or roles that involves those types of tasks. So could those be wiped out? Potentially, that's at least what they're optimizing and building AI specifically to do. But that's where their forecast tend to end.

over and that is the end, all the best to everybody else. I see a part two to that, and depending on which economists you subscribe to, they would either agree or disagree, that when an input becomes more abundant, so in this case, it's going to be, we'll say intelligence, and we'll definitely use it in air quotes, the economy will reconfigure around that new resource becoming abundant. And it could reconfigure in really strange ways, the same way when communicating and distribution became free and abundant, aka the internet. People started to make money over pretending they were in a vehicle and they're not and they're filming a video about something and there's an entire new economy around that. So when intelligence becomes much cheaper, how does the

economy reconfigure? And then what do we do on the other side of that? We will do something. We'll probably work less. We'll probably work in very unrecognizable ways, even though what we're doing right now, what are we doing? Right? That's entirely unrecognizable. So it will still be like that, it will just be something different and something that doesn't necessarily resemble the knowledge economy. Those tasks will probably go to AI. But there's a lot of disagreement. There will be AI leaders that would push back on that and say, nope, it's done. And then the robots are here. I think there will be a part two. What do you mean that what we're doing is unrecognizable? I mean, how would you describe the work that you and I do? Or even the work of a brand manager

to somebody 150 years ago. That's a good point. Yeah. How would, what? would you say that that actually is. Somebody is helping to describe, well, what's a brand? Well, it's, you know, okay, so why is there somebody managing that? All of these jobs that we invented and towards more service and towards more knowledge work. So we moved from a world where work was or labor was defined by muscle. Now we're in a world where labor is defined in some ways by the cognitive capabilities you have. And we're moving to a world where work may be defined by and that's variable X. Yeah, we don't know. We don't know. Yeah, that's fascinating, really, as a thought experiment, if you go through that and think about if you explain to somebody in 1850, like, oh, we record, what do you mean record? Like, it's just like, yeah. We build Microsoft Excel sheets and we try to predict how much money people in a different country are going to have. Well, why would you do that? Like, all of these things that we've created don't necessarily make sense out of context. And that's why whatever comes next won't really make sense to us right now because the systems that, encompass it have truly not been invented. Now, in terms of the statements from these tech figures, so one of our recent guests was Bill Gurley, and he's like a legendary investor in Silicon Valley. Uber was the big thing then he got in early on. And so we were talking with him about like AI fear. And it's interesting because he's like an insider with I think benchmark capital. And he was just talking about how

these people hype their own products and services to raise more money. And so basically, in some ways, the thing that is like sparking fear ends up raising a ton of money because it's so hyped like we're going to build this thing. And then that leads. So do you feel like that reality is also accurate part of the picture? Sure. Yeah. There's definitely marketing and fundraising incentives that are driving some of the narrative. that we hear, and that isn't anything new. So yes, I think some of the narratives definitely come from,

we have a funding round coming up. The system we are particularly building can build and do all jobs in the knowledge economy. That's very profitable. And if an AI system can do that, that company is going to make a lot of money. So that makes a lot of sense. But I don't think it's entirely wrong, again, that AI will be able to do a significant portion of the jobs that some of the jobs that we see today. And even though I think there's going to be an economy, there will be an economy, how many people are in it and do those jobs, do the jobs of the future replace or are they actually geographically found in areas where in regions where jobs were lost? Those are all questions that we don't necessarily know the same way globalization change the composition of work and who we could say

more winners and more losers economically speaking. We might see strange patterns like that. But yes, again, the narrative of it's going to be able to do everything is a very profitable one. So if you follow those incentives, sir, you're going to make a little bit more money versus saying our AI can do a few tasks sometimes for a couple people, probably not going to raise much. Yeah, it's more nuanced. Now, if you look at the latest jobs reports in the U.S., this was, I think, January, but I don't know what it was at in February. But employment's still growing and unemployment is around levels that we've kind of seen for years. And parts of Europe, there's some softening, but nothing resembling a collapse. So on the surface, the labor market looks steady right now if you were just like read the news headlines.

So is that a misreading of the data or do you think we're just asking the wrong question entirely? No, I think, I mean, that is what the data does show that even some of the productivity numbers are quite misleading as well too. You'll hear productivity through the roof. It's incredible or we're not seeing anything. So I think some of that data is right. when you drill down, though, into hiring, so we're seeing some fewer job postings in certain areas. We're seeing the composition of skills within the jobs that companies are actually hiring for change. So maybe now you're, you were hiring for a financial analyst.

This person has to be able to do amazing with spreadsheets. And now if you're to actually drill down into how that post has changed or that job position has changed, it's you have to be able to direct and observe or apply jobs. judgment to different financial patterns. So something that's much more akin to directing or guiding AI systems over just building and crunching the numbers. So the composition of work has changed. And then that has a downstream impact because that might not be the same person. So the person who was best for the job posting in 2024 may no longer be a fit in 26. So those are interesting signals and kind of the level of the data that I would be going

into to show, okay, who companies are hiring for is starting to change. But this idea that it's, you know, everybody's going to be wiped out in a year that doesn't really, I'm not seeing that data either. But I also, it's one thing for the data to be overstated or for the data to, say, one set of numbers and AI companies to say something else. But policy still has an important role to play in between. And if AI companies are telling us what they're trying to to build, even though it doesn't show up in the numbers yet, I think policymakers would still be wise to have a plan in the event that it goes really well or not so well. And that's the gap that I'm really paying attention to, that you can't, just because you don't see it in the numbers,

it doesn't mean that you should sit back and enjoy the ride because that ride might be really bumpy. And that's where my concerns lie. I wouldn't consider myself an optimist or pessimist. I'm neither of those things. And just because I think there's going to be an economy on the other side that involves people, it doesn't mean that that transition is smooth, and it doesn't mean that it brings everyone if you don't intentionally design a system to do that. And that's where it's still been crickets from the policy crowd. I think this year, and over the next couple years, we'll start to see the rise of political campaigns totally centered around AI and not sovereign AI, national security, not that type of narrative, but what AI hopefully means for the person in the

economy. I think we're going to start to see it and to hear about it. Now, when you think about all these scenarios and the government preparing for them, do you see the moment that we're living in like right now in 2026 as the calm before the storm? Is that how you would paint her or you painted differently than that? As the calm before the storm? Sure. Yeah. Because if you are to zoom out into kind of a wider historical lens and measure something over the course of a century

or over the course of a few decades, change is coming. And it's not just AI that is headed towards us. There's then quantum behind it. And then there's synthetic biology and there's space. And AI is multiplying the speed of discovery and the speed of progress in all of those fields. So sure, yes, I would say that we could see this as the calm before. And it doesn't necessarily have to be a storm. But the calm before a period where we come out on the other side, whether that's in 5, 10, 15,

years and life starts to become very unrecognizable. But again, we've, we've been living unrecognizable lives. It's just likely going to compress. What I love about your work is you, I feel like you can, you help instill hope in people in very practical ways. And so whether, you know, your podcast and sub-sac, a lot of the things that you've been writing and talking about, I think it really helps people, like, prepare for that transition. So, like, of what the next 10 years are going to look like. And so, So if you were to focus, you called this the dawn of the independent era. And so can you explain a little bit about that and what you feel like is coming? Yeah. And of course, nobody can make predictions by the future, especially not a futurist. But what we can start to see in the data is the rise of more contract or independent based work as the dominant form of work in the market. So if you think about this from the perspective,

of a company. And we've even talked about it today. A financial analyst job today may look very different in 18 months. You still might need somebody to do different things, maybe direct a bunch of AI agents, but the skills are going to change. And maybe that workflow is entirely different again in 48 months. So I'm less likely, if I'm the CEO of a big company, to hire for that role as full time. I'm going to opt much for a shorter term contract, a year, 18 months. So when you think about that times a lot of the jobs in, and we can, you know, focus in the knowledge economy for now, we'll start to see the rise of much more independent-based work in the workforce. And that's kind of new for a lot of people. We do see the rise of much more,

I mean, you and I are both technically independent workers as it is. We do our own thing. But the dominant form of labor may start to look more like that, where instead of working for one company, doing one thing, you work for a few companies, doing the skills that you are endowed with are the skills that you have in the field that you work in. And that's a very different type of workforce because it means you become your own CEO, right? You are an organization of one and you apply your skills to a variety of different companies or projects. And so that's, I'd say, the rise of the independent era. And it's a very different future. It has many implications for things like health insurance and Social Security. Not everybody wants to be an independent

worker. There is a lot of comfort for some people. Some people, it's their nightmare, but for others, being able to have consistency, nine to five. But we should start to see the idea of a nine to five job for one company will be a chapter in human history. And that chapter is closing, for sure. I mean, that could bring a lot of anxiety for some. A lot of anxiety. For people of like, I mean, I know what it's like to like run. run a company and be an entrepreneur. I mean, we've been doing this for like eight years, but there's a lot of stuff that that goes into that.

And so I wouldn't say it does sort of require a particular type of person or at least a particular type of mindset to be able to endure because there's so much uncertainty. There's so much like, like if you're working for five different companies and you're a freelancer and one of those things drops, then 20% of your income goes out the window versus is I'm, they might be bored at work, but the safety net of, I have like $80,000 a year coming in. You can plan.

Yeah. Right? It becomes impossible to not know what is my income next year or the year after. But remember, things, variables don't change in isolation. So when the fabric of the workforce starts to shift, new business models, new types of platforms and infrastructure start to come into play that allow that to make more sense. So right now what we're probably doing is extrapolating, okay, everything stays the same. The only thing that changes about the world around me is that I now hold three different jobs for three different companies. And there are these massive gaps between new projects that we're going to work on and existing ones fading away. Other variables will start to change. But yeah, I mean, it is a very unsettling future for many that take that enjoy the security of a stable job. And I mean, it is something that I do try to call attention to on my platforms. If we can see this transition happening, something like Social Security and something like healthcare is going to become really important for people.

And even just having the ability to reach up and grab new skills or to be able to continuously pivot, that's an entirely different market. But it's one that we're starting to move towards. So my advice for people in this moment is don't think of your job in terms of the title that you hold. Think of the skills that you have under it. So be industry agnostic. be job title agnostic. What are the types of skills

that you're performing? Okay, so I exercise judgment when I do this. I use creative intelligence because I'm the person that always comes up with the ideas. Whatever it is that are the kind of skills that you occupy that you use

every single day, those are what you'll continue to apply just in different ways. And so maybe you'll be directing AI systems to do those tasks, but applying the expertise that you have and the role that you've been maybe holding for the last five years.

And that's how you start to look at it. So it's going to change, of course. I mean, and work has always changed, even the idea that a lot of people work from home. Like, that was so radical even a decade ago that a significant portion of people would opt for virtual work, or at least partial virtual work. So I think we can adjust to it. But do we have the infrastructure and play, the policy support, the entire different? Again, I've mentioned Social Security because I think it's really important and we don't have those safety nets. But, yeah, thinking of yourself as an organization that offers a bundle of skills.

to a variety of different projects, that's one way to think about the future and to think about skills over thinking about job titles, much more important. Now, I don't know if in terms of thinking about skills invalidates this entire question, but the idea of being a synthesizer

versus in like a generalist versus like a specialist in one sort of area, how would you think about that? Because, like, for example, if you have been working for the past 10 or 15 years and you've been doing this one sort of thing, right? Let's just say marketing. You're doing email marketing. And there's someone who might be a generalist. They might not be an expert in, like, an email marketing, but they might be doing seven different things across the means and marketing.

So they have, like, a way wider expertise. And also in some ways, I would probably say their risk is lower because they can pipe in and out of different things because they are like general and synthesized services. Everything isn't relying on them being in email marketing and them going, oh, like, I don't know how to do anything else. Do you feel like that aspect of the conversation is going to be relevant with AI? Like who is better positioned? The experts and the people with domain expertise or the generalists. Exactly. I don't think that we've netted out on if there's, if who wins what, where.

Because there's, so let's take that example. You're working in email marketing. And I think we could probably safely say that is something that AI is already doing. So going forward, that's, you know, if it hasn't already impacted your work, it's probably going to. Okay. So does that mean that the generalist comes in and scoops up all of those email marketing jobs? Hmm. If you look at the skills under email marketing, why is it that somebody clicks?

your emails over the other companies. And how did you think about adjusting those campaigns when it wasn't working? What was the psychology that went into how you structured those titles and where you placed images that allowed somebody to respond differently? How does that type of thinking happen in a world where AI is marketing the product and you're giving AI, the framing of your brand, the culture of the company, whatever it is that you're selling? So what were the underlying skills that went in front?

to you structuring that. And that's why it's so foreign for us to think about how we were thinking or how we are thinking. We just don't think about it that way. We just do the task. But what was the thinking that happened before that task and how you evaluated whether that was successful? That is what you were taking with you to the next thing. And that you're saying that's what's going to be valuable to a company potentially. It's the thinking under it. Yeah. So maybe you're not writing emails anymore because AI writes it better. But you are bringing the skill set in that people don't like to hear the number first. When you start with the price, even though it's an amazing sale, they don't want to hear it. Like, you're still bringing in those types of things. And this is why.

Or if you'll have better ideas, perhaps if you're thinking about it that way, than somebody that's just never in their life dealt with marketing. They can do some stuff, but you could outcompete them in certain areas if you're thinking about how you're thinking. And that's, of course, not just a universal thing that's going to apply across the board, but it can apply in many cases. So does that mean that someone wouldn't have to know email marketing at all? And that like because of AI and that it's helping with that, someone would be able to pipe into temporarily doing email marketing because they carry a set of skills? Wait, so I'm not sure I understand what you mean. So if someone's carrying this set of skills across like domains and across tasks and they're working with AI to accomplish those things, does that mean that their ability to know the ends and ounce of email marketing?

is less relevant. Okay, so I love that you ask that, because what you were essentially saying is you could have skills in one area and they actually become more applicable in another area. So the person that had amazing judgment skills, let's say, in finance or human resources may actually be the best person to run marketing in the AI first world because the types of skills that they were executing may actually work well in the types of decisions that they're making where AI is the dominant platform. So yes, it is possible that somebody, that the skills, and this is the, you know, to quote one of my previous professors, the skills that made you dominant before AI may not be the same skills after AI, right? So the email marketing person, based on the types of the decisions that they were making, if they can think about how they were thinking, they may be the best person to make judgment calls on hiring, right? So we're going to start to do different things. So that's why it's so much more important to think about the underlying skills of how you made decisions for not just, the simple task that you did, but how did you make the decision before that task? And we're not

taught to think about our thinking on that meta level, but it's really important. And that also expands the type of work you think you're capable of, because you might be limiting yourself to email marketing, but you could actually be the best person to make judgment calls on finance decisions because the AI is crunching all the numbers. You're making the judgment call. Do we go with market X or market Y? And market X is these types of people. And this type of group was very sensitive to price every time we engage with them on email. But this type of group never cared about the emails about price. And we're trying to target luxury.

Let's go after them. And that could be the email marketer. Well, yeah, I mean, I think it, in terms of further pain, because we said in the beginning of the conversation, the idea of envisioning a future world that doesn't exist. It almost feels like Chinese to a lot of people. So if we further paint that world, you've talked about like career ladders shrinking and that the shelf life of skills will shorten. And so the very idea of like a career might evolve.

And so like what does that, what does that mean exactly? Yeah. So I think we have spent the last few decades building up the idea of work where you learn, you work and then you retire. And that worked for a certain type of economy where skills and tasks were cumulative and pretty predictable. But in an era where AI and different technologies will continue to change the types of skills that we're going to need to bring to the table and how different types of work gets done and which types of products are interesting and our buying behavior,

that consistency of working vertically up a ladder starts to make less sense because in an era of skills over, say, job titles and sometimes even over experience, it doesn't necessarily matter if someone has worked five years or 15. If the person who's worked five years is continuing, they can learn different skills or how they apply their skills is more advantageous. So that career ladder starts to make less sense. And we're already starting to see some of it not entirely get pulled out, but junior hires not necessarily making us, we're seeing lower numbers of junior hires. And that, I think, is actually going to be temporary. I think we're going to start to see them funnel into different types of roles, like directing AI systems and AI agents.

And then that becomes, and that's actually quite interesting, right? If you take a legal firm, a partner is probably best to make the final judgment calls. Like, okay, we've been in this type of court scenario before. This is how this judge behaves. But the junior or the younger person that now is no longer on that paralegal ladder or whatever came first, but they're on the AI agent director ladder. They're, I don't know who's, they're pretty equally important in that firm because that legal company can no longer keep up if they aren't diffusing agents the way their competitors are. So that idea of the autonomy ladder and all of that, that starts to make less and less sense in a skills. over job title era.