Everyday AI Podcast – An AI and ChatGPT Podcast - EP 258: Will AI Take Our Jobs? Our answer might surprise you.

Episode Date: April 25, 2024

To celebrate our 1 year anniversary, we're going to take a step back to where it all began with episode one and answer the hard-hitting question that no one wants to talk about when it comes to AI and job displacement. Will AI take our jobs? Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AI and jobsRelated Episodes:Ep 222: The Dispersion of AI Jobs Across the U.S. – Why it mattersEP 1: Will AI Take Your Job?Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTimestamps:02:00 Housekeeping items05:00 Will AI take your job?11:10 Generative AI advancing fast, concerns, hope remain.15:46 2/3 jobs exposed to AI, 300M at risk.23:26 False information spread by self-proclaimed influencers.26:36 Smart people build AI, youth teach, AI superior.36:26 Being creative involves processing past creativity for new ideas.40:03 Generative AI now affordable, powerful, and reliable.47:48 Facts presented: AI interest increasing in companies.51:09 AI not always linked to increased employment.58:14 OpenAI and Microsoft invest $100B in AI.59:33 Smart software automates tasks with specialized models.01:08:51 Workers are leaving big companies to start their own businesses due to AI.01:09:45 Generative AI reshapes business and products.01:16:40 Check out today's newsletter and enter giveaway.Topics Covered in This Episode:1. Current state of Artificial Intelligence 2. AI's impact on employment3. Future of AI and jobs4. The economics of AI5. Misconceptions surrounding AI and jobs6. AI in public and corporate view7. Preparing for AI integration and job transpositionsKeywords:Generative AI, AI affordability, AI accessibility, AI reliability, AI job impact, company layoffs, job automation, S&P 500, AI mentions in earnings calls, AI industry agents, OpenAI, Anthropic, Google, MetaLama, Cognition Labs, DeepMind, AI and knowledge work, domain-specific AI models, human intelligence and AI, AI democratization, AI exposure in jobs, AI impact on economy, AI and businSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

This is the Everyday AI Show, the Everyday Podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live in Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. It's the question that so many people are thinking about, but so few people are having a serious

discussion about this question. Will AI take our jobs? Well, the answer is yes, but the answer is much more complicated than that. I actually one year ago to this day had our first episode of Everyday AI. And I asked the same question. So today, to celebrate our one year anniversary of Everyday AI, we're going to be asking and answering the same question with new updates, more receipts, more research, and more information for you to still learn,

from generative AI and how you can use generative AI to grow your company and to grow your career. So what's going on, y'all? My name's Jordan Wilson. I'm the host of Everyday AI. We're a daily live stream podcast and free daily newsletter helping everyday people like you and me, not just learn generative AI, but how we can all actually leverage it to grow our companies and to grow our careers. So if you're here every day, if you're a regular, thank you for your support.

Can you believe it's been a year? Wild, right? I'm curious. How many episodes have you all been a part of? I've been a part of every single one. But I'm always curious. If you're listening on the podcast, there's going to be a lot of information in today's show notes. So always make sure to check that out for more. So we're going to get into it. We're going to get into this. And I want you to know a couple of things before we get started. Okay. I've interviewed some of the leading experts in the world about AI over the past year. I personally trained thousands of business leaders. And I don't want this to be a doom and gloom episode. But I'm also not going to lie to you, right? I do believe that's one of the reasons why this everyday AI thing has grown a little bit. It's thanks to you. But it's also because I bring receipts.

I bring facts. And I don't lie to you. So I know it's going to be a hard truth. I might, you know, lose some of you all from this episode. That's okay. But I'd rather stick here and speak the actual truth to you because it's important, right? Our careers are at stake. Our, you know, companies are at stake.

It is that important, right? But again, there's optimism here. Don't worry. We're going to get to it. All right. So if you haven't already, make sure to go to your everyday AI. sign up for that free daily newsletter and something something fun so normally we go over the AI news we're not going to do that today that's all going to be in the newsletter don't worry but

hey to celebrate our one year anniversary for all of you guys thank you so we are giving away some meta ray band smart glasses so they actually just uh you know introduce a whole lot of new AI powered features in the glasses so make sure to check out the daily newsletter today all you have to do is refer at least one friend to enter the giveaway. And we have a lot of other prizes as well. So I actually said this. I said, hey, if 10 people repost this episode, you know, I have some more giveaway items in mind.

So if this is helpful at the end, please repost this episode. All right. Also, I do want to know from our live stream audience, right? Yes, this is a podcast, but it's also a live stream. So I'm curious whether it's your first time here, you've been here for a while. How do you feel about this AI and job situation? Do you feel like, A, it's not at all a threat. You know, AI isn't a threat.

Our jobs aren't going to be taken. B, you know, do you feel, ah, not really. Maybe AI is going to take a few jobs, right? So the question is, do you feel AI will take our jobs? So A, not at all. AI isn't a threat. B, not really. Maybe it'll take a few.

C, quite a few jobs will be lost. Or D, AI will disrupt many jobs, right? Another thing that I'd like to do, I love interacting with you all, but I'd like to get take the pulse of people who are following generative AI and to see what they think, right? So please let me know as we go on here. So let's get this thing started. And hey, thank you all. Thank you all for your support.

You know, Carolyn's just saying bring it. Juan, saying congrats. Thank you. Dr. Harvey Castro, been around since day one. I love it. Michael's joining us on YouTube. Rob, first time watching live, long time post-live viewer. Cool.

All right, well, let's get into this. I'm not going to drag you on. And just we're going to get straight, straight to it. Yes, AI is going to take so many jobs. We're going to break it down. We're going to show you all the studies, all the facts, all the screenshots, all the receipts. But to answer the question, yes. I'm not going to make you wait around 20, 30, 40, 50 minutes to get the end answer.

The end answer is, yes, AI is going to take so many jobs. Unfortunately, it is going to have a net negative impact on the job market. And I'll tell you more about that in the long run. Yes, AI is going to create millions of new jobs that don't exist today. No, it will not be the same or more than the jobs that currently exist. And we're going to take a more historical look at that here in a second. But that's the end goal. If you don't need anything else, yes, AI is going to take a lot of jobs.

it is going to take away more jobs than it does create. And it is the new way to work, right? So even if this is your first time, or maybe you're listening to this podcast and you haven't really used generative AI before. All right. Well, I'll say this. Do you use the internet for your job? Do you Google things?

All right. And I'm guessing if you're a knowledge worker, like probably so many of us are, right? If you sit in front of a computer for most of the day and you're paid for your knowledge, your expertise, you will be using generative AI daily, hourly, minutely, is minutely a word, minutely if you aren't already. All right. So just get that. Even if your company is still, you know, on the fence, one foot in, one foot out, you're

going to be using generative AI every single day, every single hour, every single minute if you're not already. All right. So I also don't want you to all think of AI as a threat, even though in theory it is, right? You think, oh, is this friend or foe? You need to be able to work with AI. All right. So, again, it's, I'm not sitting here rooting for AI just because I have a daily podcast.

I'm not. I don't want this to happen. I don't want there to be a net negative impact on jobs, especially here in the U.S., right? I should, I should definitely denote that, you know, most of my vision. vantage point. I'm from Chicago. So most of my vantage point here is talking about this situation here in the U.S. That's what I spend every single day talking to experts about reading, about writing, about researching about is the impact of generative AI here in the U.S. on the economy, on our companies, on our careers. All right. So it's going to take a lot of jobs.

But let me first explain my vantage point because I'm sure there are a lot of you people here tuning in for the first time, whether it's on the podcast or the live stream. I'm not going to get into my background too much, but I'll tell you this, right? I've been working, you know, full time in different MARTEC communications roles for more than 20 years, right? I've been getting paid to write professionally since I was 17. I started working full time as a teenager at my daily newspaper. So I'll tell you this. I'm not some bushy-eyed, 22-year-old who doesn't really know how the world works. I've been lucky enough to work with some of the largest brands in the world.

You know, Nike, Jordan brand spent a very long time partnering with them. You know, I have a digital strategy agency for the last five years. I've been lucky enough to work with, you know, Fortune 500 companies, Inc. 5,000 companies. So I don't come to you as someone that's not experienced. right? I also don't come to you as someone that doesn't care on the on the on the on the latter end of their career, right? I don't I don't want to tell you how close I am to 40, but I'm pretty close. But what I'm telling you is this. I have enough experience, you know, in my professional career, I think, to have a valid opinion on this. Like I told you guys, I've talked to, you know,

probably 150 guests on the everyday AI show over the past year. Literally. the brightest minds in the world when it comes to generative AI, leaders from Microsoft, IBM, Nvidia, you know, everyday startups, like everyday people, but I've talked to some of the smartest people. And I always talk to people before and after the show, too. And there's things, you know, they don't want to say out loud, right? And I don't repeat those things.

But I do have a collection, you know, going to all these conferences, being able to meet, you know, people building the future of work. I have a lot over the past year, thousands of hours, conversations with very smart people. That's my vantage point. Again, I'm not rooting for AI just because I have a daily media company covering it. That's not the case here, right? My background, actually, you know, I spent nine years working in a nonprofit. I generally care about people, right?

That's honestly, that's one of the reasons why I started everyday AI. You know, about 30 minutes ago, I re-listened to that very first episode. I said I did this episode exactly one year ago to the day. And a lot of those same reasons hold true today. I care about people, right? And I feel, you know, whether you want to say lucky enough or unlucky enough, but I feel I'm in a position with my background. You know, I've used hundreds of AI products, you know, dating back to about four-ish years ago.

You know, our team's been using the GPT technology since it came out in 2020. since it was publicly available through third-party tools like copy AI, Jarvis at the time. I feel that I'm in a very unique position to be able to hopefully help people. And that's ultimately what I want to do. That's what everyday AI is. It is to help everyday people because AI is coming at us fast. Genitive AI is coming at us fast and it's not all good, unfortunately. And, you know, I noticed about two years ago, right, I said our team had been using the GPT technology.

I wanted to learn a lot of other things outside of that technology. So I looked everywhere and I couldn't find anything. Everything, like it felt like you had to have like five PhDs in different types of machine learning just to understand what people were saying or what people were writing about. So this is for you. This is for all of us, right? Because I feel, I feel if you are learning every day, I feel if you're putting the things that you learn into practice, we're going to be okay. We're going to be okay. All right. So that's, that's my vantage point.

So now let's talk facts. All right. Let's talk facts. And, you know, hey, if you are, if you are joining us live, thank you all. If you do have questions, I'm going to try to get to the questions, you know, like Rob saying, is there an E in that poll? No, no, Rob, there's not. You got to pick one of those. But if you do have questions, I'll try to tackle some at the end. I might, I might not have time. I might go a little long. But let's talk facts here, y'all. All right. So when we talk about will AI take our jobs? Again, my first career, I didn't even get into this. I was an investigative reporter.

You know, I reported on a lot of different things, but I spent the majority of my career covering things like sports and politics. But I was always investigating. All right. So we're going to go over facts. We're going to go over receipts. I don't make these claims lightly when I say, yes, AI is going to take your jobs, all of our jobs.

And yes, it's going to take away more than it will create. All right. So I've talked about this study a couple of times, McKinsey Digital. So, and we're all going to have this in the newsletter if you want to read more. If you're like, oh, this Jordan guy seems weird. It doesn't seem like he's, you know, knows what he's talking about. He's making stuff up. No, I'm not.

So a little excerpt here from a McKenzie, McKinsey Digital study. And this one's a little old, so it should be getting updated here, hopefully in a year. So it says current generative AI in other technologies have the potential to automate work activities that absorb 60 to 70% of employees' time today. All right. And also, this study was updated because previously they said 50. And then they were like, oh, wow, wait, this whole generative AI thing is pretty big, right? And if you don't know, McKinsey is one of the largest consulting companies in the world.

So they have many people who just study this. So they were like, oh, wait, when we said 50%, we were actually wrong. This generative AI thing is actually pretty good. It's actually 60 to 70%. Whoops. No, it's not. This is also, if I'm being honest, this is false. It's much, much, much, much higher than 70%.

My best estimate is probably 80 to 85%. Yes, 80 to 85%. We're going to talk about that more here in a bit. But think, if you are a knowledge worker, if you are getting paid for your expertise, you are sitting in front of a computer, you are reading, you are analyzing, you are writing, you are creating, which is what most of us do. McKinsey says 60 to 70% of that can be automated with generative AI. That's an understatement.

Okay, but facts. More facts. So this is both from the World Economic Forum and the International Monetary Fund. So you might be saying, all right, Jordan, yeah, some consulting company in the U.S., not a big deal. All right, well, what about when we talk about worldwide in the impact of AI on jobs? All right. So again, the World Economic Forum and the International Monetary Fund both referenced this.

And here's what they said. They said in advanced economies like the U.S., about 60% of jobs are exposed to AI due to the prevalence of cognitive task-oriented jobs. Okay? Knowledge work. So what they're saying here is 60% of jobs have the exposure to being displaced. buy AI. More receipts. More receipts. You need more facts. We got more facts. Goldman Sachs, Goldman Sachs, regardless of what you think of them, right? One of the largest financial institutions in the world. Some of the smartest financial analysts and researchers on the planets.

So here's what they said. And this is a quote here. So we find that roughly two-thirds of current jobs are exposed to some degree of AI automobes. and that generative AI could substitute up to one-fourth of current work. Extrapolating our estimates globally suggests that generative AI could expose the equivalent of 300 million full-time jobs to automation. All right. So that's looking at a global perspective, but 300 million jobs could be exposed to AI, right? And I've read all these studies and, you know, you do have to pay attention to the words, you know, exposed to AI is essentially saying,

hey, we don't know if all these jobs, if these 300 million jobs are going to disappear, but these 300 million jobs have exposure to be replaced or displaced. All right. And also, we're going to have more in the newsletter, but so many people talk about, oh, okay, well, this is just how the world works.

No, it's not. No, it's not. I wish this was just how the world works. This is not generative AI, and we're going to get to the difference between AI and generative AI, but generative AI is not like the internet. It is not like the cloud. It is not like mobile, right? We think of these big innovations. It is not like the PC. It is not like that at all. Those things change the way that we share intelligence. Generative AI is changing how we create intelligence.

And it is creating intelligence on its own. Yeah, I know you don't believe me, but I brought the receipts. So let's talk about more AI and job loss. Guess what? It's already been happening. Yeah, it's already been happening. Have you seen this? Have you noticed it?

All right? If you follow everyday AI, you've noticed it because we share about it every day when this happens. But again, if you're new here, let's take a look. So IBM was one of the first large companies that explicitly stated job loss or not hiring for roles because of AI. And stick around for later in the show because we're going to see if that paid off for them. They were one of the first. So IBM announced 7,800 jobs wouldn't be filled due to AI.

Google, all right, Google laid off hundreds in its sales team with a C-suite officer, citing the quote unquote profound moment we're in with AI as a reason. And this was earlier this year. All right. So now we're in 2024, right? We're three and a half months in. UPS announced 12,000 jobs would be cut due to advancements in AI in January of this year. SIP, you know, one of the largest software companies in the world announced plans to restructure 8,000 roles in 2024 due to AI.

Cisco just announced 4,000 employees would be laid off to focus on AI in 2024. Google CEO literally is warning employees about layoffs in 2024 due to AI, even though they have record profit. Adobe just introduced an entirely new way to create, bringing the power and precision of its creative suite into one conversational experience. Meet Firefly AI Assistant, now live in the Adobe Firefly app, the All In One Creative AI Studio. Powered by Adobe's creative agent, Firefly AI Assistant lets you start with your vision, just describe what you want, and shape the outcome as it takes form with the Assistant. The Assistant orchestrates multi-step workflows, drawing on 60-plus pro-grade tools across Adobe

Creative Cloud apps, including Photoshop, Illustrator, Premier, Lightroom Express, and more to help bring your ideas to life. You can also get started with creative skills, a growing library of pre-built workflows for common creative tasks, like batch editing photos, creating mood boards, portrait retouching, and creating social variations. Every step the assistant takes is visible, so you can refine, redirect, or take over at any time.

You stay in the driver's seat as the creative director. Adobe Firefly AI assistant now in public beta. See it today at Firefly. dot adobe.com. Instacart cut nearly 2,000 jobs, saying it needs to focus on AI in 2024. Coinbase, right?

If you're worried about, these small tech companies, future tech companies, they're just growing. No, they're not. Look at these three. Coinbase laid off 20% of its workforce in 2024,

saying AI will automate those tasks. And anthropic. Yeah. You've heard of anthropic. It just, off 20% of its workforce in January of this year, citing a need to focus more on AI safety. Right. So even these companies generating record profits are cutting jobs.

And really, IBM was the first, but now we've seen this slew of companies, almost like it's in vogue now. And we're going to get to that. We have some original research today, y'all, which I'm excited to share with you. It's almost in vogue now in 2024 to say that you're cutting. jobs due to AI because before almost no one was talking about it, right? It was almost like taboo to say, ah, yeah, we're, we're cutting jobs. You know, we're laying off 2,000 people because of AI or, hey, normally we'd hire these 5,000 people, but, you know, that's going to go off to AI, so we're not going to hire

them. It was taboo in 2023 to talk about that. There's a trend. There's a trend. We're going to get to that. But now, in 2024, companies are understanding. that it actually pays to lay off employees and say it's because of AI. Yeah.

We're going to get to that more. All right, so maybe you don't believe in facts and trends. Maybe you hear and read and see things on the Internet that you believe in, and you're like, all right, this Jordan guy's crazy. He really needs to stop talking about AI every day. He's becoming a robot. this AI information is swarming his brain. No, it's not.

No, it's not. I like to fancy myself a somewhat critical thinker. I like to talk with people who don't believe anything I say, so I can understand their point of view as well. So let's tackle some misinformation on AI's impact on jobs, because I think we have eight or nine things here that we're going to go through. Common misconceptions, because I'm telling you right now, you are not going to get the benefit.

And I'm not saying the benefit of this show like it's something fancy, right? But you are not going to get the benefit of generative AI. You are really going to put yourself, your company, at a tremendous disservice if you do not fully embrace generative AI. If you have one of these mental blocks, if you are believing some of these things that are straight up misinformation or straight up not true. And so many of these thoughts, ideas and misconceptions misconceptions are. so popular that you see them in the mainstream media. But they're all false. All of them are false.

It's not Tuesday, but we got a couple hot takes coming. And hey, live stream audience. Live stream audience, right? Denise joining us saying it is creating its own intelligence. Douglas joining us saying Jenny Eye is creating itself, yes. Let me know about these misconceptions. Are you seeing these? Are you hearing these?

What are your thoughts on them? I'm going to go through later. You know, might finish this today, might finish it tomorrow over the weekend. I'm going to, if you're joining on LinkedIn, I'm going to answer every single comment and question out there. So now's the time. Normally we have guests that do this. I'm going to do this, all right? So let's tackle the misinformation on AI's impact on jobs.

Number one, this phrase should be banned. And you've probably listened to it. And you've probably thought, oh, that's smart. And you've probably spread this message throughout your company. Okay. Someone saying this on social media. AI won't take your job. Someone using AI will take your job, right?

Couldn't be more false. Couldn't be more false. You know what? I'm going to put this in the newsletter. This is a tactic that quote-unquote influencers, I call them Billy Boy. these 22-year-olds that live in their mom's basement that used to be crypto experts. And then they were NFT experts. And then they just converted their audience to AI.

And they're all in these engagement pods. So when they write this on LinkedIn, it goes viral. And small business owners, people who work at Fortune 500 companies maybe don't know any better. And they see this and they think, oh, okay, well, my company doesn't need AI, right? Or I don't need AI. Because, hey, as long as I'm using AI, my company is safe. My job's safe. Couldn't be further from the truth.

This is a bunch of rubbish, a bunch of malarkey. All right. Let me tell you something. AI is not a one-to-one replacement. Right? It's not like if you're using AI or your department's not using AI, one person is going to come in there and say, okay, okay, Bill, you're not using AI.

I am using AI. I am using AI. I'm great at it. So I'm going to take your job now. No, that one person who is great at AI is going to take over 10 jobs eventually, right? And that department of 50 becomes a department of five. And then what happens with those five? Well, those five then are going to, in theory, become better. They're going to be building stronger generative AI processes.

The models are going to get smarter and smarter. The five become three, you know, and then the three work on agents. And then they work on agents that are completely automating all of these tasks that the 50 used to do. Again, y'all, this isn't gloom and doom. This is where the world is heading. Whether we like it or not, I don't necessarily like it. I personally like to type and pound on the keyboard and sometimes do things manually. It makes me feel alive, right?

But that's not the way the world is heading. So if you see that, again, this is a tactic. Go search for this on Twitter. There's thousands of people who say this every week, and they're all in these engagement pods and these posts go viral all the time to make you believe it and then they sell you some crap. Stop believing it. If you see this, never listen to that person again because they don't understand. Ask that same person.

What was the last time you read benchmarking reports from large language models? When was the last time you read a research paper on generative AI? They don't do that. That's what I do. Luckily, you know, my wife's pretty cool. and I'm like, hey, I'm going to spend all weekend, you know, reading these, you know, new prompt engineering papers. And she's like, yeah, that's good.

All right. That's what I do. I come here with facts. All right. Number two, big piece of misinformation when it comes to AI and jobs. People say, AI cannot perform at a human level. Yes, it can. It absolutely can.

People always screenshot something online and they're like, oh, look, chat GPT stinks. No, you stink at using. it. All right. The problem is you have the smartest people in the world building generative AI, but then you have, yeah, these 20-year-olds trying to teach you. All right. No one's actually learning. But here, if you want to know, is AI better than humans? Yeah, it absolutely is. We've far achieved what's called, you know, artificial narrow intelligence. And we are very close to artificial general intelligence, right? So what that means, when we talk about AI, AI's not new.

We're going to get into that in a second. When we talk about generative AI, technically not new, but, you know, the smartest people in the world kind of say chat GPT was the kind of quote unquote official start of generative AI, even though it's technically not, but people just like to say that's the, you know, BC AD moment, right? That's the line in the sand. But we've already achieved this concept of, hey, AI. is smarter than humans in every single tasks, right?

Every single task. So we've already achieved this, you know, artificial narrow intelligence where, hey, the best writer in the world, AI is better. I've won national writing awards. I won ACP store of the year. I want a Pulitzer fellowship. ChatGPT is a way better writer than me, but you have to know how to use it. Any single task that involves knowledge work in front of a computer, I'm sorry,

AI is better than you at that one task. Is AI yet at that point when we talk about AGI and agents, you know, so artificial to general intelligence, that's when essentially when an AI system across a variety of tasks can perform better than the best human at all of these tasks, regardless of the task. We're not there yet, but we're very close, right? I partnered with Invidia. I think that was last month. Got to go to some closed-door sessions, right? And the Nvidia CEO, who I think is probably one of the smartest people in the world when it's,

comes to AI essentially said, yeah, we're less than five years out from, from AGI, from artificial general intelligence, right? And don't think either, because I think people have this misconception of AGI that that means Terminator robots. Could it mean that? Yes, does it mean that? No, that just means a single AI system across no matter that the task of the field when it comes to knowledge work, the AI will be better than the best human in all of those areas. I think we're very close. I think we're a lot closer than people want to admit than they want to talk about. But that's the reality. So you can choose to live in the reality,

or you can choose to say, oh, I'm better at AI at this. No, you're not. No, you're not. The thing is, with large language models, they're actually not the best for every single use case, right? They're essentially, if you know what you're doing, you know,

they're B plus at literally everything, which is scary, right? So once it becomes A, right? Once it gets an A grade at everything, then that's when, oh, well, we probably achieved AGI at that point. and the AI is, you know, self-aware, right? We're not there yet.

We're very close. However, let's say you're a data analysis, right? Data analyst. AI is better than you at your job in limited scopes if you know how to work the system. Let's say you're coder, developer. AI is better than you. It's faster. It's better every single time.

Say you're a creative writer. AI is better than you. Okay. accountant at certain tasks, AI is better than you. At certain tasks, a certain AI system fine-tuned or built or trained or tweaked to perform a certain task is better than you at that task every single day out of the week if you know what you're doing. But most people don't understand that.

Misconception number three, AI will only affect low-skilled jobs. Nope. Wrong. Recent studies say the exact opposite. They say one of the most at-risk positions is college graduate. it's making $80,000 a year or more. Those highly, you know, quote unquote, highly paid, highly skilled workers that companies are paying a lot for for their knowledge, for their expertise. Guess what?

When you can turn that knowledge and expertise into data, when you can turn it into training documents and then build a model around that, all of a sudden, the thing that we've been paying a lot of money for for many decades becomes commoditized. That's okay. You have to become okay with that. But advanced misgenerative AI affect both low and high-skilled jobs. So, yeah, we're talking about legal, medical, creative. All these sectors are technically a rick, technically exposed, right? We talked about all of these reports, the Goldman Sachs report. We talked about the World Economic Forum report, the McKinsey report.

It is the jobs of not just low-skilled, right? We're not, I think when people think about AI, they think, you know, oh, we're going to have all these robots now working in factories and not humans, but I don't work in a factory. No, well, that's probably going to be happening. But it is knowledge workers. If you are someone, I cannot emphasize this enough, if you are someone that sits in front of a computer and gets paid for your knowledge of expertise, whether you are fresh out of college or you've been in a field for 10, 15, 20 years, why does that company pay you? Yes, there's obviously. You have to be able to navigate corporate culture. You have to be good interpersonally.

You have to have soft skills. You have to be a great communicator. But at the end of the day, one of the reasons they pay you is you have a certain level of knowledge and expertise in a certain domain. Right. You are a highly skilled worker with experience. You have this brain full of knowledge. Guess what? Smart companies are creating domain specific models.

and they are paying people like you, whether you know this or not, go look, go look in your field. Go look in your field. There's someone out there that's raised tens of millions, hundreds of millions of dollars to build a large language model specifically in that field. And they are paying people like you to go in there and train their models. So if you think that knowledge in your head, if you think that 10, 15, 20, 25 years of experience, if you think you're special, someone out there that's actually smarter than you is getting paid right now, decent money, to go train a model specifically for that task or skill that you think

is so special. None of us are special anymore, right? It was great for 50, 60, 70 years. We got paid great money to be specialized and to have a knowledge in something. I'm not saying that's going to go away tomorrow. That's not what I'm saying here. But it is going to become commoditized sooner rather than later. The writing is already on the wall whether you want to read it or not. That's up to you. All right. And a lot of these, a lot of these recent studies have actually showed that skilled jobs and developed economies may be the most heavily impacted. Okay. Number four. So this is our list of bad information that's out there regarding AI and job loss. But people saying human intelligence, creativity, and empathy can't be replicated by AI. Yeah, they can.

Yeah, they can. Oh, you want facts? Those are the three, those are the three areas. People always say, oh, well, AI can't do this, this, this, and this. No, you don't understand AI. Right. Yeah, I can't. All right. Ready? Human intelligence. People say, oh, you know, large language model, generative AI. All it is, it's just, it's just regurgitating what other, what knowledge is already out there. Nope. No, it's not. It is creating its own intelligence, right? So we talked about this on the show before, but as an example, Google Fun Search, which is a specifically trained large language model from Google. It solved a decades-old math problem that literally you had countless mathematicians and scientists spending their careers to try to solve this math problem. They couldn't do it. Google built a large language model that solved it. So if you think that large language models cannot create intelligence, if you think they just regurgitate, if you think they are simply next token predictors, then you're wrong, right?

That's like saying Michael Jordan was just, you know, someone that sat on the bench at an NBA game. Okay, yeah, he did. Yeah, he was on the bench a lot, right? Resting or if there's a blowout. So both of those things can be true. Michael Jordan can just be a player that sits on the bench, but he can also be the greatest player ever. So if you think generative AI is simply next token prediction, and it's just regurgitating information,

kind of accurate, but it is also out there being the goat. It has been the greatest of all time. It is already creating new intelligence and smashing records. your thought or, you know, it's your call if you want to understand things or not. All right, so that's human intelligence. What about creativity? Well, a university of Montana study published showed that AI tested in the top 1% for original creative thinking. And this was a blind test based on thousands of college students, top 1%.

It seems pretty creative to me. you can train a model to be creative, to think creatively. Guess what creativity is? Whether you want to think so or not, you are acting as a large language model when you are being creative. You are thinking about every single creative thing that you've ever seen. And you are thinking, okay, how can I connect all of these dots and come up with a creative idea, creative strategy for my company, for my career, et cetera?

That's all you're doing is you are processing things in the past that have been creative. or you are processing where creativity has not existed yet. But your brain is processing information that already exists when you are creating new creativity. That's what models do. Do you want to argue with science and math and stats? You can. Empathy.

So a very famous study showed that chat GPT was 9.8 times. So 9x more empathetic than doctors when it came to bedside manner. and they were testing for empathy. So if you think AI cannot create its own intelligence, you're wrong. If you think AI cannot be creative, you're wrong. If you think AI cannot be empathetic, you're wrong. It's not me. That's facts.

Number five, AI has been around for decades and hasn't disrupted jobs. Yeah, this one's funny. People are like, oh, AI, yeah, I'm not going to worry about that. That's like the boy who cried wolf. We've heard this before. Yeah, AI's been around since the 50s, right? people say, ah, AI is nothing new. AI is not going to disrupt anything wrong, right?

So, yes, traditional AI, deep learning, machine learning, neural networks had been around and they've been used in certain niches and verticals for many decades, right? An easy one is in the financial sector. So you've had kind of these deep learning algorithms being used to, you know, detect, identity theft or to detect fraud for many decades. So people say, oh, AI's been around for decades. I'm not worried about it now. Well, maybe you should because there's a difference.

Generative AI is completely different because if you were a company or an individual that wanted to use AI in the 80s, good luck. It was super expensive. And it's very few people could actually build or use the technology, let alone make any use case of it. It was for very specific use cases in niche verticals. Yes, it was used all over, but it was very specific, very expensive, very limited. That's not what AI is now. When we talk about generative AI, generative AI is affordable. It's accessible. It's reliable if you know what you're doing. This is, I think, the first time in human history that the difference between the biggest companies in the

world with the best technology and the everyday person that has nothing, right? It used to be worlds of difference between capabilities, tool sets, tech stacks, not anymore, right? Not anymore. Some of the biggest companies in the world. I know. Hey, we even just had someone from a public company on the show yesterday from Lonsa Tech. They based their model, right, which they're getting great results off of.

they base their model off of GPT, which anyone can go have that for $20 a month. You got to pay for the pro version or the chat GPT plus, right? But the biggest companies in the world that are getting the most out of generative AI right now are using the same technology that's available to all of us for a mere $20 a month. That's it. That has never happened in the history of humankind. So generative AI for the first time is affordable, accessible, and reliable.

And right now, we are hitting a sweet spot. We are hitting a sweet spot of compute capabilities and cost. All right. What that means, AI is more powerful than ever. It is more capable than ever. And it is more affordable than ever. So we are in a sweet spot. And 2024 is going to be wild, right?

I think that's one of the reasons why you've seen, especially in the early part of 2024, we went over, right? We bought receipts. But that's why we've seen these big companies being like, yeah, we're going to lay off 5,000 jobs. And we're fine saying it's because of AI. Because these big companies realized about a year and a half ago, oh, yeah, our knowledge workers that were paying a lot of money and we're hiring tens of thousands of them a year, we can stop doing that. We can start investing in our own internal systems, right? We can start investing in creating our own language models based off of this domain-specific knowledge and

expertise that is RIP. All right. Number six, this one's fun. Jobs historically evolved and shift, but AI is just a part of that, right? People say, hey, it is human nature that jobs just change. And hey, this new AI thing, it's going to be the same, right? Yes, there's periods of ups and downs when it comes to, you know, as an example, unemployment in the U.S.

And people say sectors change, jobs change. That's true. It's true, right? It's why we don't have, you know, the same number of, you know, switchboard operators and farmers and, you know, industrial factory workers that we did 60 years ago. So people say AI is going to be the same as that. They're just saying, oh, no, all the jobs are just going to change. Nope, not true. Because AI's scale and speed of change are unprecedented.

Let's even look at the example of switchboard operators, right? I think this is an interesting one. it took 30 plus years for companies at large to phase out switchboard operators, even when it was widely understood that there was better technology, right? So call centers, automated customer service, VoIP, right? All of these things, even with all these things, it still took 30 plus years to kind of quote unquote phase out. But they came out with a similar number of roles, right?

Switchboard operators versus, you know, let's just call it, customer service, similar amount of roles, and it took decades, right? So I'm not picking on these sectors or lines of work, but think of that now for data entry. It's not going to take 30 years to phase out data entry roles. It's going to take a year or two. Customer service, right? Very smart CEOs have said, yeah, customer service, for the most part, it's going to be

AI pretty soon, which if I'm being honest, might be better. Sorry. It might be. Right? Pretty soon. Customer service, content writing, all the coding, right? All of these types of jobs. And there's been reports on that.

We're going to share in the newsletter that. I'm not here to list, you know, 500 stats and facts. But all of these types of jobs are going to largely be replaced or impacted by generative AI in a year or two. not 30 years. That's the thing. AI is made to automate automation. AI is made to eventually replace the need for humans. Whereas previous changes, right, like as an example, you know, phasing out or transitioning

out of the industrial revolution or whatever you want to say, the dot com, right? If you look at these major eras in the, you know, the U.S. economic history, it is kind of changing A for B, right? Changing B for C. It's not like that anymore. The future of where we are, we are training AI systems to take the place of humans. It stinks to say that, but that's the reality. Yeah, I got more receipts.

Don't worry. Don't worry. All right, seven, AI will create more jobs than it takes. No, it won't. Not even close. Will AI create millions of new jobs? Yes. Will it create new industries?

Yes. Will it create new sectors that we didn't even think today can exist? Yes, of course. It'll create probably tens of millions of new jobs, new roles, new sectors, new industries. Yes. It's not one to one. It's not one to one. AI will have a net negative impact on employment.

It will. Right? Because AI, like I said, it's built in the way to, automate knowledge work, which is the main skill that humans have. When we talk about the internet, the internet wasn't built to replace the main skill that humans get paid for in their jobs. That is specifically the intent and purpose of these AI systems. We're going to talk about agents here in a second.

All of the money right now, billions of dollars is going to the companies who are trying to replace the value. of a human in a job. I hate saying it. That's the truth. All right. Also, AI is automating the creation, curation, and dissemination of knowledge. That part's important, right?

I wrote that down. I'm like, wait, that's pretty good. Let me say it again. AI is automating the creation of knowledge. It's automating the curation of knowledge. And it's automating the dissemination of knowledge, all things that in general humans do in different domains. and verticals.

Reskilling and upskilling will take decades. So if you think, oh, yeah, you know, next year, there's going to be, you know, five million new jobs are going to be gone. And these five million new roles that didn't exist are going to exist now. No. Reskilling and upskilling will take decades, largely because the current U.S.

higher education system is failing in training the workforce of tomorrow. Also, let's be honest, CEOs and Wall Street don't want humans working. Yeah, which takes us to our last point here. Companies will prioritize ethics and deploy AI responsibly to protect their workers. No, they won't, right? That's PR, right? That's marketing, companies, you know, especially these big public companies that say, oh, yes, we care about ethical AI deployment.

We are going to use AI responsibly. We are going to protect our workers. No, they're not. They're protecting shareholders. They're protecting their CEO who wants to go from making 20 million this year to 22 million next year. And if that means laying off 11,000 humans, then that's what they'll do. All right, ready? More receipts, y'all?

Yeah, probably didn't like that one. That one probably hit. Right? This Jordan guy's a jerk. No, I'm not. I'm just presenting the facts. Ready? We have more receipts and some original research.

I'm excited about this one. So I was just talking about will companies, will CEOs, will C-suite, will board members, want humans or do they want AI? Well, here I'm sharing a chart here on the screen here on the live stream. So again, if you're listening on the podcast, I know this is a long episode, but you can come back and watch this. But this chart here is tracking the number of S&P 500 companies mentioning AI during quarterly earnings calls. And obviously, it is now skyrocketing. Companies that before were like, ah, you know, we're not going to touch this AI thing.

Everyone is talking AI. It's literally like, have you ever had a conversation with someone? And you're like, this person is just spitting out a bunch of buzzwords. That's what public companies are now doing on their quarterly earnings calls. They're just saying AI, generative AI, agents, agents, agents, agents, AI, AI, data, large language models, data, right? They're just spinning things out because here's why. This is, yeah, little original research here. So this is also a graph from fact set.

Again, we'll have this in the newsletter. All right. So this is tracking the number of references in quarter four, 2023. So I know quarter one just wrapped up here. You know, we're in April 24 right now. But this is tracking for the last full quarter. This probably graph should be updated here soon. The number of times certain companies have mentioned AI on their earnings calls, right?

So, Nvidia, a lot. Microsoft, meta, right? Like all these companies that we all know and love. Guess what, y'all? Guess what? I went through and I looked at their year to date. I'm like, okay, if they were just pushing out AI, everything, AI, everything, AI, everything, are these companies growing?

Well, over this time, the Dow average here in the U.S. went up 2%. Look at how much these companies. The companies that are mentioning AI the most, in theory, are probably implementing AI the most. Side note. But also, all of these companies, Nvidia, up 65% year today. Salesforce, 8%, cadence, design, 6%, alphabet.

which is Google 15% Microsoft 10% meta 43% HPE 20% Broadcom 16%. I don't even know with this one. Arista, sorry, my screenshots a little blurry. 10%. The companies that are mentioning AI the most are outperforming the rest of the market. So guess what? Companies are saying, oh, wow. We're crushing it.

We keep talking about AI, so then we have to do AI. And then we make more money. And then we outperform everyone else. Our competitors that aren't talking about AI. They're not focusing on AI. They're not implementing AI. Guess what? These companies, as you'll see in a second here, these are the companies also laying off the most people.

Coincidence? No. Talk about AI, invest in AI, lay employees off profit. But that doesn't make sense, right? Because you think, okay, if you mention AI, that means you make more money and then you hire more people, right? No. Not the case at all. Not the case at all. All right. So this data here I'm showing on the screen. This is from layoffs.f y.i. So I'll link to that. But do have a little bit of original research here in the right-hand column.

So this is the 20 biggest layoffs over the past. I believe this is about 18 months. Okay. Because I wanted to have a little bit of context here, right? Because if you've lay someone off like there's some big Tesla layoffs like two days ago, you know, that hasn't played out yet in their in their stock price, right? So these are some of the biggest layoffs. So the 20 companies with the single biggest layoffs. So you have your biggest companies, right? A lot of them that were just on this chart, meta, Google, Microsoft, Amazon, Cisco,

SAP, right? IBM, we talked about them. So here's some of the original research. I went and looked at, okay, for these companies, these public companies with the biggest layoffs? Are they making more money now? You know, whether the, the layoff was three months ago or 18 months ago? Is this a direct correlation? Yes, right? We have the one-year stock price. So out of these 20 companies, 16 of them, their stock has gone up a lot of times significantly. All right. So even the average there with all these companies, 20 biggest companies,

Yes, four of them didn't make more money, you know, over the past year. But an average 72% increase, right? And then I have the other major indexes at the same time. You might be saying, okay, well, that's just all the stock market. No, yeah, the S&P's been crushing it up 23%. Dow Jones, 14%, NASDAQ, 8%. But here's what this means. You lay off thousands of employees.

You are rewarded. Wall Street hates employees. Sorry. You can't argue with facts, did you? I didn't cherry pick two. I went through. I've spent dozens of hours over the past year. Literally, just getting information ready for this episode.

Because I knew I'd be doing one like this again. There you go. The more people you lay off, the more you talk about AI, the more you implement AI, especially in big companies, the more money you make. It is not a coincidence that many of these companies that make up the top 20 layoffs in the past 18 months for U.S. public companies. It is no coincidence that many of these companies in here have individually invested billions or tens of billions into AI, generative AI, large language models. It's not a coincidence.

Sorry, y'all. All right. Let's go back and look. at IBM, right? One example, because they were the first, I believe they were the first major company that explicitly said. They said it in August of 2023. They were one of the first companies that explicitly said, yes,

we are not hiring these 8,000 roles because of AI. So a couple hours ago, they just released their quarterly earnings. Guess what? Quarter one of 2023 and quarter one of 2024. Revenue was the same. How's that work? if you decrease your headcount by thousands and you say, oh, nope, these jobs are going to AI. You're making the same amount of money.

But look at the stock price. My gosh, 46% increase, even though revenue is stagnant. Why? You cut headcount. You invest in AI. You talk about AI. You make more money. And what happens, these big public companies, they set the tone for everyone else, right?

That's why I've always said, I don't know why. I've always said like, hey, the end of 20, 24 is going to be bad, right? I do think that's going to be when the rest of the business world, right? This is, you know, some of the biggest companies, I'd say this is like Fortune 100 companies that have been, you know, working on this behind the scenes for the last, you know, maybe two years, this process of investing in AI, reducing headcount and implementing AI has been happening. But now the rest of the world is going to start following suit.

And what does that mean? Jobs. I'm sorry. Y'all, I don't want this to happen more than probably anyone else wants this to happen. But these are facts. These are stats. These are trends. So you can either look at the writing on the wall and do something about it, or you can cover your eyes and say, I'm special.

And the world's not changing. It's up to you. All right. So the biggest companies are investing hundreds of billions of dollars in AI and laying off hundreds of thousands, which makes people uneasy about the future. So I'm going to put my futures hat on. All right. This should be fun. And I know this has been a long episode.

I'm going to try to go a little quickly here to wrap things up. Let me put my futurist hat on because that's what you care about, right? Today is the worst that generative AI will ever be. So number one, the real chat GPT moment hasn't happened. So even, you know, InVIDIA CEOs, you know, says generative AI was chat GPT. And people talk about the chat GPT moment. I'll say this. The chat GPT moment of generative AI hasn't happened yet.

I do think GPT5, whenever it is released, will blow away every other model. And just like the kind of release of chat GPT did for generative AI, I do think the next iteration of GPT5 will do that same thing for generative AI all over again and be much more impactful. That's just what I think. That part's my personal opinion, right? But presumably this next version of GBT, which Open AI has been the leader in this space by far. Their old models are benchmarking and outperforming models that have cost billions of dollars from companies like Google, Amazon, Anthropic, etc.

Open AI is still outpunching its weight, even though its model is very old. The next version is going to be better at reasoning. It's going to be multimodal input and output. It's going to act and behave in a way similar to a human, right? Or you can talk to it. You can give it a photo. You can give it a video. And it can give you anything on the outside, right, or in the output.

Agents, we haven't really talked about agents. Agents are going to be huge, right? I don't cover them because I say up until maybe three months ago, agents weren't that good. Now they're getting good. You know, and agents, if you're new here, are essentially pieces of AI software that are literally built and you can, you know, train them and you essentially click around on the website and you say, here's what I do. And then it does it for you. Performs all those tasks for you.

Okay. 100 billion dollar Stargate project between Microsoft and Open AI investing in infrastructure. That's huge, right? So reportedly, Open AI is working on agents, GPT. They have this huge $100 billion infrastructure project with Microsoft to create more compute, you know, reportedly Sam Altman is looking to raise $7 trillion. So this Open AI CEO is reportedly looking to raise $7 trillion to create more compute that powers all these generative AI systems. Nvidia's new chip, right? The Blackwell, impressively powerful.

They already have the most powerful GPU, which powers all this generative AI. So the future is, I don't think our big, quote unquote, generative AI moment has happened yet. Yeah, I don't think it has. I think it's going to be happening real soon. Number two, as we look in the future, programmable expert agents are coming quickly. Yeah, agents. Here's why. And I like to think of it as this.

If you're an old school dork, you probably know RPA robotic process automation. So I think of this as agents as RPA meets large language models, meet subject matter experts. Or in other words, a smart software that automates tasks on your computer across multiple platforms. Combine that with domain-specific large-language models, more powerful ones, and combine that with what I think has already been the big trend of 2024, which is tying in domain-specific information into large-language models, right, through things like RAG, you know, retrieval augmented generation or fine-tuning models, right? So it's combining the

best models out there with your company's IP, with your company's data. So combine that, with essentially these agents, so, you know, RPA, and that's, that's another big thing. We've got to keep an eye on. So Open AI has reportedly been working on agents. Anthropic has announced agents. Google, just two weeks ago, announced agents in their vertex AI agent builder. Matta Lama, Mata's Lama 3, agents just announced. Cognition Labs, Devin, already in a limited release, getting pretty impressive results.

Langchain, even though I don't think Langchain was very useful when it first came out. It's getting better. Agents, they have general release. DeepMind from Google, working on agents. In other words, the biggest company with the most monies. Two years ago, it was the shift towards large language models. Now the shift is going to be toward agents.

We're going to be talking about it a lot here on the everyday AI show. Number three, as we look forward in the future, Your expertise becomes your AI. What that means is employees will be charged with collecting first party data and company data. Yeah, that's going to be a whole new sector. Companies, you know, think of like, you know, L&D. I think L&D becomes LLM. It becomes collecting first party data.

It becomes, you know, essentially unloading the smartest people, which this is like a bittersweet thing. But there's, you know, there's kind of like, quote unquote, side gigs out there, a lot of them for domain specific models. that people are building in different fields. And they're essentially just saying, hey, all you experts out there with 20 years of experience, come in, we'll pay, I don't know, $50, $100 an hour. And you essentially give us your brain. And we're going to put that brain as domain-specific experience in our large language model.

And then everyone in your category, well, we're not going to need as many of you anymore. Right. So I think employees at individual companies will be charged with doing this internally. I think this is going to, you know, when we talk about current roles that don't exist inside companies. I think that's one of them. You're going to have huge teams of companies that are essentially taking your companies, your businesses IP, turning it into data, collecting the data, cleaning the data. AI agents are going to help with that process, obviously, right? You know, just talked with someone on the show yesterday. They said they have

30,000 pages of their IP tied into their model. That's what's happening in 2024. And now all these tasks that used to take, oh, this used to take seven days. Now it can be done in three hours. Okay. Your expertise, your company's expertise is going to become your AI. So we're going to be talking a lot about, you know, rag and fine-tuning models, turning your company IP or your individual skill sets into data for a large language model.

But I also think it's going to, it's going to come down to the individual level. Think of how much customization you can have like on the home screen of your smartphone. Now think, and I don't know if this is three months or three years, that's what it's going to be like to work in the future? You're going to have a very customized version of many different domain-specific, fine-tuned LLM agents, generative AI softwares, all very specific for the type of work that you do. Okay. So we're going to wrap up here, y'all. Will AI take our jobs? Yes. Many, many of them. There's no way around it. Follow the money. Follow the trends. Follow the stats, follow the facts.

And there's no other conclusion that can be made. Again, y'all, I need to re-emphasize this. I'm not rooting for AI to take jobs. I don't want that to happen. That's weird. It's a world none of us know. It's a world that none of us are probably comfortable living in. That's the reality.

So what do we do? It's like, okay, great, Jordan. I'm still listening an hour and four minutes into this podcast. Now I feel like crap. Thanks, man. No, it's okay. here's what we should do. So how do you survive in an AI world?

Well, don't run from AI. Is it your enemy? Technically, make it your friend. Keep your friends close and your enemies closer. We all need to learn how to coexist with AIs, maybe even AIs that are built and specifically trained to replace our role. You need to become comfortable working, using, getting the most out of it. All right?

I do think late 2024 is when the rest of the world, the rest of the business world is finally going to catch on. I showed you that chart of the top 20 companies in the biggest layoffs, the biggest layoffs in public companies here in the U.S. over the last 18 months, 20 of them. And I looked at their stock. They're all making more money now. Obviously, public companies know this. And they're saying, how can we follow this blueprint? This is going to happen, whether we like it or not.

So one thing that Sam Altman, whatever your thoughts are on him, he's one of the smartest people in the world when it comes to AI, right? There's a handful of them. He's one of them. He said for a year, one of his biggest concerns about, you know, the GPD technology or generative AI or large language models is disinformation and economic shock. The economic shock is coming. I think we're going to see some crazy ups and downs here in the U.S. economy. And I do think that there's going to be growing momentum around universal basic income. income. UBI, right? Because job displacement is real. That's not my opinion. I showed you guys the facts.

You know, McKinsey Digital, 60 to 70 percent, the World Economic Forum, you know, up to 60 percent of jobs in advanced economies are going to be exposed. The 300 million jobs globally figure, okay? It's happening. So how do we survive? We unlearn, unlearn good behaviors. I know that's weird, right? A lot of people have this mentality in business. We need to keep doing things the way we've always done them because that has led to success. That will be to failure, right? If your company has not fully gone on, gone all in on AI, if you still have one foot in, one foot out, if you're on the fence, or maybe you haven't dipped in at all.

If you continue to do things the way you've always been done just because they've led to good results, you're going to go out of business. I don't care. If you're an eight-figure company, if you don't. adopt to generative AI, the seven-figure company, that small one, maybe you've never heard of, they're going to squash you. They're going to be using it. They're going to be doing it the right way. They're going to squash you.

Also, you need to know that knowledge workers and subject matter experts will have limited importance in the future. That's what large language models with your company's data are for. That's weird. Right? even myself, right? Companies pay me because, you know, for my digital strategy expert, my marketing, technology, comms, it's not going to matter much anymore, right? It's not.

Sorry. I've come to that realization. It's hard. It's not going to matter as much. I'm not saying, hey, next year, your 30 years of experience in this field are worthless. No, you're not worthless. They will be worth less. They'll still be valuable, but not.

valuable because guess what? People who are just as smart as you are training models with all of that information. So that information, that domain specific expertise, those highly valuable skills of today are going to become less valuable tomorrow. Highly specific knowledge is going to become commoditized. You have to be okay with that if you want to succeed in an AI world. All right. Here's some hot takes. I think the rise of, you know, this kind of like gig economy that we've seen over the past decade, it's going to 10x easily because what's going to happen is all of these displaced workers,

something that people don't talk about, right? We talked about all these biggest companies, right? Amazon, 36,000, meta, 21,000 layoffs over the past year and a half, Google, 12,000, Microsoft, 11,000, right? Guess what's going to happen? I've talked to, even in the past couple of months, I've talked to, even in the past couple of months, I've talked to about five or six people who work at some of the biggest companies in the world, and they've talked about this.

They say, this is all off the record with them. I'm not naming them my names, but they're like, hey, my company, we're creating AI. These jobs are going to be different. So I'm starting my own thing. Right. So many people, I think, are going to be starting their own thing. Right. Right now, let's just say, you have a group of, you know, 20 friends in the room and you say,

hey, how many of you have your own business or side hustle? I don't know, maybe two or three, depending on, you know, I mean, if you're running in entrepreneurship circles, it's probably more hands. let's just say on the average. I don't know, maybe two or three hands go up. I think in five years, it's going to be the majority of people. I don't know how that's going to work with, you know, insurance and benefits and retirement. I don't know.

But I think that's the reality. I think so many people are going to have, you know, multiple part-time jobs, multiple side gigs. They're going to own multiple businesses because, hey, this is something Sam Altman said. He said, hey, I can see a single person business, you know, making millions or billions of dollars. and that's actually a reality because generative AI completely rebuilds the playing field.

We're not saying it evens it. It rebuilds what it means to play in business and compete in business. I think we're going to see hyper-targeted products and services, right? To where instead of, you know, if let's just use movies as an example, right? We talk about SORA and all these,

you know, very powerful AI models in their videos. You know, instead of, you know, let's just say, oh, 10 new movies coming out, on Netflix this weekend and maybe one or two appeal to you, I think you're going to see 10,000. And they're highly targeted, highly specific toward you. Right. You're going to see all these things like, wow, this looks like it was made just for me.

Well, it's because AI is going to make it easier to do that. Also, I think one of the best things that we can do if we are knowledge workers, right, if we're getting paid for our experience and do something in front of a computer, is shift our mindset to not be domain-specific, skilled specialists, but to be adaptive AI generalists, right? That's what we need to be. I think of it like a language, right? Let's say you were studying a foreign language, right?

And you're like, all right, I'm going to learn Spanish, and I'm going to go deep on Spanish, and I'm going to be a Spanish expert, let's just say, right? Instead, you need to learn the basics of 50 languages because that's what I feel the future of jobs are going to look like, right? And my biggest background is kind of in marketing and communications. So you might have had a team of PR people, a team of internal comms people, a team of internal creatives.

I don't think that's how that's going to work anymore. You're going to have, you know, hey, here's your team of people setting up your company's data. Here's the team of people deploying and building your agents. Here's the group of people who are actually building the creative with help of the agents. But they need to know everything. You need to know the PR, you need to know the communications, you need to know the design,

you need to know the UI, UX. You need to know a little bit of everything and understand how AI, how generative AI, how large language models, how agents impact all of those things. Again, for the human existence, we've all been trained and we've been rewarded to become experts and extremely skilled in one very specific field. I don't see that working three, four, ten years into the field. I don't see that, at least not at the same level. They're still going to be experts, absolutely.

But think, all of these models are being trained specifically for that. If the smartest people in marketing and technology and communication are getting paid to give their knowledge away to these companies that are raising billions of dollars to essentially create agents or to create models that would do all the work of those skilled people, is it as valuable to have those skills anymore? I don't think so. So that's what we need to do. and the most important thing, always be learning.

Right? When we talk about AI and jobs, I just laid out a lot of facts, a lot of receipts, a lot of stats. You probably feel a little weird right now. I feel a little weird saying all this. But this is the reality. And I know that this is the absolute worst, most generic, most cliche thing you can say, always be learning. What advice should, what should we be doing, right? It's like, that's lame.

you'd just spent, you know, an hour plus laying out this scenario that doesn't feel great. How do we, right? I gave you what I think you should be doing. But ultimately, what you need to be doing is you always need to be learning. Okay. Not just in your field, but how AI is impacting your field. That's what you need to be spending your time on. Again, we've been rewarded for decades, right?

to keep learning in our specific field, you know, ongoing education and training in your specific field. Instead, you need to be looking at the applications for AI in your certain field. That's what you need to be spending your time on. Always be learning AI in your field. Always be practicing AI in your field, right? Because that's the only thing that I know come next week that is still going to be valuable, timeless information. Always be learning about AI in field, always be practicing AI in your field. And if your company has not already implemented generative AI into your day-to-day workflow, you need, if it's you in charge, hit me up. We'll help you. If it's someone else, you need to say, hey, why aren't we doing this yet? Right. So if you are

that person charged with implementing generative AI in your organization, and it hasn't been yet, you need to push. You need to push. Because if you don't, you're going to have a problem competing. All right. So that's it. That's a wrap, y'all. I know that's a lot.

Will AI take our jobs? Absolutely. Is the future a little clear and uncertain? Absolutely. But can you prepare? Yes. Do we all know what's coming? No.

But if you are always learning, If you are always practicing, you're going to be okay. And you know what? We're going to be doing that together. That is literally what we do here at everyday AI. We bring on experts. I know we haven't had a lot of guests over the last couple of weeks. I've been traveling, but we're going to have a great guest lineup next month

and the month after. I'm excited. But you can be learning every single day here. You can be practicing every single day here. We're going to be launching a free community soon. That's going to help that even more. So one year later, after one year of everyday AI, I think we set out what we wanted to do. We wanted to help everyday people.

People who didn't know what a neural network is. People who didn't know what a decision tree is. People who didn't understand tokenization. We wanted to simplify things for you. So you could feel more comfortable about growing your company and growing your career. And we are going to continue to do that. We're not saying, all right, one year we have. hit the finish line.

All right? Because in one year, stick with me every day. Stick with me every day. Learn from different experts. Keep learning with us. Keep practicing with us. Because when I have this same show, April 25th, 2025, will AI take our jobs? If you come and if you learn and if you practice every single day with us, you're going to be

in a lot better position today than you, in a year from now than you are today. All right, so keep joining us. And also check out today's newsletter. Yes, we are giving away not just meta, these new meta AI Raybans, which I think are really, really cool. But we have some other things. And like I said, if this was helpful, I know this was a long post. But hey, if this LinkedIn post gets to 10 repost, I have another thing, another giveaway that we're going to be doing. So all you need to do to enter this giveaway, again, if you're not already on our newsletter, you need to go to your everyday AI.com.

I put the link. If you're on the live stream, if you're listening on the podcast, the link is there to sign up, as always. All you need to do to enter our giveaway is refer one friend to our newsletter. That's it. So check today's newsletter. You're not going to miss it. It's going to be big and in your face.

All you got to do is click a button. You can get this link, your own unique link and share that with your friends. Put it on social media. Do you have a newsletter? Put it in your newsletter. So we'll explain it more. But whoever refers the most people gets their choice of our different kind of prizes. The meta rayban glasses are just one of them. There's going to be more. And if we get to

10 reposts, I think there will be another really cool one. But also, there's going to be three total winners. So one is going to be the person who wins the most. Then we're going to have two random people. So minimum, all you have to do to be eligible is refer one friend. So make sure you read today's newsletter, grab that link, share it with people. Also, I do have something special for every single person that refers at least one friend today. So this contest is going to run through Monday. So we're going to have about four days. But anyone who refers at least one friend successfully refers one friend today,

there's something a little special for you too. All right. So that's it. I hope even though this was kind of a Debbie Downer episode, I hope this at least gives you a little bit of optimism. It gives you a little bit of hope. What we do here at everyday AI, we're not here to, to put out these like AI won't take your job,

someone using AI will. Now, we're here to give you the truth. We're here to bring you the facts. We're here to bring you receipts. And we are here to learn and grow together. Thank you for joining us. We hope to see you back tomorrow and every day. For more everyday AI.

Thanks y'all. Meet Firefly AI assistant. Now live in Adobe Firefly, the Allman One Creative AI Studio. Just describe what you want to create in your own words and the assistant handles the rest, orchestrating multi-step workflows across Adobe Creative Cloud apps, including Photoshop, Premiere Express, and more in one conversational interface.

You direct the outcome while the assistant accelerates execution. Stand control with the ability to step in and refine at any time. See it today at firefly.adobie.com. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit Your Everyday AI.

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