EP 196: The Silent AI Productivity Killer - Why companies can't fully leverage AI

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There's one very specific reason that so many companies aren't fully leveraging generative AI. And it's a lot easier to solve than you might think. All right, we're going to be talking about that today and more on Everyday AI. What's going on, y'? All? My name is Jordan and I am the host of Everyday AI and this is for you. This is your daily livestream podcast and free daily newsletter helping everyday people like you and me learn and leverage generative AI. Yes, it is the new frontier. It is like if the Internet and computers all got rolled up into, you know, like a one month rollout period. So this is your spot to learn and leverage everything that you need to know. So let's, let's get into it. Let's just start right away. And let me tell you this, if you're listening on the podcast, thank you. Check your show notes. As always, we have related episodes, other great resources, and one of those greatest resources is our website. It's your everyday AI. So a lot of people don't know. Yes, we have an entire website. Every single episode we've done now nearing 200. We have recaps of all of those websites. You can go and learn anything you want to. So if you want to learn more about automation or content creation or entrepreneurship, whatever it is that you need more of to help you grow your company and to grow your career, we have dedicated podcasts. We might have 10 different podcasts on sales as an example on how to leverage AI and sales. So make sure you go to your everydayai.com, check that out as well as you can go read every single newsletter we've ever published. All right, so before we get into that silent, a silent AI productivity killer, we're going to tell you what it is, we're going to say it out loud, and we're going to break it down. But before we do, let's start as we do every single day, with going over the AI news. So, first and foremost, Yelp reviews are either going to get way better or way worse with AI. So Yelp is introducing a new feature that uses AI to summarize user reviews, as well as adding other features to their iOS app to improve search and content recommendations. So this new Yelp AI feature will use large language models to summarize user reviews and highlight a business's key features. The AI Summaries are currently only available for businesses in the restaurant, food and nightlife industries. All right, our next piece of AI news. A new partnership is seeking to bring safer AI to teens. So OpenAI announced a partnership with Common Sense Media to develop AI guidelines and education material for teens. This comes after so many concerns about the safety and responsible use of AI, including its potential to spread misinformation and affect human rights. Yeah, bad things. So this new partnership aims to ensure family friendly GPT branded language models and adhere to Common Senses standards. So this partnership could be the first step in us maybe eventually seeing rating systems for different AI models similarly to how we do with movies. You know, here in the US could we see a PG13 version of ChatGPT and A rated R version maybe? All right, last but not least, Chat GPT's paid model has competition now from Meta's updated Free model, at least when it comes to coding. So Meta has just released its updated AI model for CO generation called Codelama 70B, which is capable of handling more queries and achieving higher accuracy than previous versions. So this model is available for both research and commercial use. So Code Llama 70B is Meta's most advanced and powerful coding AI model with 70 billion parameters. And in benchmarking, this new model outperformed GPT 3.5, but fell just short of OpenAI's GPT 4. So pretty big news there. So yeah, if you're not, if you don't follow Meta's models, but essentially this is a fine tuned version of their large language model specifically for coding tasks and it's already performing extremely well. All right, I'll tell you this, it was pretty hard for me to decide the news this morning because there is so much. So make sure if you haven't already, to go to your everydayai.com and sign up for that free daily newsletter. Because we don't just recap the news, we don't just recap our conversation every day that we have here on the live stream. But there's actually so much more and we keep it to just important things that help you leverage generative AI to grow your company and to grow your career. So if you're new here, it's hot Take Tuesday, y'. All. So every Monday we give you the AI news that matters and on Tuesday we come up with a hot take. Something maybe a little controversial, but hey, let me know if you're joining us on the live stream. You know, like Tara, Tara's been first this week. I love it. So if you're joining us, like Tara or Josh, thanks for joining. Or Harvey or Brian. Appreciate y' all tuning in. And Val and Cecilia, let me know, how hot should we get today? How hot should we get, Megan? Megan says we should burn, baby, burn, right? Because I've got some takes here on this silent AI productivity killer. And like I said, it is so much simpler than it needs to be. The solution is simple. All right, so let me know. Here's the thing. I might offend some people here. I might, you know, because I'm gonna be. I'm not gonna be naming names here. Y' all, like, going back to my reporting days as an investigative journalist. I'll keep my sources disclosed, you know, keep them close to the vest. But I might. Might hurt some feelings here, right? All right, everyone. Everyone says hot, hot, hot. I'm still waiting for the day when someone says, take it easy, Jordan. All right, so we'll crank up the heat on today's hot take Tuesday. So here's what it is. We're going to skip to the end because people complain that I ramble on too much on my hot take Tuesdays. So here is the silent AI productivity killers. And this is why companies can't fully leverage AI. And it is so simple. It is a lack of training in education. All right, so before I get into it, and, you know, if you are listening on the podcast, we always have the link that you can come back and, you know, watch the live stream because I am going to be sharing, you know, some slides on the screen here. But before I get to some of these slides, I just want to talk high level. There's pressure right now. I get it. There's pressure. There's. There's pressure on, you know, know the, the big tech companies who are building the AI to build faster, right? You don't want to be the, you know, the, the, the new model that didn't score high enough or the new model that no one's using. You don't want that. So there's immense pressure on the big tech companies and the growing startups who are building the AI. There's pressure to just build, build, build. All right? And then there's pressure on companies, right? There's pressure on, you know, whether you're a, a large enterprise company, maybe you work in the consulting space, maybe you're a small business owner, but there's pressure on companies as well, because you see all of these, you know, case studies or stories, and, you know, it looks like just about everyone out there is sharing on how they're properly implementing generative AI. So. So it's almost like we get this hot case of fomo, right? Like, the fear of missing out, and you're like, man, it looks like everyone's just running and everyone's sprinting and everyone's so successful with generative AI implementation. So it's problematic. Right, because what's happening right now is everyone is sprinting. And this is the first time, I'd say, in modern business times that the technology is literally too fast for even the smartest people, the smartest companies, the most prepared enterprises. Everything is too fast for the rest of us to keep up. So education and training is a huge problem. But do I understand how that has been pushed to the wayside? Yeah, I kind of do. I kind of do. Because it seems like if you're spending too much time educating your, your staff, your employees, you might miss something. There's literally new, new updates, new groundbreaking features every single day. So I understand. Right. So there's probably going to be some people that get upset when I say, why aren't you training your employees? And they're saying, all right, Jordan, you don't understand. Things are happening too fast. I get that. But we are collectively, especially here in the US we are collectively dropping the ball. All right, so let's dive in a little bit here. And let me know. Let me know for our, our live stream here. Everyone joining us, Mike and Woozy and Ken. Thanks. Thanks for joining us live. What do you think? Let me know, yes or no? Or give me some details. Has your company done official and ongoing training on generative AI? Let me know. Or what questions do you have on the proper way? I'll try to tackle everything as we go along and try to tackle things at the end, too, if there's any questions. But let's start here. I need to say this out loud because sometimes I think smart people get too smart for their own good. Right. And we are trying to compare generative AI to previous business innovation. It's not like that. It's comparing apples and pumpkin pie. Right? Because so many people are, you know, have been now for, you know, the last two years when the, the generative AI wave has crashed ashore. So many people have been comparing generative AI to the Internet. And that is a ridiculous comparison. That is a ridiculous comparison. So right now, if you're a business leader, and that's what you're preaching, or if that is your mindset, get rid of that. That is a, A, a mindset for failure. All right, here's why companies had a decade plus 15 years to, to properly adapt to the Internet, right? Internet was, you know, popularized in, in businesses in the late 90s. You know, you had your, your dot com boom and everything was.com.com.com, right? And eventually the dot com mindset just became, this is how you work, right? I had a conversation with someone, you know, doing a consulting session with someone yesterday, and I have a conversation about this and about how smart people are maybe just getting a little too smart and they're saying, oh, you know, AI, it's going to follow, you know, the typical hype cycle. You know, it's, oh, now we're gonna, you know, go into this 18 month period of disillusionment. No, we're not. Just like the Internet. Slowly, over the course of 10 or 15 years became the new way that we do business. So, you know, now when we're talking about our company, we're, you know, we don't tell people, oh yeah, we're big on dot com. Oh yeah, yeah, yeah, we use the Internet, oh yeah, yeah, yeah, we're, we're connected to the cloud. No one talks like that anymore. If you're a fully functioning business, you've obviously been using the Internet in literally every aspect of your job from top to bottom. Everything. Data analytics, cloud syncing, etc. Buzzword.com that is the same thing with generative AI, all right? Whether you realize it or not. The same way that if you are a knowledge worker working in front of a computer, you obviously can't get through your day without being connected to the Internet essentially from beginning to end. The same thing will hold very true with generative AI. You will be using, whether you fully realize it or not, you will be using generative AI from the moment you start work until the moment you stop. But generative AI is not like the Internet at all. Again, that was a 15 year period that companies had the leisure to adapt at their own pace, right? To say, all right, let's investigate, let's wait and see. Generative AI is not like that, right? And I got stats today. I got stats, you know, I got facts. I brought my facts with me. Old journalists in me always brings the receipts, but I got hot takes too. So if you are still, or if your company is still on the fence and still hasn't fully implemented generative AI, your clock is ticking, y'. All. Your clock is ticking. And that's not a clock ticking of like, oh, your growth is going to be stunted. That is your company. That is your company. I, I'VE said this literally, probably the very first episode of Everyday AI. I said companies, they have 18 months, right? I don't care if you're a small business with 50 employees or a giant company with 50,000 employees. If you are fighting off AI still, generative AI at this point, you're going to be toast, period. You. Yeah, even 50,000, you know, companies with 50,000 employees, billion dollar companies, they will get either acquired, mergers are going to happen, or they're just going to get straight squashed. Because if you aren't using generative AI, all of your competitors are, and they're getting ridiculous gains and ridiculous returns on their time invested, and you aren't, period. I got that off my chest. Now let's get into. Let's get into some stats, y'. All. Let's get into some stats. All right. Hey, Frank says that, you know, him and his company are using generative AI. That's good. Tara says every company needs a Jordan Wilson. I don't disagree with that. Tara. Yeah, people can reach out to me if they need help implementing generative AI, but let's look at this study. Ready? So a Deloitte study said 79% of people expect generative AI to transform their company within three years. Guess what? We're already a year and change into that. So a year and change, that's what you got left to fully implement generative AI from top to bottom. If you don't want to get passed by your competitors, I cannot wave a larger red flag on the podcast and the everyday newsletter and the live stream. Maybe I should literally get a red flag, y', all, so you can understand the importance. Because there's still very smart people, very smart companies out there that are still saying, nah, not for us, y'. All, I'm warning you, this is not like the Internet. Here's the big difference, y'. All. Every single big tech innovation up until generative AI, it changed or it impacted or it improved the way that we share intelligence. Right? Sharing intelligence. That is not generative AI. Generative AI creates intelligence. Yes, it does. You can argue that, oh, all large language models are all generative AI is. Is. It's autocomplete. Well, yeah, that's technically true, but it's also technically true when that autocomplete system has trillions of parameters and works 24, 7 and you have the smartest people using it. It is literally making new discoveries. It is literally creating new intelligence. It is literally solving, you know, mathematical problems that have plagued scientists and researchers for decades. The Internet was how we shared intelligence game changer generative AI creates new intelligence, new game. All right, and 79 of companies surveyed by Deloitte expected Gen AI to transform their company. All right, here's another, another study from ey. Hey, Shout out. I think we got someone from, from EY here in the comments. What's up, Josh? So EY study said that 73% of people are concerned about their organization not offering sufficient training. And I'm guessing, honestly the 27% of people that said yes were probably people that had an impact on bringing whatever training that they currently have into the organization. Because I would guess that that number should be in the 90s, so. But still, almost 3/4 of people are concerned about not having enough trading. All right, so let's hit rewind here and let's talk a little bit more about why there might be this huge lack of education or what. I'd like to say there's a lot of misinformation out there. Here's the problem. And I want to see like, hey, for, for my live stream, folks. Let me know if this is true, all right? I think I've solved this, y'. All. I think I've solved this. So here's, here's why we have this huge gap, right? We have such a large jaw dropping gap between the powers of Generative AI and how it is currently being leveraged across the business landscape. Here's why, right? I talked about it. Build, build, build, build money, money, money, money, right? I spoke at the AI Summit in New York last month, okay? And I was straight up flabbergasted, talking to huge companies, right? Dozens of Fortune 500 companies having conversations with people and just going through the sheer lack of training they have. And I said, why? And they said, well, we got to build, we gotta ship faster, gotta raise money, right? That's the concern. Education is not a top priority at all, right? Like literally. All right, so here's the problem. You have the smartest companies in the world, the smartest engineers, and by the way, like these engineers that are building the AI systems we all use now, they're legit, like NBA superstars in terms of, like, they are in crazy demand. They're getting paid oftentimes, you know, more than a half a million dollars a year. And that's not even counting, you know, equity or stock options. They're getting paid ridiculous amounts of money because everyone wants them. Because the focus is to build, build, build and raise more money, money, money and make more money, money, money. Makes sense, right? That's The American way. So the brightest minds are building at breakneck speed at OpenAI, anthropic, meta, IBM, Microsoft, Google, Amazon, Nvidia. Right. I'd say those are, you know, eight of the largest players in the AI space and they're building at breakneck speeds. And here's the thing, I don't want to gloss over this, but most of these companies offer some sort of free training, right? They have, you know, online courses. You can take, you know, a free three hour course on this, a free two hour course on that. Sure. But they're topical, right? They're extremely topical. Also. They're a little bit not salesy. But they're a little salesy. Right. Fear. If you, you're a trillion dollar company and you're competing with other, you know, other large language models for enterprise customers and you're putting out free training, obviously that free training is going to be geared toward convincing people, hey, use my large language model, not theirs. Right. So do these big trillion dollar companies put out free education? Sure. Is it properly educating and training both their employees and their clients? Absolutely not. Fail. Big F on the paper from Professor Jordan. All right. Failure across the board. So that's the problem. The smartest people in the world are head down. The smartest companies are head down building. Not training, not educating. So who's training and who's educating? This guy. This guy here on the screen. Right. For our podcast listeners, this is a fictional person. I call this person Billy Boy. All right, so Billy Boy was. First Billy Boy was a crypto expert, and then he was an NFT expert, but now he's a chat GPT expert. All right, so Billy boy is 20 years old, he lives in his mom's basement and he has zero work experience. Yet everyone is following Billy Boy and they think Billy Boy here, who is tweeting out chat GPT will make you rich this weekend. Like, comment and retweet this post and I'll sell you my prompts book. 9724 chat GPT prompts to make you rich for 99. Normally 4995 doll. Hashtag crypto. Right. This is fictional, but it's also very real. We have the biggest companies not fully following through with training, and instead we have these 20. Yeah, and this is, I know this is like old man Jordan, old man Wilson shaking his fist on, on the porch, but this is who we're looking to, to train the general business world. And this is snake oil. This is one of the reasons why so many companies have not properly Implemented generative AI because they got swept into this smoke and mirrors craze of, oh, look at all these prompts. Look at this person sharing these prompts. And then they take those prompts, copy and paste, they waste their money on, on some, some nonsense that this person is, is pushing them. And it is literally snake oil. You put it into chat GPT and you're like, oh wait, this isn't that good. These copy and paste prompts from Billy Boy are, are average. Looks like generative AI isn't for my company. Right? Because if you, if you look at tech, you know, giant tech company, trillion dollar tech company, and you're like, can we get training? They're too busy building. So you turn to Billy Boy here and you are sorely disappointed and then you feel, oh, okay, well, generative AI doesn't work for us. The outputs aren't good. Let's just not do it. Let's wait and see. Let's wait and see for someone else to do it. That is the problem. Stop listening to inexperienced people who are blowing up on social media, right? Because they're in these engagement pods with 50 of their other NFT Billy boy crypto friends. So we all think they're genius. No, they are tricking you. They know nothing. Prompts do not work. If you are equating the power of generative AI with the output of a copy and paste prompt, you are doomed. That is not generative AI. Snake oil, y'. All. Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Genai. Hey, this is Jordan Wilson, host of this video very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everydayai.com partner to get in contact with our team or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI. On GenBR says yes. So many Scams going on. Seriously, watch out for these fake AI coursers, courses and super prompts. Yeah, absolutely. Hey, shout out to former guests here. Josh, dropping some knowledge here. So it's not just me. All right, so Josh is saying, spot on, Jordan. There's a massive lack of documentation from OpenAI, Microsoft and Anthropic and I'll say lack of documentation across the board. Right? But he's just said OpenAI just, OpenAI just came out with a prompt guide one year after release. Yeah, a whole year. And we finally got a prompt guide, right? And it finally said, oh, guess what? You know, zero shot prompting doesn't work, of course. Right. So if you use these copy and paste prompts, those are zero shot prompts. They don't work. No such thing. Stop doing that. Got that off my chest, y'. All. So that's a big piece on education because that is misinformation, right? And a lot of times I will even go as far as to say it is disinformation because these silly Billy boys know that prompts don't work. But they keep putting them out there because they know you're going to comment, you're going to share, you're going to buy their, you know, BS course that they're pedaling, that does nothing. So they're going to keep doing it. So stop doing it. Stop feeding the trolls. All right, so let me talk about personal stories here. All right, so if you're listening on the podcast, I'm going to do my best to explain this very elementary graphic that I made. Yes, AI didn't make this, I made it. That's why it looks so bad. All right, but let's just imagine we have three tiers of companies, all right? In any company here in the US fits under one of these three tiers, all right? Our top tier, let's just say this is our trillion dollar tech companies, you know, so there's a handful of companies up there, you know, it's your, it's your, Microsoft's, your Googles, your Metas, Amazon, etc, right? These are the huge tech giants, or we'll say trillion dollar capable, right? So let's just put all of our major AI giants in, in tier one, right? Then you have your tier two, your tier two companies. This is as an example, this is your enterprise company, your Fortune 500, your Inc. 5000. These are the fastest growing companies, enterprise companies, publicly traded companies, etc, and then Also in Tier 2, I'm going to put large consulting companies, all right? And then you have tier three. That's everyone else, right? So that's your small and medium sized businesses, your startups, See look, error, error. That should say small businesses right there. Or local businesses, right? So we have our three tiers, big giants, then you have your public companies, consulting companies, and then you have everyone else, your entrepreneurs, your small business, small medium businesses, startups, local businesses, etc. Okay, the way that this in theory should work when it comes to AI education and AI training is there should be tight communication between tier one and tier two. And in theory, knowledge, education and experience should trickle down. In theory, right? Look at any other major tech implementation in history, right? Look at, I mean this is a very small example, but look at CRMs, right? CRMs obviously really improved how business gets done for the most part. That was a top down education approach, right? If you were a big Fortune 500 company, you would have unlimited on demand training from that giant conglomerate trillion dollar company that was selling you a CRM or the, you know, the leader in the space on tier one that is providing that service. It's not like that with generative AI. Ready, we're going off the record reporter Jordan. So one cool thing that I don't talk about a lot here on the everyday AI show is the type of relationships that we have, right? There's obviously nice perks that come along with having the most listened to AI podcasts in the world. I've got people from these trillion dollar companies reaching out to me, sharing information, right? Like, which is nice. But I also have conversations with people that work at these big companies, you know, kind of off the record and guess, guess what, right? So many of these people at trillion dollar companies have told me, hey, even though we're building AI, most of our employees don't know how to use even our own AI, right? Y' all see how crazy that is? You see how crazy that is? Like if this is changing the way that we work and it literally is, the biggest companies in the world, the trillion dollar companies are too busy head down building, building, building money, money, money. And they are not even educating their entire staff or at least not properly, not required education. And y', all, I've heard this from multiple trillion dollar companies that are building the AI systems that we all use. They're not educating because they're worried. They're worried about their other competitors. They're saying, oh we, if we spend too much time educating and training our employees, that's taking your foot off the gas, right? Huge problem, huge problem. So then what happens is normally you have this tier two, right? So tier one is your trillion dollar tech and just huge AI companies that are building the technology we all use. Tier 2 is usually first, you know, kind of first adopters, right? Those are your large consulting companies that are generally serving as liaisons. Right? Their clients are either tier. So if we're talking large consulting companies, their clients are either tier 2 or tier 3 customers, right? And they're looking at big consulting companies saying, hey, how do I use this new generative AI? Right? We're paying for it, we don't know how to use it. Guess what? Not naming names. I've had people let these large household name consulting companies ask me, ask me, number one, how do we use this? We're, we have this in our, in our organization. Our clients are asking us, we don't know how. They're saying, Jordan, can you introduce us someone at this company? We don't, we don't know how to train our staff or our clients. And everyone's asking us, right? And then people are just saying, oh, let's do what Billy boy does, right? That is literally happening. I'm not making that up. I'm not. Naming names happen on multiple occasions. Same thing with big public companies. You know, your Fortune 500, your Inc 5000. There's, don't get me wrong, there's outliers, obviously. You know, I'd say, you know, you, you have your, your 10% of companies that, that are ahead of the game, they're training properly, they're, they're literally running away. And those 10% that have properly taken the time to train their employees to understand how these technologies actually work, they're the ones that are going to win in the end. All right, so you have your 10% of companies that are prioritizing and going all in on training, education, understanding and practical use cases. Then you have your 10% that are ignoring it, that are ignoring generative AI and then you have your 80%. So that's what I'm talking about here. When I have this diagram up, there's obviously outliers. Okay, I'm not talking in absolutes here, but I'm talking about that middle 80% in the middle 80% of tier 2 companies. The largest companies in the US that aren't these mega cap tech titans, consulting companies, etc, they don't feel great. They, again, I started that stat. 73% said they do not have the proper education, training and resources yet. Everyone is expecting these, this, this tier two to be. These are the companies showing us the way. No one knows. And I'll Say this tier three. So those small and medium businesses, startups, entrepreneurs, local businesses, I'd say they're actually some of the ones that are best off right now leveraging generative AI, y'. All, if you're a small business owner listening, if you're a, a startup and, and maybe, you know, you're, you're smaller compared to your larger competitors, you are actually at an advantage because if you properly do things the right way, if you properly understand how even just large language models work, you are instantly at a huge competitive disadvantage. But by being small and nimble and agile and being able to shift and being able to learn new things quicker, we're actually at an advantage. Right. We do our, you know, our free prime prompt, polish prompt engineering course all the time and we've had people from literally all three of these tiers, right? We've had people from literally the tech trillionaires take our course. We've had people from large consulting companies, Fortune 500 small medium business businesses, startups, etc. I'd say out of the 2, 000 plus people that have taken our course, it's actually the tier three that are putting that free prime prompt Polish Prompt Engineering 101 into practice and getting the most out of it. There's too much red tape, there's too much lack of, of top down leadership at so many of these companies in tier one and tier two. It's problematic if you're a leader in one of those companies listening, you gotta make a change. Your people might not be telling you about it, but they're telling me, hey, Jordan, we're not getting trained. We're building this technology. No one's training us. Problematic, y'. All. Hey, Tara said she loves ppp. That's good. All right. Yeah. Marcus. Hey. Another former guest, Marcus. Thanks for jumping on Said. That's the age old problem of training. We have no time. We're being predictable, productive. Right? Yeah. Which again, generative AI is something that we have never experienced before. Right. Similarly to how the Internet changed how we do business, Generative AI will change how we do business even more, but in a fraction of the time. Right? We're not going to get that 10 to 15 years to figure out generative AI. We're gonna get a couple more months. All right, let's talk more facts, y'. All. I brought more receipts. You think I'm gonna go on a three flame emoji rant and not have more receipts? I think I'm just gonna go off what people are telling me. Off the record. Nah, Nah, nah, nah. Here we go. Ready? All right, we're gonna go through this fast because no one wants to sit here and listen to stats, but they're important. All right, ready? 83% of companies claim that using AI in their business strategies is a top priority. All right? And there's different, different studies on here from Tech Co, Workday, IBM, Etc. All right? 65% of businesses say they use Chat GPT. Pretty, pretty large amount, right? Only 4% of companies have implemented AI throughout their entire organization. Only 4%. Imagine right now if you said, hey, this Internet thing, yeah, only. Only 4% of companies out there have implemented it top to bottom. That's wild. There are so many easy productivity gains with generative AI. Right? 80% say their company has yet to share guidelines on responsible AI use. What? What? That's. That's nutty. If 83 of companies claim that using AI in their business is a top priority, so 80+ say it's the top priority, but 80 say their company has yet to share guidelines on how to responsibly use AI. Those two things don't add up, y'. All. More stats, more contradictions. Ready? 72 say their org doesn't have the skills to properly implement AI use. 72% of people are saying, y', all, like, we, we don't have the team for this. We don't have the skills. Do you know how bad that is? Right? If you're a leader at a big company, think 72% of employees out there think, yeah, my company, we don't. We don't have the skills. That is a big vote of no on the confidence scale. 70%, 72% of people, right? Here's another thing. This one's from the, the newest IBM AI study. It says, so at different organizations, AI investments yield 2x greater return on investment than non AI projects. All right, let me say that again. So AI projects yield a 2x greater return on investment than Non AI projects. This is across. The IBM study was across thousands of enterprise companies throughout the world, y'. All. That's wild. That's wild. Yet we're not investing in proper education, proper implementation and understanding. All right, I want to go through some conundrums here. Ready? We're going to go through these quick. And then I want to get, get to y'. All. If you have questions, get them in now. If you have concerns, get them in now. I want to talk about them. Ready? So there's an AI paradox here. So despite 83% of companies claiming that AI is a top priority, a staggering 80% haven't shared guidelines on responsible AI. You on responsible AI use literally doesn't make sense. Everyone is saying AI is a top priority, but hardly no one has said, here's how to responsibly use AI. AI is just a buzzword right now. All the big companies, they know they need it because they don't want to get passed up. If they're a public company, they got to say AI and spit it out all the time during earnings calls in order to, you know, keep their stock price up. But they haven't even shared guidelines. Okay, let's talk about the skill gap here. All right, so it's ironic that 72% of leaders admit that their organizations lack AI and machine learning skills, yet continue to accelerate AI investments. Right. 59 of companies, according to the IBM study, are accelerating their AI investments. Yet 70 in a separate study from Workday, 72% of leaders admit that their organizations lack the skills. Okay, so the overwhelming majority of of people are saying our organization lacks the skills to implement AI, yet nearly 60% are accelerating their investments in AI. That seems like a recipe for it blowing up in their face. Okay, all right, here's another one. Some fun things to ponder on this hot take Tuesday. So the biggest barriers are all education based. So this is according to an IBM study, the three biggest barriers to AI implementation are data privacy, trust in models and skills. Okay, guess what? All of those things are based on education and training, right? Data privacy, yeah, that's a concern. But you need to properly understand and train your employees on data privacy. I agree. The tech companies need to also be a little more transparent and give you more information about how you know data is and is not used, what type of data is used to train models and what data is not used, and you know, according to what plans or what tier of their product you're using. So yes, companies need to be more transparent about that. The big companies building large language models, but all three of those things, data privacy goes to knowledge and education and training. Data trust in models goes to knowledge, education and training. And then skills. Knowledge, education and training. We've fallen, especially here in the US and it's interesting. I'll leave a, I'll leave a comment on this, on this LinkedIn post to the IBM study. The US is, you'd think the US is, is world leaders in successful AI implementation. We are not. According to the latest IBM AI study, we are actually, I believe, behind the global average. And here's. Hey, I wasn't going to say this until all of y' all gave me the three flame emojis. This was only a three flame emoji take. But I'll say this. In the US we only think of generative AI as a shortcut. We're lazy. Yeah. We're looking for the easy way out. So when it comes to generative AI, that's all we're looking for. It's all we're looking for. We're not seeking to first actually understand the data privacy. We're not truly seeking to understand how we can trust models output or how to increase the quality of the output so you can have more trust in it. We're not investing in skill development and education. We only care about shortcuts. Right. How can I automate 70% of my work and not tell my employer? Right. That's what people are worried about. Or they're just worried about how can we appease shareholders by investing more money into AI in hiring fewer humans. That's what people in the US we are looking for shortcuts. Again, this is the 80%. I'm not talking everyone, but we are looking at generative AI as a shortcut, which is why we are massively failing at implementation. Speaking of AI implementation, the AI implementation cliff. So if 77% of businesses are integrating AI, why are only 4% fully implemented? Right? Talk about that Cliff. Talk about that drop off, right? More than 3/4 of businesses are using AI, but only 4% are using it across their organization. My gosh, there is such a huge disconnect there, right? That means that the overwhelming majority of companies that are implementing AI in some facet are not fully investigating how to properly roll it out across the organization. They are not getting quantifiable returns on their investment, just looking for shortcuts. All right, I think our last. Our last conundrum here. So here's our AI investments conundrum. All right, so like we talked about, businesses are accelerating their AI investments with 59 increasing their stakes. Yet the top barriers are data privacy, trusted models, and skills. So this again just looks like we are. So many companies are just pouring money at the problem, right? Nearly 60% are wanting to invest more money. Yet the biggest drawbacks are all solved with more knowledge, more education, more training. But we'd rather just throw money at it and hope that it eventually goes away or hope that our employees will eventually figure this out. Ah, it's like the Internet, you know, I don't know. Like, I started working in 2002, right? So the Internet had obviously been around for a while. I was never properly trained on the Internet. You just figure it out, right? Large language models are not like that. I think the Internet is actually much more cut and dry than gener, than generative AI. You have to train, you have to educate y'. All. So I'm gonna get to a couple questions here and wrap up. So, Rolando, asking Said, first time live. Thanks for joining us. So asking, who is at the forefront in training on the three biggest barriers to AI implementation? No one. No one. You know, I'm being honest. Yes, the big tech companies do have, you know, some decent trainings out there, right? All of the models you're using, for the most part, they all have training. Not all of them, which is funny, but no one. No one. Because I think instead of fully understanding large language models and getting to the root of the issue of understanding in creating a learning plan, instead, Rolando, the big companies are just focusing on where they are seeing measurable gains and they're just doubling down on that, right? That might be only 10% of their use case, but as soon as companies say, oh, wow, we're getting huge returns on, you know, in department L instead of figuring out department A through K and why departments A through K aren't getting positive returns on generative AI in tackling those, those three issues that we just talked about, you know, data security, trust and skills. Instead of saying, ah, I wonder why all the other departments aren't getting, you know, crazy great returns. Or, you know, maybe they don't have the mechanisms in place to measure, you know, quantifiable outcome, to calculate a return on investment or return on time invested. Instead they say, oh, look, this department's crushing it. Let's double down here, let's triple down here. Companies are too focused on finding quicker wins than they are about properly using it and implementing it across the organization, which is why only 4% right now have AI implemented top to bottom. All right, that's it, y'. All. I could go on literally forever. But luckily we have a show tomorrow kind of related to this. So if you're hearing this and you're like, oh, wow, this sounds like my company. Oh, this, this seems like a problem, right? This seems problematic. Well, join us tomorrow because we're going to go over the five simple steps to start using Gen AI in your business today, Y', all. We've had almost 200 shows here on Everyday AI. I've been very lucky to talk to some of the smartest people in the world around AI. We always get tidbits before and after the show and some great things in the show that we never come back on. So we're digging deep into the archives and we are building you literally a blueprint. All right, so if you heard today's show and you're like, yeah, this sounds like my company, there's no education, there's no training, or I just don't know how to implement it. Make sure to tune in tomorrow. Hey, Thursday, it's going to be a straight up creative banger. We have Rory Flynn, the magician of Mid Journey, joining us to go over mid journey v6, what's new and how to produce powerful ad creative. And then Friday, we're capping it off with maximizing the effectiveness of AI and healthcare with the president of the American Medical Association. Yeah, that's right. We are bringing you some expert level guests to break it all down. That's what we do here on the Everyday AI Show. If this was helpful, please let me know in the comments. If you're still listening, if you still have questions, get your questions in. We're always here to help, to be a resource and that's what our website is. So go to your everydayai.com. sign up for that free daily newsletter. We recap every single episode in great detail. Every keep you up to speed on everything else going on in the world of AI so you can properly leverage Generative AI to grow your company, to grow your careers. I hope this was helpful. I hope you at least now have a better path forward on how your organization can properly tackle this. One secret. It's not a secret anymore, but this silent productivity killer when it comes to AI is proper education, proper training. Get after it, y'. All. Thanks for joining us. We'll see you tomorrow and every day with more Everyday AI. Thanks, y'. All.

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 youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.