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Why “AI-Powered” Is Not Your Edge: Rethinking Competitive Advantage for 2025
Businesses implementing generative AI at scale were once lauded for their foresight—now, that distinction has all but vanished. Many organizations continue to treat AI as a special capability or differentiator, as if it’s still 2023 and not an essential infrastructure. Current market signals and internal practices reveal this approach is outdated, exposing companies to risk and missed opportunity. Here’s an in-depth exploration of the current landscape and the crucial actions organizations must now prioritize.
AI Is Now the New Internet—Not a Moat
Organizations still touting “AI-powered” solutions as evidence of innovation are fundamentally misreading the marketplace. AI adoption has become so widespread that labeling an offering as “AI-enabled” is as redundant as calling a business “Internet-powered” in 2025. Customers expect AI seamlessly integrated into every product, workflow, and interaction; it is no longer optional or novel.
The transcript introduces a practical litmus test: Replace the word “AI” with “Internet” in your strategy. If the claim of being an "Internet-powered" organization sounds absurd, so does "AI-powered." This test exposes the superficiality of strategies that hinge entirely on deploying generative AI without deeper operational transformation.
Customers Are Using AI—Often Unknowingly
The boundaries between traditional digital tools and AI-driven features are rapidly disappearing. Search engines, email platforms, and productivity apps now embed AI so thoroughly that end users rarely recognize when they’re interacting with it. For example, Google’s “AI mode” already handles more than two billion queries monthly, and nearly half of all search queries receive AI-generated results automatically.
A Microsoft study cited in the episode found that 60% of workers already use AI without labeling it as such. Meanwhile, 90% of Fortune 500 companies run on generative AI tools. These numbers pinpoint the quiet ubiquity of AI and raise a clear implication: Not using AI is now the glaring outlier. For any business, being “AI native” will soon be as fundamental as having a company website.
Superficial AI Strategies: A Warning Sign
Large enterprises often mistakenly frame generative AI as mere “tech enablement,” missing the mark on true disruption. Many public companies, for instance, emphasized AI buzzwords in earnings calls in 2023 and saw short-lived stock gains. But such bravado masks a lack of strategic depth. The script is familiar: Encountering stagnating growth or operational inefficiencies, leadership hastily attempts to “apply” AI as a patch rather than instituting a root-and-branch rethink.
A root cause: Many are following outdated blueprints from earlier digital transformation efforts—Internet, cloud, mobile, social—without grasping the fundamentally different scale, speed, and internal impact of generative AI.
The New Table Stakes: Real Training, Internal Benchmarking, and First-Party Data
The transcript draws three actionable priorities for companies moving forward:
Comprehensive Training on Generative AI
Every employee, regardless of role, should understand the basics of large language models and generative AI. The skills gap is now a liability—training is as fundamental as providing staff with computers or Internet access.Development and Ongoing Evaluation of Internal Use Cases
Benchmarking based solely on third-party metrics is insufficient. Companies must define, iterate, and continuously reassess custom internal use cases. AI learning and deployment is not “set and forget." Rapid cycles of experimentation and measurement are required to maintain relevance.Building a First-Party Data Collection Team
Generic data sets or simple retrieval pipelines (“RAG”) aren’t enough. Future AI advantage will depend on capturing, curating, and utilizing unique institutional knowledge, reasoning, and decision frameworks. This includes not just structured data (from CRMs/ERPs) but the implicit logic of senior staff and business leaders.
Don’t Rely on Retrofitting: The Call to Redesign
Overlaying AI onto legacy processes fails to unlock productivity or defend against nimble competitors. True differentiation involves re-engineering processes from the ground up with AI at the core. The reliance on “upskilling” or minor tweaks will not suffice; organizations must be willing to unlearn and redesign how work is done at every level.
This need is underscored by the actions of giants like Microsoft, which simultaneously reduce headcount and invest billions in AI learning—amplifying both upheaval and opportunity. As layoffs in the tech sector generate fresh startups, smaller groups unencumbered by legacy mindsets are poised to outpace larger, slower incumbents.
Missing the Profit Window: The Cost of Delayed Adoption
Early adopters of generative AI reported returns of $3.70 for every dollar invested (IDC/Microsoft study), but 74% of late movers struggle to measure any positive ROI (Boston Consulting Group). The window for easy gains has closed; latecomers will be forced to fundamentally reorganize operations—and profits will lag without bold, systemic changes.
Conclusion: Stop Bragging About the Plumbing and Start Building
Integrating AI is now akin to providing electricity or wired Internet: indispensable but invisible infrastructure. Simply “using AI” is no longer a strategy—it is the new baseline. Genuine advantage lies in how unique data, processes, and human expertise are embedded for the next wave of generative AI advancement.
Competitive advantage will not go to those who signal, but to those who reconstruct. The expectation has shifted; business leaders must respond in kind—before being left behind.
Topics Covered in This Episode:
- Companies’ Outdated View of AI as a Differentiator
- AI as Baseline Technology, Like the Internet
- “AI vs. Internet” Test for Strategy Validity
- Superficial Use of “AI Powered” in Marketing
- Widespread, Unconscious AI Use by Employees and Customers
- Universal Expectation for Companies to Be AI Native
- Tech Sector Layoffs and Productivity Tied to AI Adoption
- Agile Startups Threatening Slow AI Adopters
- Integration of AI Seamlessly into Web Tools (Google, Bing)
- Major Providers Offering Free AI Tools
- AI’s Pervasiveness in Fortune 500 and Customer Expectations
- AI Improving and Compressing Business Communications
- Early AI Adopters’ Profit vs. Late Adopters’ Missed ROI
- Necessity to Treat AI as Infrastructure, Not Innovation
- Recommendations: Employee Training, Custom Use Cases, First-Party Data
- Warning Against Superficial AI Integration
- Urgent Need for Process Reengineering for True AI Advantage
Keywords:
Generative AI, AI strategy, company AI advantage, digital transformation, business innovation, artificial intelligence, ChatGPT, large language models, AI implementation, AI-powered companies, AI enablement, AI versus Internet test, business processes, AI native, competitive advantage, AI adoption, AI disruption, Internet powered, AI expectations, enterprise AI, Microsoft Copilot, Google Gemini, OpenAI, Anthropic Claude, AI in business, customer expectations, agentic AI, first party data collection, reasoning data, RAG, AI use cases, productivity gains, AI training, business automation, workplace AI, upskilling, reskilling, institutional knowledge, data
Podcast Transcript
So many companies are living in 2023 right now. Here's what I mean. I can't tell you the amount of people that talk to me or pitch to be on this podcast and treat AI like it's something special, like it's 2023. Here's what I mean by that. If your company had fully implemented generative AI in 2023, you could do something with that. That could be your company's advantage. Yet here we are two and a half years later after the generative AI wave. That was chat GPT in November 2022.
Jordan Wilson [00:01:02]:
And so many companies still think, and they honestly believe that using AI can be their company's advantage. I'm here to say you're wrong. And if you still think that way, not only is that a archaic way to go about building your company or your department, but I'm letting you know you're going to get lapped. You're going to get pass up by smaller, more agile companies that understand AI isn't your company's advantage anymore. It's just the Internet.
Midroll [00:01:44]:
All right.
Jordan Wilson [00:01:45]:
I'm excited for this episode. I hope you are, too. What's going on, y'? All? My name is Jordan Wilson, and welcome to Everyday AI. This thing is for you, unedited, unscripted, live. I say sometimes it's the realest thing in artificial intelligence, where you can't tell what's real and what's fake. Well, this is real. And if you're trying to grow your company and your career with Generative AI, it starts here, right, with a live stream of the podcast. But if you really want to take it to the next level, you got to go to our website at your everyday AI.com, because there you will find not just a place to sign up for our free daily newsletter where we're going to be recapping the highlights of today's show and everything else to keep you in the loop with what's happening today in AI, but also you can go learn from hundreds of the industry's smartest, most creative, most innovative companies that we've interviewed on our show, all for free.
Jordan Wilson [00:02:38]:
So if you want the AI news, make sure to check out today's newsletter. But let's get straight into today's show. And let me just be blunt in saying this. I think this is one of those episodes I'm making kind of for Myself.
Midroll [00:02:54]:
Right.
Jordan Wilson [00:02:56]:
Sometimes it's, it's, you know, we do these hot take Tuesdays, right, And let me know if you guys like this new kind of lineup that we kind of unofficially started a few months ago. So we do the AI news that matters on Mondays, Hot take Tuesday where I give you all a hot take, putting AI to work on Wednesdays and then we generally do interviews on Thursday and Fridays. So this is, this today's Hot take Tuesday. It's a selfish one, let me be honest, because I get so many people all the time, right, pitching me or, or trying to tell me about some innovative thing that their company's doing and I'm like, you're using chat GPT. This is not tech enablement, this is not disruption. And so many companies truly believe that just by using generative AI, by using large language models that this is somehow a competitive advantage. And yes, this is a real thought by real enterprise companies here in the US and globally. So don't get me wrong, I'm glad that the conversation has turned from AI being this like, oh, should we touch it? Not sure.
Jordan Wilson [00:04:07]:
Right to now every single company does realize that they need to use it. But in today's show I want to tell you a couple of things. One, I'm going to give you the AI versus Internet test to see if your company's strategy or marketing is sound or useless. I'm going to tell you why your customers are using AI without even knowing it and how that impacts what your company does. And then I'm going to give you the three things that you should be doing instead of just slapping AI powered on your website or blindly saying that you offer something of AI value. So here's my straight up hot take, right? So you don't have to listen in the next 15 to 20 minutes. Number one, companies are just slapping AI powered blank on their website and they think that makes them innovative. I think that makes you look foolish and I'll tell you why.
Jordan Wilson [00:05:02]:
Because AI is just the Internet, okay? The lines are blurring every single day. So many people are actually using and benefiting from AI and relying on AI without even knowing that they're using AI. So if you want to be so braggadocious, right, as a company and, and, and you know, put out there how you're AI powered, AI enabled. It looks fairly foolish because that is the baseline, that is the expectation now. And I think most companies AI strategy is embarrassingly basic and we're going to prove that today. Hey, Douglas said live stream audience. Good to see you Douglas. Good to see you.
Jordan Wilson [00:05:52]:
Douglas said I may need coffee for this. Hey, I got my coffee, got my hoodie on. I'm going hoodie, mellow, mellow hoodie. Any basketball fans know what that is, right? Carmelo Anthony, when he had the hoodie, he was just in a vibe. He was just in a mood, right? I'm in one of those moods today where I think I just have to rip a bit. Little, little bit.
Midroll [00:06:10]:
All right.
Jordan Wilson [00:06:13]:
All right. But hey, live stream audience, it's good to see you as always, but I want some questions from you all.
Midroll [00:06:22]:
All right?
Jordan Wilson [00:06:22]:
Do you have any hot take questions on this topic on how AI, how companies are using this as a strategy or the maybe misalignment between what companies think tech innovation is and what the current reality is? I'd love to take a couple questions today. Don't always do that, but I'd love to be able to do that today. If you have any questions for me, hot take questions on today's topic, get them in. But let me start with the simple test that exposes weak AI strategies. And it's very simple, right? Whatever your company's AI strategy is, right? And obviously this isn't going to hit a hundred percent of companies, but I think this will hit the majority of companies, right? When you say we're going to leverage AI to do blank, blank and blank, are you going to slap that on your website? Are you going to send that over, right in your, in your proposal to a potential customer about how you're using AI? Here's the test. Swap out AI with the word Internet. Simple as that. Now if you say something like we're an Internet powered company, it sounds absolutely ridiculous in 2025, right? We're an Internet, right? But that's what I think you need to do.
Jordan Wilson [00:07:41]:
AI is the expectation, right? Slapping, you know, AI like, like flex seal, right? If, if you remember those infomercials, right, There's a leaking boat and the, the, the infomercial guy, which by the way, I don't know why, even when I was like 8, 9, 10 years old, I loved staying up late and watching infomercials for stuff I would never buy. I was FAS them, right? But you're slapping the flex seal or whatever to stop a leaky boat. That's what companies are doing with AI. They can see the leaks in their company. They can say, hey, we've, you know, for 10 years we've seen, you know, X year over year growth and we're not really seeing it anymore. So what are we going to do we're in a flex seal some AI on this thing, right? We're going to tell our customers, our clients, our board members, our shareholders, whatever this the case is for your company, that we are AI first, we're AI native.
Midroll [00:08:37]:
Right?
Jordan Wilson [00:08:37]:
Buzzword, buzzword, buzzword. And I think that this has actually worked for a lot of companies in 2023 and 2024, especially public companies.
Midroll [00:08:46]:
Right.
Jordan Wilson [00:08:46]:
It was kind of trendy or in vogue at the time, especially in 2023, especially for public companies in earnings calls to talk about AI as much as they could. Artificial, intelligent, agentic AI.
Midroll [00:09:00]:
Right.
Jordan Wilson [00:09:00]:
Rag.
Midroll [00:09:00]:
Right.
Jordan Wilson [00:09:01]:
If you could throw out any of these kind of buzzwords in earnings calls, what happened? Your stock went up. Because at the time, a year and a half ago, two years ago, most people weren't really sure what this AI thing was going to be, but they, they knew they wanted it.
Midroll [00:09:16]:
Right?
Jordan Wilson [00:09:18]:
They're like, all right, I don't, I don't know. This agentic AI with rag pipelines is. But we need it. Yes. Talk about it more. CEO. And then I think the rest of the business world followed suit, but years too late. And if your AI strategy or your AI positioning sounds stupid, if you just swap out the word Internet, does it still make sense? Does it still sound like a differentiator? Probably not, because so many companies, AI strategy right now is thin and useless.
Jordan Wilson [00:09:53]:
And that's not necessarily a knock on every single company because this is a wave of tech innovation that I don't think that we have a comparison to. And that's one of the reason why even companies that I think are ultimately still going to be successful and have been successful for many years or decades, I think are so behind the curve because they're taking the digital transformation blueprint that they've used for every single tech innovation over the past couple of decades.
Midroll [00:10:26]:
Right, Right.
Jordan Wilson [00:10:27]:
Here's what we did with the Internet, here's what we did with cloud, here's what we did with mobile, here's what we did with social media. And they're applying that same blueprint. Sometimes successful, right? Or in many cases, oftentimes their blueprint was successful. And they're trying to apply it to AI, which is why we are here in today's climate two and a half years later. And I'm constantly face having to face palm myself by seeing the position of a lot of big public companies and how they're talking about how they're using AI. And you've probably heard a lot of these rumblings, right? You know, OpenAI CEO Sam Altman has, you know, said, oh, there's going to be a, a one person company that's going to be a unicorn.
Midroll [00:11:11]:
Right?
Jordan Wilson [00:11:11]:
A billion dollar company, one person, because of how they're going to use AI. Will that happen? Sure, but I don't think that's the, the diamond in the rough, so to speak, or the, the, the needle in the haystack.
Midroll [00:11:28]:
Right?
Jordan Wilson [00:11:28]:
That's what it's going to be. That's going to be an anomaly. Will it happen? Absolutely. What you need to be worried about, what your company needs to be worried about and what I ultimately think is going to happen.
Midroll [00:11:38]:
Right.
Jordan Wilson [00:11:39]:
Oh, I'd hate to have the jobs discussion here, but this is the reality. So many companies are going to be laying people off in mass. Everyone's following the example of Big Tech and Big tech has been laying off tens of thousands of people because they're the ones that implemented AI first and they're trying to figure out what it means to work with AI. I think Microsoft is a good example and I'm not dragging Microsoft through the mud here, but they recently laid off about 10,000 people and they've laid off tens of thousands of people over the past couple of quarters, yet at the same time they're investing billions of dollars. They just announced their Microsoft elevate.
Midroll [00:12:16]:
Right?
Jordan Wilson [00:12:17]:
And a lot of people now have this sour taste in their mouth with Microsoft. They're like, okay, well you laid off tens of thousands of people because of AI, yet you're investing, I think it was $4 billion in Microsoft Elevate.
Midroll [00:12:33]:
Right.
Jordan Wilson [00:12:34]:
I'm double checking this here. I think it's $4 billion. Yes, $4 billion in cash and technology into essentially a program to help people learn AI. It's quite a cutting dichotomy, right? When we look at this technology and we're saying, okay, it's going to quote, unquote, take jobs. But then we're also investing in it because we know ultimately it's going to create jobs. But what is ultimately going to happen is companies are going to lay off a bunch of really smart people and then they're going to figure out, oh, our company's AI strategy stinks.
Midroll [00:13:15]:
Right?
Jordan Wilson [00:13:16]:
And you're going to have, right, let's, let's say a, a mid level consulting company, right? I'm not talking about a big four, I'm saying the next tier. All right, Think of the second tier of consulting companies. Let's say this company does, I don't know, $5 billion in revenue, they lay off 10% of their staff in 2025 because of AI. You know what's going to happen? I don't think one of those people is going to be that single company, billionaire company, single person, billionaire company, right? What's going to happen is a group of 10, 15, 20 of them are going to come together, right? Especially when companies lay off people by the hundreds or thousands and they're going to come a company 1/100th of the size that laid them off and they're going to start eating that company's lunch. That's what's going to happen. Because companies have been slow to adopt to AI because their AI strategy right now is, oh, we're using it, right? Oh, we're finally deciding in 2025 to train our employees. Yes, it's a good thing, don't get me wrong, but you should have been training your employees in 2023 and 2024. So that's ultimately what's going to happen.
Jordan Wilson [00:14:25]:
And that's how I think companies are ultimately going to get exposed, by having a weak AI strategy, because ultimately they haven't been leveraging it in the way that I think smaller groups can. And here's another reality. People right now, they don't even know they're using AI, right? A good example of that is Google's AI mode. I think sometimes, especially over the last couple of years, with AI overviews, right? Which aren't necessarily new, but it's getting harder and harder when you're using a search engine, whether you're talking about Google or Microsoft's Bing, to be like, wait, is this a normal search? Or am I using AI right now? Because the lines are being blurred and I think intentionally so. And I think that same concept is going to spill over into not how we work, but also into what customers and clients ultimately expect. They're going to expect your company to just be AI native, right? Let's even look at some examples. Google's AI mode right now, they just rolled it out, is already answering two plus billion searches monthly. And I think most people don't even understand that they're using AI right now.
Jordan Wilson [00:15:48]:
47% of search queries show AI results automatically without users asking. And Google processes 40480 trillion AI requests monthly right across their whole suite of products. People don't even understand they're using AI because the AI is just becoming the Internet. The lines are being blurred and it's creeping into everything in that employees touch. Have an example as an example, right? Not at the enterprise level, but the biggest companies in the world are just giving away their AI for free. Microsoft gives away Copilot free with Office subscriptions starting in January of this year. Google gives away AI for free. My gosh, if you're not using AI Studio, why, Google's AI Studio is absolutely amazing.
Jordan Wilson [00:16:47]:
One of the most powerful tools in the world, ChatGPT gives away AI for free. And their free version of ChatGPT is actually pretty good now, right? Whereas a year ago, if you listen to the show I told you, don't touch it with a 10 foot pole, now ChatGPT's free version, it's pretty good for limited use cases. And right now, 90% of Fortune 500 companies are already running on generative AI tools. So if you, business leader, still think that just using AI can somehow help your company or department grow, compete against smaller and larger competitors, you're dead wrong. And consumers, like I talked about, they're going to expect you to be an AI native company. A lot of studies are saying that 95% of customer service will be using AI by the end of this year. 60% of people, according to a Microsoft survey, are using AI and they don't even know it. They're using AI at work and they don't even call it AI.
Jordan Wilson [00:18:02]:
And not using AI. Your company, if your company's not using AI, your customers and your clients are going to look at you kind of funny, right? I honestly think for companies that aren't using AI in every aspect of their business, by the end of the year, it's going to be like not having a website. Imagine if your company didn't have a website. Red flag, right? Or not having a phone number, especially for local businesses. Red flag. Not having a social media account. Red flag. Consumers and clients will expect all companies to be AI native because no one wants to do those burdensome manual knowledge work transactions.
Jordan Wilson [00:18:54]:
No one wants those, right? I think of the, the meme, right? I'm gonna see if I can pull it up here for our, for our live stream audience. Let's see if I can.
Midroll [00:19:09]:
Right?
Jordan Wilson [00:19:09]:
But there's one person. Here we go. All right, I got it, I got it. So there's one person here, this, in this cartoon that's saying, hey, see if I can share it here. There we go. Live stream audience. You got it. So there's one person on the left hand side and another person on the right hand side.
Jordan Wilson [00:19:35]:
And each of these people are talking to a co worker, presumably at work. And the first one says AI turns this single bullet point into a long email. I can pretend I wrote, right? Oh, wow. Look at this AI. So great. And then on the other side, presumably it's someone reading the email and talking to a co worker and they say AI makes a single bullet point out of this long email. I can pretend I read.
Midroll [00:20:02]:
Right?
Jordan Wilson [00:20:02]:
It's funny. But it's also, I think, indicative of how the business world is going to work soon. We're going to be cutting out all of that nonsense, right? The way that we learn and synthesize information is quickly changing and consumer demands are going to meet that, right? Because what happens is in our personal lives, I think more and more people are starting to use AI because it's hard not to. Like I said, right? We all use, you know, Google on our phone or Bing on our phone or whatever, right? It's AI native. As our personal lives become AI native, our tolerance for needless and now archaic business processes, our tolerance for that is going to become very, very slim.
Midroll [00:20:56]:
Right?
Jordan Wilson [00:20:57]:
I'm not saying it's a good thing, right? But now we don't want a long email, right? We don't want to go on 50 different websites to find one single piece of information. The good thing that AI has done is it's brought more personalized, clearer context to the forefront immediately. And what that means is in our personal lives and everything else, we're getting higher quality information faster that's personalized to us. Consumers are going to expect the same thing. So you need to be an AI native company. And early adopters, I think got rich while other companies out there are still figuring out how to do a year long AI pilot. You're out of luck if that's your company. So According to an IDC and Microsoft study, companies that moved early in generative AI received $3.70 for every dollar that they invested.
Jordan Wilson [00:22:03]:
But 74% of late adopters aren't making money or aren't able to measure a positive ROI on AI. So that's according to a Boston Consulting Group study. So if your company has not already gone fully in on AI, I'm not saying you can't find a positive roi. You can, but you're going to have to drastically rework how your company works because you missed the profit window, treating AI like a regular tech innovation, which it is not. I've always said, like I've been trying to tell people this AI is the Internet. You can't treat it like this thing. You can't touch. Would you withhold? If you're a business leader, business owner, would you withhold Internet from your employees? Absolutely not.
Midroll [00:22:54]:
Right?
Jordan Wilson [00:22:55]:
We need the Internet to read our emails, to research our competitors, to stay up to date with industry trends, to update your CRM, to look up information in your company's erp. You need the Internet, you need AI, right? And here's the thing. Now as these large language models are growing in maturity, growing in capabilities, becoming more and more robust, they're cutting out even the middleman, right? There's companies now, right? I, I read a post as a simple example, right, like oh, you can book travel with AI, which I think is an absolutely terrible use case. And I don't know why all the companies are always showing this when they're showing off agents, right? Let's have this agent take 30 minutes to find you a hotel in Barcelona. No thanks, I'd rather do it myself in a minute. However, you know, now there's companies that are cutting out the middleman and they're just bringing that hotel information straight to a large language model. So a large language model doesn't have to go on third party sites. That's what's going to happen, right? We've seen these large language models grow with their connectors, their integration.
Jordan Wilson [00:24:03]:
I'm not saying it makes retrieval long meta generation pipelines useless. It doesn't. But dynamic company data is going to become easily accessible in large language models if it's not already. And that's I think has changed drastically in the last couple of months. That's why you can't treat AI like some special thing that we have to, you know, hey, let's talk about the board at this next quarter and then we'll roll out a year long pilot. You're going to lose money. Here's what's happened, here's what's essentially happened. AI is basic infrastructure now.
Jordan Wilson [00:24:41]:
It's not a moat, it's not innovation, it's not digital transformation, it's the baseline. The AI market right now is growing 120% every year and usage is doubling every two years. So let me get into some advice here, all right? And if you do have any questions, please get them in. And I always like when you put question in the front, that makes it easier. Thank you for that as I, as I scroll through some of these comments here. All right, so saying AI power now in 2025 in the year 2025 is like saying Internet enabled 15 years ago. And your AI implementation doesn't make you special, right? It's a necessity. Training your employees on using generative AI in large language models is like providing them a computer.
Jordan Wilson [00:25:52]:
It's the basics now Customers assume that you're using AI just like they assume that you have electricity. So stop bragging about the plumbing, right, and start building something with it. That's all it is. I'd like to say you need to treat AI like electricity. It needs to power every aspect of your business, but you would never brag about how your company is leveraging electricity. We need to move past that. I think the conversation on using and leveraging AI needs to change because it is becoming synonymous with the Internet and all that is is electricity. It needs to be powering every facet of your company.
Jordan Wilson [00:26:50]:
So let me tell you three things that you should be doing.
Midroll [00:26:53]:
All right?
Jordan Wilson [00:26:54]:
I just spent 20 some minutes getting this off my chest.
Midroll [00:26:58]:
All right?
Jordan Wilson [00:26:59]:
So thank you for this opportunity. Live stream audience, podcast audience, for a somewhat therapeutic. And I think, honestly, what this is, is I'm tired of.
Midroll [00:27:08]:
Right?
Jordan Wilson [00:27:09]:
We get pitched all the time. Hundreds of companies a year pitch to be a guest on the show, which I'm grateful for, don't get me wrong. And when I was getting these pitches two and a half years ago, when companies are like, oh, we're using AI to accomplish A, B and C, I'm like, oh, cool, that's a great. It's a great use case. Let's interview you. And I don't know if anyone's realized this. I'm doing fewer interviews in our Monday to Friday lineup because if I'm being honest, I'm a little fed up with how companies are treating AI now. Like it's special.
Jordan Wilson [00:27:48]:
We still get those pitches. Oh, you know, we're. Our company's using AI to do A, B and C. You need to talk to our CEO. No, I don't. You're going to go out of business if you honestly think that using AI to do A, B and C is special. I don't want to talk to you because there's a good chance that your company is going to go out of business. If that's still your mindset.
Jordan Wilson [00:28:08]:
If you still think that using generative AI wrapped in your data is something to brag about, it's not two and a half years ago. Yes. Two years ago. Yes. A year and a half ago. Maybe in 2025. Absolutely not. So here are the three things that you should be focusing on.
Jordan Wilson [00:28:23]:
Instead of just slapping AI on whatever leaky thing that is existing in your company, you need to train every single employee on large language models and generative AI basics. Every single employee. People are always asking, okay, well, hey, if we have all these productivity gains, if all these Studies are true. The McKinsey, the famous McKinsey digital study that says you can save up to 70, 70% of time using standard of AI and large language models on manual knowledge work tasks, which is what so many of us do. What do you do at that time? Well, you start assigning certain people on your team to learn AI, right? Listen to the show every day. There's your cheat code.
Midroll [00:29:06]:
All right?
Jordan Wilson [00:29:07]:
And train the rest of your organization. If, if an employee has a computer, they need to be trained on generative AI. What is your company's AI operating system? How do you use it? You need to be training people, keeping them up to date weekly. That's how fast this space moves. You need to be training every single employee on large language models and generative AI basics. Number two, you need to focus on developing internal use cases and benchmarks for your company. Not enough. Not enough organizations are doing that.
Midroll [00:29:39]:
Right?
Jordan Wilson [00:29:39]:
It's fine to rely on third party benchmarks, right? There's plenty of third party benchmarks. We talk about LM Arena a lot here on the show. That's great. But there's a certain point where large language models for a large part can become a commodity. You need to be finding use cases for your company and you need to constantly be benchmarking those use cases on an ongoing basis. Learning and actually leveraging generative AI is an iterative process. It's not like tech innovation of decades past where you, as an example, choose a cloud provider and stay with them for decades.
Midroll [00:30:17]:
Right?
Jordan Wilson [00:30:17]:
It's not like, okay, here's our social media strategy and we're just going to blindly post and hope something happens and have a lot of meetings about it and try to go viral, right? No, this is iterative large language models in the generative AI scape. It is a living, breathing thing. Take it from someone who covers it every single day. Your strategy that you feel so proud about, that was maybe sound a year ago. If you're still doing that. No, not going to make it. You need to be iterating, revisiting. It is a cyclical process.
Jordan Wilson [00:30:54]:
And then number three, you need to develop a first party data collection team that feeds your AI. Unique information rag is not enough. As we look at agentic AI, you need to start collecting reasoning data from your leaders.
Midroll [00:31:10]:
Right?
Jordan Wilson [00:31:11]:
Sometimes we talk about the silver tsunami here on the Everyday AI show. So many companies are going to be losing decades of institutional knowledge. And it's not just these structured information that lives in spreadsheets and CRMs that you need to be collecting. You need to be collecting the expertise, you need to be collecting reasoning, you need to be connecting, collecting, curating, cleaning logic. That's what you need to be focused on. I think so many companies, especially enterprise organizations, they have all their structured data. It's not hard to, you know, connect those and you know, spin up mini rag environments. You know, now you can essentially do in a couple of clicks in front end large language models, which is wild because you used to have to pay millions of dollars and spend a lot of time and hire some engineers to do that.
Jordan Wilson [00:32:02]:
You can now do a mini version of that with a couple of clicks in any front end large language mod. So you need to be focusing on the future of AI, which is agentic AI, which is when you hand over decision making processes to AI agents. You can't be focused on what has happened, you need to be focused on what is happening and how you can find that information and actually leverage it. So again, the three things train. Number one, train every single employee on large language model and generative AI basics. Two, focus on developing internal use cases and benchmarks for your specific business. And three, develop a first party data collection team that feeds your AI unique reasoning information. All right, let's see.
Jordan Wilson [00:32:51]:
Might have a couple of questions. I'm going to try to get to a couple here. All right, couple questions. Here we go. See how this goes. Marie, question. Who do you think will win the AI race to the top? The us, China or India? It's a good question, right? And it's actually kind of relevant to today's show. Even though if you don't know it or not, I'll say this, obviously I'm based here in the United States and most of the companies that I work with are based here in the United States.
Jordan Wilson [00:33:25]:
I don't know who's going to win. I will say this, if you are an enterprise company that does business in the United States, you should be focused on US based models. You should be focused on OpenAI, Google, OpenAI ChatGPT, Google's Gemini, Microsoft Copilot, Claude from Anthropic, those four, right. You shouldn't be using Chinese models, period. It's a huge safety issue. There's a reason why there's ongoing conversations of banning Chinese AI in the US Federal government. Who do I think will win? I mean, honestly right now I think it's a two team race. It's, it's Google and open AI.
Jordan Wilson [00:34:09]:
At least when it comes to the front kind of the frontier, you know, Microsoft's in a very unique position with a 49 equity stake in, in OpenAI. So you can't count Microsoft out, obviously. And it's going to be, it's, it's going to be interesting to see what they do in the coming years as their current agreement with OpenAI changes terms. Another question here from I am tollboy on YouTube. Do you think one of the major large language models will win or do you think a new player will arise in the next year or so and take off and win the war? No, it's going to be one of those four. It's probably going to be either OpenAI or Google.
Midroll [00:34:50]:
Right.
Jordan Wilson [00:34:50]:
It's 1A and 1B I'd say at least recently it's been Google 1A and OpenAI 1B. But you know, that could change next week. All right, Cecilia, isn't an AI strategy a quality enhancing tool that requires re engineering work processes which most people don't take the time to do? Absolutely. Cecilia is right on the money here and I think that's an important thing when it comes to AI strategy. So an analogy that I say sometimes is people think an AI strategy is looking at their current processes, their current SOPs, and just sprinkling a little bit of generative AI on top. We're like, oh yeah, yeah, yeah, let's keep the process the same and sprinkle a little chatgpt here, sprinkle a little bit Google Gemini here. No, you need to absolutely rethink the work that you do. You need to blow it all up, period.
Jordan Wilson [00:35:47]:
All right, an actual AI strategy that will keep you competitive in the years to come. You need to absolutely relook at how you work, which I think is what the big companies like Microsoft are doing. Even though that's not popular for me to say. And I'm not overlooking, right. The, the harsh reality of, of cutting thousands of jobs. But that's what big companies like Microsoft are doing, right? They're rethinking how they work. And that's a process. And you have to.
Jordan Wilson [00:36:18]:
I've said this many times on the, on the show, I hate the word upskill and reskill because I think of that as just sprinkling AI on top. Or hey, we have a 10 step process of how we work and you know, steps three through five, we're just going to combine into one step and we're going to put AI there.
Midroll [00:36:35]:
Right.
Jordan Wilson [00:36:36]:
Is that okay for now? Sure. Will that keep you competitive in the future? Absolutely not. You have to literally unlearn and rebuild from scratch being an AI first or AI native company. Otherwise you're just using the Internet like everyone else. That is not a competitive advantage. That's not a moat. That's not going to help you build into the future.
Midroll [00:36:59]:
All right.
Jordan Wilson [00:37:01]:
All right, one more, one more question here from the YouTube audience. How do you explain how AI works with the average person? They keep hearing jobs will be replaced, but they don't understand how it works or how prompts work. How do you explain it? Good question. I say find someone's pain point, all right, Maybe this is a department head, maybe it's a colleague, maybe it's a co worker. You need to understand what they do in their role. Ask them, see what they hate, right? Then go find the right generative AI tool that can do 80% of the work in 20% of the time, right? Find a story, find a pain point and say, hey Jim, I know how you hate going through monthly expense reports. And then you have to grab them, you know, grab all this information. You have to reformat it.
Jordan Wilson [00:37:54]:
You know, you have to open, you know, the, this, this sop, you know, compile a new document, you have to create a new spreadsheet, update all these rows and cells, create a PowerPoint for the board, blah, blah, blah. Here, look, this AI does this and I checked it, it's all correct, right? So you have to actually, number one, you have to know the right way to use large language models. If you're a novice, I don't think you can convince the naysayers. If you are a power user, if you're using large language models the right way, if you're going through a proper prompt engineering process like we each with pride, prompt polish. If you're using connectors and integrations, then yes, I think you find the use case, you find the pain point and you go solve that one thing that naysayer or the fence sitter absolutely hates and you do their job for them, right? If someone's not taking it seriously, that's what you should be doing. Yeah, you don't, don't, don't focus on job loss, don't focus on sprinkling AI on top. Unlearn an entire process, right? But one mind numbing task that someone hates because you could have, you know, an AI system do something great, something fancy, something shiny, it doesn't matter, right? You have to hit someone where it hurts. What does someone hate doing? You have to make it personal for them to show them the upside.
Jordan Wilson [00:39:21]:
All right, got a couple questions in and I'm happy for that. So as we wrap up, let me just say this. Using AI is not a strategy. Sprinkling AI on the top of current processes is not going to keep your competitors from lapping you. Simply using large language models is not going to help you win new customers in the future. Someone smaller or bigger is going to squash you. If that is how you're actually still using generative AI in large language models today. You have to understand the AI.
Jordan Wilson [00:40:13]:
The AI you have to understand AI is just the Internet. Everyone's using it. If your company, if your department is using AI, that is not a strategy. That is a basic requirement. That is the electricity. Now you have to use that power and go do something with it. And please stop just slapping AI on something and pretending it's special. It's not.
Jordan Wilson [00:40:44]:
I hope this was helpful. If so, please let me know. Repost this. I don't know if you don't want any more gripey old man Jordan shaking his fist at the digital cloud. Tell me. I just felt I needed to get this off my chest, all right? And kind of set the record straight. As someone that talks AI every day I get to talk to a bunch of smart people. You know, my email inbox is flooded with, you know, people saying, we're innovative, we're doing this, we're doing that.
Jordan Wilson [00:41:08]:
No, I need you to say, I need you to understand. Repeat after me. AI is the Internet. Just using AI is not a competitive advantage. Thank you for tuning in Podcast audience. Please make sure to subscribe and leave a rating. I'd appreciate that. If you're listening on the live stream, appreciate that as well.
Jordan Wilson [00:41:26]:
Love being able to interact with you all. And if you haven't already, please go to your everydayai.com Sign up for the free daily newsletter. We're going to be recapping the main points and more from today's show as well as keeping you up to date with everything else that you need to be the smartest person in AI in your company or department. Thank you for tuning in. Hope to see you back tomorrow and every day for more Everyday AI. Thanks, y'.
