EP 597: Do 95% of AI Pilots Fail? Why You Should Ignore MIT’s Viral New AI “Study”

Topics Covered in This Episode:

1. MIT AI Study Claims 95% Failure Rate
2. Breakdown of MIT Study Methodology
3. Impact of Viral MIT AI Study Headlines
4. Flaws in MIT Study ROI Measurement
5. Comparison With Reputable AI ROI Studies
6. MIT Study’s Biased Participant Selection
7. Nanda Project Marketing in MIT Report
8. Five Major Red Flags in MIT AI Research
9. Business Implications of Flawed AI Pilots Data
10. How Media Sensationalizes AI Study Results

Keywords:

MIT AI study, 95% AI pilot failure, enterprise AI pilots, generative AI ROI, AI pilot success rate, AI project failure, state of AI in business, GenAI divide, MIT Media Lab, AI investment, AI implementation challenges, AI return on investment, AI research methodology, AI study critique, AI marketing, Nanda project, AI vendor solutions, agentic web, MCP protocol, A2A protocol, Fortune article, AI media coverage, stock market impact, NVIDIA stock drop, Palantir, ARM stock, qualitative AI data, AI structured interviews, AI industry surveys, IDC AI research, Snowflake ESG report, McKinsey AI analysis, Microsoft Work Trend Index, Boston Consulting Group AI study, AI adoption rates, enterprise AI transformation, sample size in AI studies, research limitations, AI productivity impact, AI workflow automation, AI business decisions, AI bubble, AI reporting in media, AI pilot timeline, enterprise AI tools, AI agent capabilities, AI autonomy, custom AI solutions, AI study bias, marketing disguised as research, sensationalized AI studies.

Podcast Transcript

Jordan Wilson [00:00:17]:
Do 95% of AI pilots actually fail? Absolutely not. But if you've been paying attention to the business world, the media or AI LinkedIn or AI Twitter, you might think so. That's because a recent MIT study said exactly that that 95% of enterprise AI pilots show zero ROI and therefore they fail. But that study itself is actually a failure. So I'm going to be kind of nicely tearing it apart on today's episode of everyday AI and showing you why you should all but ignore MIT's viral new AI study and actually how its misconceptions can play to your advantage. Alright. I'm excited for this one. I hope you are too.

Jordan Wilson [00:01:12]:
Let's get into it. If you're new here, welcome. My name is Jordan Wilson, and this is Everyday AI. This is your daily live stream podcast and free daily newsletter helping everyday business leaders like you and me not just make sense of what's happening in the world of AI and keep up, but how we can use it, actually dissect it and understand and separate the marketing from the BS from the real, and how we can use this information to get ahead to grow our companies and our careers. Starts here with the unedited, unscripted live stream podcast, but if you wanna take it to the next level, that happens on our website, youreverydayai.com. We're gonna be recapping today's, podcast in today's newsletter, but also keeping you up to date with all the other AI news. So if you want that, make sure to go check the newsletter. Alright.

Jordan Wilson [00:01:54]:
So let's just start dissecting. It's hot take Tuesday, y'all. So, yeah, almost every single Tuesday, we do a hot take on something that's happening in the AI world, and nothing has been bigger than this study, which says a lot. It's usually not a study, from MIT, nonetheless, that grabs all the AI headlines. Right? When Google's releasing this and, you know, Elon Musk is suing everyone that walks, this is the thing that grabbed the most headlines, and, let's just go ahead and preview a little bit what we're gonna be going over today. We're gonna be going over the findings of this now mega viral MIT study that claimed ninety five percent of AI pilots fail. We're gonna uncover why it was an abysmal study that was actually just marketing in disguise, show you what real reputable studies actually say about GenAI return on investment. I'm gonna give you the five biggest red flags of this study, and I feel weird calling it a study, and I'm gonna expose how this was actually just marketing for an MIT project.

Jordan Wilson [00:02:57]:
Alright. And this isn't on repeat. Yes. I did have to tear apart a different ill conceived m I study, MIT study before, their brain rod study. So, yeah, if you didn't hear that one, go listen to that episode five fifty three. So this viral study was called the state of AI in business 2025, what they called the GenAI divide. This is done by a, group out of MIT. And like I said, the study went viral overnight.

Jordan Wilson [00:03:27]:
It started with a Fortune article. The study itself was actually in July, was released in July. It wasn't until August 18, that Fortune picked up the story. And within hours, literally, almost every single big publication that I knew was covering it from the economic times and Axios, to the hill and Forbes. Right? Just about any big online publication covered this story, and, unfortunately, many of them just copy and pasted that attention grabbing headline. Ninety five percent of AI pilots fail. So here's kind of what happened and what unfolded. So like I said, in July, MIT released that report that show that 95% of enterprise GenAI pilots showed no measurable GenAI, gain.

Jordan Wilson [00:04:16]:
And despite, the company spending 40 to, 30 to $40,000,000,000, on AI. So like I said, the Fortune article dropped on August 18, and that really started the media storm. The findings kind of also spooked investors. I'm not gonna get into that. I think plenty of people have covered this on the financial side, and it wasn't the only thing happening. Right? There's been a lot of talk on this AI bubble, some things happening with the Fed, some interest rate nudes. But this was also one of the things that really, caused the stock market to lose hundreds of billions in dollars in, in market cap. So NVIDIA fell by three and a half points, ARM fell by, almost 4%, Palantir, nearly 9%.

Jordan Wilson [00:05:02]:
Right? This is one of the things, that a lot of, investors pointed to as one of the reasons why. But smart people who actually read the entire study realized after all this media storm had, kind of come and gone and the dust had settled, wait. This study's absolutely terrible. Like, why is no one talking about that? And there was actually had to been some follow-up articles from all these media publications that kinda got, spoofed. Right. And they're like, oh wait, we probably should have read this a little more closely, but don't worry. That's what I'm here for. So here is the executive summary from MIT's findings.

Jordan Wilson [00:05:42]:
All right. So I'm just gonna read the first, sentence or two. So they said, despite 30 to $40,000,000,000 in enterprise investment into GenAI, this report on covers a surprising result in that 95% of organizations are getting zero returns. Alright. The outcomes are so starkly divided across both buyers and builders that we call it the GenAI divide. Brilliant. Brilliant. Alright.

Jordan Wilson [00:06:08]:
Oh gosh. Livestream audience. I gotta take a sip. Should I it's hot take Tuesday? Should I just burn all bridges or should I be kind of nice? Let me know. Personally feeling a little spicy. We'll see. So a little bit more on these findings, and, yes, I'm putting findings in quotes. So, a little actually, no.

Jordan Wilson [00:06:37]:
Let's let's skip forward. Because before we get into those findings, I want to talk a little bit about my background. So you understand. So, if you're brand new to the show, some of these things I've shared, some of these I haven't. So I've interviewed hundreds of people on the everyday AI podcast. You know, we're, almost at episode 600 here. So I've interviewed hundreds of people on the quote unquote air, and I've had thousands of conversations outside, obviously, outside of the everyday AI show. I've been doing this for almost three years every single day.

Jordan Wilson [00:07:12]:
This is all I do. Formally, I was, an award winning journalist. So, won some awards like ACP store of the year, Pulitzer fellow, etcetera. That's important. I'm gonna explain why. Also an important part about my background. I spent six years earlier in my career. Literally my job was reading and manually recapping studies.

Jordan Wilson [00:07:35]:
Thousands of them. Let me repeat that before this whole AI thing. Now this is what AI did. I used to have to read and take notes and annotate thousands of just boring studies. So keep that in mind. Talk about AI all the time. I've had thousands of conversations on AI and for a big chunk of my earlier career, all I did was read and recap studies. And I also want to put this in, on the record.

Jordan Wilson [00:08:09]:
I'm not against this study because it's anti AI, right? Like, oh, Jordan, this ruins your narrative. You're talking about AI. I could care less. Right. People always think, oh, I'm anti AI. No. I'm I'm not. Or or people think I'm like pro AI.

Jordan Wilson [00:08:22]:
No. This is just the direction that the world is heading. Right? Not like a huge AI, whatever they call them, you know, accelerator. Right? Like, I think it would be better if the pace of AI would slow down a little bit, right, to allow people to catch up, but it is what it is. But I want you to know, I'm not against this study because it seems anti AI. AI I'm against this study because it is anti intelligence. No one, no one that is an intelligent person. We'll read this front to back.

Jordan Wilson [00:08:58]:
Maybe unless you work at MIT, we'll read this study front to back and be like, yeah, this is sound. Yeah. Let's put this out. No, this, this is one of the worst studies I've ever read. And I've read a lot. So let's first talk about the testing methodology. All right. Oh my gosh.

Jordan Wilson [00:09:17]:
I'm laughing. Okay. So they used, 300 publicly disclosed AI initiatives. So they didn't say what those sources were, but presumably, right? They're looking at, filings from public companies, you know, the big tech companies building AI earnings calls, press releases, etcetera. So they didn't disclose what those publicly disclosed, AI pieces were, but presumably that's what they are. They had 52 structured interviews with executive sponsors and frontline users, and they surveyed, sorry. I wish this was a typo. I checked so many times that this wasn't a typo.

Jordan Wilson [00:09:56]:
They surveyed a 153 senior leaders. Oh, gosh. Another big bone that I had to pick is, like, you couldn't just go and get this study. It's almost like they really were gatekeeping it for some reason. You had to go fill out a Google form. I never got this. Luckily, people who got access to this study shared it online because they just weren't sharing it. Like, who puts out a study? And you gatekeep it, and you're like, nah, you're not gonna get it.

Jordan Wilson [00:10:23]:
Anyways, this it's laughable. Right? If you couldn't tell in my voice, the fact that they put out a study, this resounding, this, with, with this much emphasis that got so much play in the media. And then you read the notes and you're like, they surveyed 153 people. I could have done better. Right. I think I did a LinkedIn poll on this very topic yesterday, and it got like twice the number, like twice the number of responses. That doesn't mean I should go write a study. Right? We could have done better.

Jordan Wilson [00:10:58]:
We have a bigger audience. We could have, maybe I should, but that's not even the worst part. That's not even the worst part, how laughably small this was. You know, it's almost like walking into a bar and just asking random people about AI and then writing a 32 page study about it, or however many pages this was, Most people wouldn't know because they couldn't get their hands on it because you really gotta be able to find this study. How many pages was this thing? 26 pages. Right? Yeah. So it's kind of like walking in a bar, asking a couple of people about AI and deciding to write a 26 page paper on it. The 95% failure stat and how they got to that is actually even worse than their terrible methodology.

Jordan Wilson [00:11:42]:
Okay. So again, let me repeat a little bit about what this 95% failure rate stat was and tell you how they got to it. So they said that 95% of organizations are getting zero measurable financial return despite, you know, tens of billions of dollars of GenAI investment. So the study to find zero measurable measurable financial return as the point where the vast majority of integrated AI pilots remain stuck with no measurable P and L impact. Yeah. Profit. We're talking profit and loss statement. That's how they're measuring it.

Jordan Wilson [00:12:13]:
Alright. Okay. So the ROI impact was measured six months post pilot. Yeah. Six months, meaning zero ROI indicated no measurable financial return within that period. So this 95% failure rate was primarily concluded though. From the 52 structured interviews. It wasn't from the, Yeah.

Jordan Wilson [00:12:41]:
So it, it, it wasn't from the, you know, the 300 public documents or the 153 senior leaders they interviewed, are are surveyed. This was from the 52 interviews. Alright? And these figures, according to MIT were directionally accurate based on individual interviews. So they derived that ninety five percent failure stats from these 52 conversations. Right. I had a busy, busy week of interviews a couple of weeks ago. Like I talked to more than 52 people anyways. Let's talk about what that means and read some of the fine, some of the fine, print here.

Jordan Wilson [00:13:28]:
So this is from MIT's study, which you have to be, a Sherlock Holmes to find. So in the research limitations, it says these figures are directionally accurate based on individual interviews rather than official company reporting sample sizes, very bad category and success definitions may, differ across organizations. Then they also put in this section on the next page on the research note, we define, so talking about the 5% success rate, the flip side of the 95%. So they say we define successful implementation for task specific GenAI tools as one's users or executives has remarked have remarked as causing a marked and sustained productivity and or P and L impact. The 95% failure rate for enterprise a solutions represents the clearest, manifestation of the GenAI divide. So in other words, that 95% it's, it's directional accuracy from 52 organ, from 52 interviews. So it means that that figure indicates a general trend or scale, but it is not precise. They are not audited numbers derived from formal company reports or, simple, you know, before after survey.

Jordan Wilson [00:14:47]:
It's just from conversations, and they are kind of the ones that are dictating something by their, ability to decide on the directional accuracy. So the researchers say that they're confident in the direction of their finding that successful implementation rates for custom, enterprise AI tools in these pilots are very low, but they also acknowledge that the exact percentage is an estimate based on gathered qualitative data, not quantitative data. That is terrible. Who approved this? Who approved this study? Did no one outside of this little group look at this study and be like, nah. Someone's gonna laugh at this. Yeah. Smart AI people are laughing at this. Right? Go, you know, I'm I'm I'm sure there's if if if you follow other AI sources, like actually smart people, academics, they're laughing at this.

Jordan Wilson [00:15:45]:
Right? They're saying, yeah, this isn't a real study. So this is, this one headline that's been setting the business world and the AI world on fire was essentially a vibe study. Right? We talk about vibe coding. It's directionally. Yeah. That's accurate. 95% based on some interviews. But it's I'd say it's more marketing for MIT's Nanda project.

Jordan Wilson [00:16:12]:
That's what I think, but more on that, in a couple of minutes. But that's not what a real study looks like. Talking to 52 people and, taking some, direction from them and being like, yeah. We feel confident, on this qualitative, data. So let's go ahead and mark it up. That's not what a real study looks like. This is what a real study looks like. Alright? So podcast audience, have a couple, have a screenshot here on my screen.

Jordan Wilson [00:16:43]:
I'm gonna walk you through it. So I have different studies, from 2025, from reputable organizations, their key finding in the survey details. See if you can find a difference here. Alright. So the MIT Nanda or MIT Media Lab survey that we're talking about here said 95% of organizations get zero return from generative AI. Alright. And that's from talking to 52 people. Right.

Jordan Wilson [00:17:12]:
But in the survey or sorry, in the study, they also had the 153 people surveyed, the 52 interviews and then the 300 AI initiatives that they, discovered or used. Right. Okay. Here's what real studies look like. The international data corporation. This is weird. The international data corporation, one of the more reputable organizations in the world. I cite them a lot on this show because they put together real research.

Jordan Wilson [00:17:44]:
They surveyed 4,000 decision makers and they found that there's an average ROI of $3.70 for every $1 invested in GenAI. That's weird. Dollars 3 and 70¢ is a pretty freaking good ROI, but MIT says 95% get zero. That's not adding up. Let's look at more. Snowflake and ESG, talked to 1,900 business and IT leaders. They said that 92% of early adopters are seeing a positive return of, return on investment on AI. Very different from MIT.

Jordan Wilson [00:18:29]:
One of the biggest management consulting companies in the world, said 97% of senior leaders investing AI report experiencing positive ROI. Okay. McKinsey, they're legit. They're real. 92% of companies plan to increase their investment. You wouldn't do that. You wouldn't get 92% of them increasing their investment if 95% of them were getting zero return. Alright.

Jordan Wilson [00:18:58]:
The Microsoft work trend index. Great report. One of the best out there by far 31 is surveyed 31,000 professionals. And it said 66% of workers report measurable business benefits from AI. Then you have the Boston consulting group there. BCG AI at work study said that 75% of employees see value in momentum from AI that's from a survey of 10,600. Even just looking at the first couple IDC $3.70 for every $1 positive ROI, the study 97% of leaders said that they are seeing a positive ROI. It gets worse for this MIT study.

Jordan Wilson [00:19:41]:
Don't worry. So here's where it starts to get worse. Alright. There's a big problem. Right? The MIT study, they got all this, you know, all this positive momentum. Everyone's talking about it. Oh, no. The bubble's going to burst.

Jordan Wilson [00:19:59]:
What are we going to do? Generative AI is bad. What's the solution? MIT. MIT Nanda. All right. So that was on their cover. And then you can read about MIT Nanda, but I'll save you the time. All right. So this is from I kid you not.

Jordan Wilson [00:20:17]:
This is from MIT's report that hardly no one could get their hand on. All right. So from their conclusion, they said organizations that successfully cross the GenAI divide do3 things differently. They buy rather than build gosh, empower line managers rather than central labs and select tools that integrate deeply while adapting over time. Alright. And then they go on to say just as the original web decentralized publishing, publishing and commerce, the agentic web decentralizes action, moving from prompts to autonomous protocol, driven coordination systems like Nanda MCP and represent early infrastructure for this web, enabling organizations to compose workflows, not from code, but from agent capabilities and interactions. Then they go on to say next page for organizations currently trapped on the wrong side. The path forward is clear.

Jordan Wilson [00:21:19]:
Here's here's the marketing. Right? Stop investing in static tools that require constant prompting. Start partnering with vendors who offer custom solutions. Right? No one's heard of Nanda. Like the audacity for this report to just go from straight, like, oh yeah, we're, we're super serious. We're MIT. Right. Just copy, copy paste this headline, run with it.

Jordan Wilson [00:21:42]:
Right? And then at the end, we're just gonna go ahead and throw in this Nanda thing that hardly no one's ever heard of, but we have the audacity to put it next to MCP. Right? Anthropics protocol, and a to a Google's protocol. So they're like, all right. Yeah. Trust us. We know this study is going to get legs, right? Cause we have this bold claim that ninety five percent of GenAI pilots are failing and don't worry. The solution is stop doing this GenAI thing. Right? You gotta get to agentic web.

Jordan Wilson [00:22:12]:
And Nanda is the leader in agentic web along with MCP from anthropic and a two way from Google. I can't make this up. This is like one of those like punchlines that writes itself for Saturday night live for AI dorks like us. Yes. They literally went into like as seen on TV mode for organizations currently tracked on the wrong side. The path forward is clear. It's oh, gosh, it's no one at MIT is no one else that didn't work on this study, like hanging their head. Like I can't believe this happened or did no one just bothered to read past the headlines.

Jordan Wilson [00:22:51]:
There's more. All right. I'm going to give you five huge flat, huge red flags from this study. Right. And I actually just thought of an, an additional one, right? Pilots are precursors, Right? So if 95% of, AI pilots, failed and didn't show ROI, then why is 90%, of enterprise, Fortune 500 organizations using GenAI? Right? The math isn't mathing there. Right? Oh, if your pilot fails and it blows up in your face, you're not gonna use it anymore. Right? No. Alright.

Jordan Wilson [00:23:25]:
Anyways, five huge red flags from this study. Again, study in quotes. Number five, the absurdly short success timeline in ROI measured at six months when enterprise transformations take one to two years with archaic tools, trying to measure ROI on a GenAI pilot in six months, actual ROI? Nah, that's just setting up a study ahead of time that you know is going to fail. Here's another one. How about their microscopic sample for their gigantic claims? Right? 52 interviews, that that's what they used to get to their 95% of organizations. That's like talking to 52 people, one from, you know, each state and, you know, one from, I don't know, DC and some other territory and being like, yeah. We have a good now, representation of the entire USA. We talk to one person from each state.

Jordan Wilson [00:24:29]:
It's laughable. I would never put my name on this. Alright. Number three, it's contradicted by just about every single other real reputable peer research organization out there. I already gave you the examples, but like I said, recent studies show anywhere from, you know, mid sixties to ninety seven percent positive outcomes with samples that are 10 to 600 times larger. Right? So there's a reason MIT is a dramatic statistical outlier that's because they want you to get their Nanda, whatever that is. Also, they only recruited companies with problems. Another thing hidden in there, in their, report that no one could read.

Jordan Wilson [00:25:16]:
And they knew that they knew what people are only going to be able to read the headlines. So the study explicitly recruited organizations, quote, unquote, ready organizations willing to discuss AI implementation challenges. End quote. Talk about a biased pool of participants. Right? Yeah. Hey. Are you willing to discuss AI challenges? Organization? Yes. Okay.

Jordan Wilson [00:25:48]:
Let's let's have an interview. Do you want me to fill out a huge survey? No. No. I just wanna talk to you, and I'm gonna decide the direction of this one. So of course, you're going to find extremely high failure rates when you ask for organizations willing to discuss their AI implementation challenges, right? The, the hordes of companies, the, literally tens and tens of thousands of enterprise companies who are successfully, using AI. If they've looked at that, they'd be like, oh, well, no. We're good. And number one, the research quote unquote is actually again, marketing disguise as science.

Jordan Wilson [00:26:34]:
Yeah. Apple fell victim to this with their illusions of thinking research a couple of months ago, and MIT did it again. So Nanda, like they said at the end, hey. 95% of AI projects fails, but Nanda is the answer. You know, Nanda is in in line with MCP and a two way, right, from from Anthropic and Google, respectively. So Nanda is a project developed at MIT Media Lab, which charges reportedly $250,000 for corporate memberships to commercialize their agentic AI technology. So this study, you know, obviously identifies a learning gap problem, which was a, predetermined conclusion from the terrible, methodology of their study. And then it concludes that companies need exactly what Nanda sells as the solution.

Jordan Wilson [00:27:27]:
Right? So it's not research. This is an elaborate sales pitch. So why did this happen? Remember when I gave you my background earlier? I was a journalist. I used to read these studies for breakfast. But if it bleeds, it leads. It's the same thing in journalism. That's how AI research is now. People in AI research, they want to make a name for themselves, Right? Because now you have AI researchers getting NBA salaries, but this is how journalism works as well.

Jordan Wilson [00:28:04]:
Right? And I get it. And I feel for the journalists that kind of just blindly copy and pasted what they saw someone else write. I remember, right, being a journalist and, you know, you have two stories for that day and then a third one gets thrown on your desk this one. You're like, I I you know, like, I got thirty minutes to research this thing. So you read someone else's report, you retype it up yourself and you're like, oh, yeah. Yep. This checks out done. That's how journalism work.

Jordan Wilson [00:28:29]:
And unfortunately, this is how studies are working now. AI studies are becoming sensationalized. They are becoming marketing tools, which stinks, but that's where the money is. So just because you see a study, a research, even from a big organization, do not blindly believe it. Read it. Use your brain and research. And, yeah, unfortunately, I think this was, kind of pushed and fueled by the media. But it makes sense because right now, news organizations are getting crushed because of AI.

Jordan Wilson [00:29:06]:
They're getting crushed because people are using ChatGPT and Google's AI mode and perplexity instead of going to their websites. So they need clicks at all costs. So when they get a story like this and someone, you know, from tech blog1.com throws the fortune article and says, we need this in, you know, an hour, they're gonna put it up there. They're gonna say ninety five percent of AI fails. Ninety five percent of AI fails. Copy, paste, copy, paste, copy, paste. I literally showed it on my screen. Even the headlines were essentially the same.

Jordan Wilson [00:29:34]:
So they need clicks and journalists are overworked and underpaid, but just as bad, just as big of the reason is why this thing spread like wildfire is because you had people out there not even reading the study yet, Reposting and perpetuating the same claims. Right? I like, my feed was littered with with with people that I knew didn't read the study. Right? Because if you read the study and if you have a brain, you have an opinion probably somewhat similar to mine. Maybe mine's a little too hot. Right? But anyone is gonna read this and be like, yeah. This isn't a real study. Okay. So why is this mad? Why did you just waste thirty minutes talking about this? Well, and what should you do about it? Why does this matter? Well, number one, don't just take my word for it.

Jordan Wilson [00:30:30]:
Go read the study. Right? And read all actual studies that you care about or impact you. Right? If you're gonna believe something or use it as a decision, to potentially make a decision for your business, go read the actual study. Don't read the media reports, social media. Most of it is rubbish like this MIT study was. All right. Also, if there's anyone out there, you know, maybe it's someone in your workplace, maybe it's someone you follow online, maybe it's a newsletter you subscribe to. If anyone is just blindly parroting these points, ignore them.

Jordan Wilson [00:31:04]:
Right? And if this comes up as a discussion around AI implementation at your company, you need to educate people. Right? You don't need to send them my podcast, or I'm not gonna tell you, go promote my stuff, but just go be like, hey. Here's the study. Go read it. It's 26 pages. Takes an hour. It's an hour of analytical thinking. And here's the thing and why this is important.

Jordan Wilson [00:31:29]:
Yeah. We talked about, hundreds of billions of dollars of fluctuation, on the stock market, but more than anything, this is impacting real organizations, real companies' AI efforts. And that's what I want to end with. This study is going to cause more fence sitters, right? People that were, yeah, we, we, we have our AI pilot and they're gonna be like, oh, look at this study. Let's cut it. Or we're not gonna extend it. Or we're not gonna go from pilot to production. Nope.

Jordan Wilson [00:32:05]:
It ends here. There's literally gonna be probably hundreds or maybe more of large enterprise organizations that are just gonna read the headlines. They're just gonna read the social media posts. Right? And they're gonna make their decision on that. And they're gonna say it's not worth it. This is a bubble. It's gonna burst. We gotta stop.

Jordan Wilson [00:32:24]:
Look at this MIT report. Don't fall victim to that. Take advantage. So much of what's happening in the AI business world right now, it's first mover's advantage, right? That's long gone by now, but now you're going to have some new fence sitters. You're going to have some companies that maybe had successful pilots, but just didn't know how to measure ROI. And they're going to be like, oh, well, it looks like it didn't work. Take advantage. When others pause, you can go forward.

Jordan Wilson [00:32:59]:
I hope this was helpful. Y'all, so no 95% of AI pilots don't fail. But 95% of people who believe this study, I wouldn't be trusting them with business decisions. And, you you know, 95% of people who actually believe just the headlines, I wouldn't I wouldn't just let's let's end it there. Alright. But actually, no, it's not ended there. So if you repost this story, there was so much I couldn't get to. My goal was to keep this hot take Tuesday, under thirty five minutes.

Jordan Wilson [00:33:31]:
So I'm gonna make it there. Alright. But there was so much information that I couldn't include. I literally had so much research, so many notes. I literally made a small little website, inside, Google Gemini Canvas with so much more information that I literally just couldn't get to. Alright. So if you want access to that, and that includes that chart, that you should probably show your organization. Right? Don't spend ten hours going to find, all of that information.

Jordan Wilson [00:34:01]:
I'll just give it to you. So go repost this, on LinkedIn. So if you're listening on the podcast, thank you for your support. We always put in our show notes, the LinkedIn post, so this goes live, live on LinkedIn. So just click that repost, and I will share, this long website with you as a resource. So make sure you go do that. And then after that, if you haven't already, make sure you go to youreverydayai.com. We're gonna be giving you the too long didn't read version of today's show, but I hope it was helpful.

Jordan Wilson [00:34:31]:
So thank you for tuning in. Hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.