The AI Gold Rush Is Dead. Corporate AI Is A DELUSION.

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0:00AI isn’t taking your job because it’s cheaper.

0:03That’s a lie. In many cases,

0:04replacing you with AI costs hundreds of thousands of dollars more than your salary… and Wall Street

0:10knows it. So, why is this happening? Because right now, there’s a $1 trillion

0:15hole in the global economy caused by executives making decisions under what experts are calling

0:20a kind of mass AI delusion triggered by a $20 chatbot. And it’s leading to one thing…

0:28CEO’s are replacing humans with AI… and it’s backfiring.

0:32Chapter 1: The Sycophancy Trap Business leaders know what they want. That’s how

0:37they got to the top. They have more money, more power and more confidence in their own judgment.

0:41And that’s exactly where the problem begins. By the time they reach that level, they’re already

0:46used to “yes men.” People who don’t challenge them. People who don’t question decisions.

0:51Now imagine giving that environment a tool that never argues back. That never questions them.

0:57At first, it feels ideal.

0:59AI creates a dopamine hit disguised as intelligence. A quick boost to the

1:03ego. Every question gets a confident answer. It’ll very rarely disagree. It

1:07can usually be counted on for positive feedback, and it can be customized to

1:12whatever your interests are. Instead of talking with people outside the computer,

1:15users stay inside a closed loop of validation. Conversation after conversation happens with

1:21no real resistance on the other side. Soon, they start to think of the AI as foolproof,

1:26relying on its wisdom as some sort of collective, a virtual Oracle without checking other sources.

1:32And it can be dangerous.

1:34Researchers at Aarhus University in Denmark examined patterns of AI use,

1:38and came to a disturbing conclusion. People struggling with mental illness not only were

1:44vulnerable to influence from AI, but could display worsening symptoms after interacting

1:49with AI chatbots. They studied the records of 54,000 people with diagnosed conditions,

1:55and found dozens of cases where patients suffered from worsened delusions and harmful behaviors.

2:01And you get what you put into it.

2:03And when there are billions of dollars on the line, that can have serious consequences.

2:07The CEOs who are replacing their workers with AI, ironically,

2:11are likely getting their advice from… AI. The technology has been integrated into companies

2:16long before the ax falls on the first workers. And the CEO is sitting in his corner office,

2:22asking his chatbot for advice - and getting back encouragement to keep investing in AI.

2:28This creates a delusion loop that helps no one besides the AI. The CEO gets the

2:33dopamine hit from the AI agreeing with him, and invests even further as a result.

2:38And the end result might be the biggest capital misappropriation in human history.

2:43Across the tech world, AI investment is in full swing. And while there are several major

2:48AI companies seeking to take advantage, it helps to be the first. The biggest gun in the AI world

2:53is still Sam Altman’s OpenAI. The company continues to cut massive deals with other

2:58companies to the tune of $1 trillion so far. Most of this is still planned investments,

3:03but it’s a level of trust in this new technology that’s unheard of.

3:07This kind of money is huge even for Silicon Valley.

3:10There are only 15 companies with a trillion-dollar market cap and

3:14only one that has reached the $5 trillion point… Nvidia. Its GPUs and semiconductors have become

3:21the backbone of the AI boom. And that changes everything.

3:24Because as major companies race to build the future of artificial intelligence,

3:28two names keep appearing in almost every major deal. OpenAI and Nvidia.

3:33One supplies the intelligence, the other supplies the hardware.

3:36And if all that investment plays out, it’s going to make a lot of people unfathomably wealthy.

3:42How much is a trillion dollars? It’s roughly the cost of building 10 International Space Stations.

3:47This total AI investment alone is larger than the market cap of many big tech companies. Amazon,

3:53Microsoft, Meta, and other big names dropped heavy investment into AI in 2025, and so far,

3:59according to one of the biggest names in economics, it’s contributed… nothing.

4:04Now, people are starting to get worried.

4:06Chapter 2: The Trillion Dollar Hallucination

4:09The warning bell is ringing.

4:11Goldman Sachs is one of the most trusted sources for economic and investment news, and they’re

4:15sounding the alarm. According to Harvard economics professor Jason Furman, while the data processing

4:21sector of the economy is only 4% of American GDP, it accounted for 92% of GDP growth in the first

4:28half of 2025. It’s the only area where the economy is actually growing. That means every other

4:35business is helping AI grow, but AI isn’t lifting those other sectors with it… at least not yet.

4:41And everyone is watching the stock market very carefully.

4:45If AI is getting heavy investment, but so far hasn’t resulted in any boost to the US GDP,

4:50how long is the golden goose going to last? Goldman Sachs didn’t outright

4:55say that AI is a bad investment, but did encourage caution. They didn’t

4:59think AI would have a significant impact on the economy until 2027.

5:03But if people start to lose faith, things could unravel… fast.

5:07Savvy investors are starting to warn about a possible AI bubble and the circular wave

5:12of investments simply stops. Stocks take a dive, and all the other companies that

5:16are now heavily invested in its success go with it. In the worst-case scenarios,

5:21people worry this could result in a massive market crash. Because right now,

5:25the AI economy is just a massive wealth transfer from one tech company to another.

5:30And it’s not even staying in the US economy.

5:33Without the energy generated by data farms, large parts of the internet could be taken down by heavy

5:38AI use. While it might seem the same as asking a search engine, a ChatGPT query can use at least

5:4410 times as much electricity and as much as 60 times, depending on the task. And with sites

5:49like Google now incorporating AI into their search engines, the demand is constant. All

5:54this increases the demand for data centers. These are straining power grids in wealthy nations, with

5:59the human labor required to train these models is quietly outsourced to lower-income areas overseas

6:05Which has a lot of people asking: who’s benefiting?

6:09The technology isn’t growing the economy right now. To many people,

6:12it feels like a financial house of cards - with every investment going to a new

6:16technology that no one is sure will be a long-term game-changer. It could wind

6:21up being a curiosity. It could wind up hitting a singularity that could put us

6:25all in danger. Or it could revolutionize the economy in a way that no one could predict.

6:30In one way, it already has. Because the companies

6:33are already acting like this is the future and there’s no going back.

6:37And a whole lot of people are losing their jobs.

6:40Chapter 3: The Efficiency Lie

6:422025 was the year when the AI job layoffs hit home, and it became a dark year for the

6:48tech sector. According to consulting firm Challenger, Gray & Christmas,

6:52there were 55,000 layoffs in the US directly attributed to AI investments. However,

6:57that was only a small percentage of the overall layoffs. Approximately 1.17 million,

7:03the worst number for jobs since the Covid-19 pandemic shuttered large portions of the economy.

7:08There’s a real human cost to the decisions the companies are making right now.

7:12And it might not be slowing down any time soon.

7:15Amid the worries about mass layoffs, Goldman Sachs issued a blunt warning in April 2026

7:21for the workers being pushed out by AI: don’t expect it to be an easy road back. They stated

7:26that these workers might face a long search to secure a new job in their current field,

7:31with the odds being that it will pay less and have less-desirable

7:35conditions than the one they left. The field of available jobs is shrinking all the time,

7:39as companies seek to put AI to work for them to save money.

7:43All AI investment right now is, essentially, a bet on a future that

7:47hasn’t happened so far. Companies talk about AI becoming as smart as people,

7:51being able to do tasks in seconds that would take humans hours to accomplish.

7:55But right now, AI is imperfect… and costly.

7:59The technology is a massive energy-eater. As of July 2025, ChatGPT was processing around

8:052.5 billion queries per day, with Gemini and other AI portals dealing with similar

8:11traffic and using the same technology. That requires the energy use of roughly

8:15a full nuclear reactor to keep them running daily. To train the next generation of models,

8:20supercomputer data centers will require the energy use of up to 10 nuclear reactors each day.

8:26Data centers burn round the clock to keep these services up and running,

8:30and the demand only grows as companies incorporate it in more and more services.

8:34And few of them actually work.

8:36For the average person, AI looks impressive. But behind the scenes,

8:40there are still serious problems. The technology isn’t actually thinking. It’s a predictive model,

8:45pulling from other sources. Companies have been criticized for posting flawed AI art

8:49with glaring errors, and AI-generated text has been found to be riddled with errors,

8:54requiring the use of editors to ensure it passes muster. So companies put all

8:59this investment into AI, only to have to fall back on people anyway.

9:03Despite that, the investment isn’t slowing down.

9:06In fact, it’s quite the opposite.

9:07In the past, CEOs were often distanced from their product and could see its flaws. Famously,

9:12Mark Zuckerberg said he wouldn’t allow his children on social media until they were

9:17teenagers. But in the case of new AI technology, that’s often not the case. AI CEOs have access

9:23to new AI agents before the general public does, and they don’t just interact with them,

9:28they get pulled in by them. They become their first true believer. And once they’re that

9:33deep in with their new pet project, it’s very hard to pull them out of that orbit.

9:38They know this… but it’s not stopping them.

9:41Chapter 4: Psychosis In The Corner Office

9:44Garry Tan, CEO of Y Combinator, has been involved at many of the biggest tech companies over the

9:48last few decades, and he’s all in on AI. But he wound up in the news recently for popularizing

9:54a new term: Cyber Psychosis. It’s something that emerges when people spend too much time chatting

10:00with AI. But Tan wasn’t warning of it. He was describing himself in gleeful terms. He described

10:06how he was so excited to work with AI agents that he was only sleeping 4 hours a night. In the past,

10:11he relied on the sleep-prevention drug modafinil to survive grueling startup hours. But now,

10:17he doesn’t even need to pop pills because the AI provides him with so much energy.

10:21Tan’s public display of faith in AI, in which he publicly released some of the

10:25code that he was developing on Anthropic’s Claude, was seen as one of the most dramatic

10:30displays of how AI affects the mind. He has been working with AI prompts extensively,

10:35and the more exposure someone has to the technology, the more they are prone to believing

10:39they’ve created something truly revolutionary. In fact, there’s even a term many of them use - “God

10:45Mode” - where they believe they’re getting closer to that fabled singularity of truly autonomous AI.

10:51But under the hood, it’s a lot more fragile.

10:54Ultimately, AI is based around a series of text prompts. The more complex the prompt workflows,

10:59the more precise AI appears and the more complex tasks it

11:02can accomplish. But each feature relies on a highly structured series of code,

11:06and none of the current technology approximates the actual process of a thinking mind. However,

11:12the more time a CEO spends with their own technology, the more it appears to be otherwise.

11:16Anecdotal reports from people working in the tech industry report that Cyber Psychosis is

11:21increasingly common as the development of the technology speeds up and the arms race escalates.

11:27But success is hard to achieve… and even rarer.

11:30In late 2025, an MIT study looked into the state of AI in business,

11:35and examined 300 public implementations of the technology. It was well-known that the

11:40technology was still in an early state, but the news was bleaker than anyone expected.

11:44It found that the vast majority of AI enterprises were still not profitable. Only 5% of integrated

11:51AI pilots showed any significant impact on company profit, and the vast majority

11:56never even reach the phase where the public can have a say on whether they work or not.

12:01In fact, most never get off the ground at all.

12:04The vast majority of successes in AI are geared towards individual consumers. ChatGPT and Gemini

12:09are used by millions of people a day, but most users are free users. Only a small percentage

12:15are paid subscribers. These AI services do most of their businesses by partnering with other

12:20companies, and those companies then develop ways to incorporate the technology into their services.

12:25But while 60% of companies evaluate tools, only 20% of those take the project to the pilot stage.

12:31And only 5% make it to the final stage and are deployed on the production or service line.

12:37That means the vast majority of money invested in AI just…fades away.

12:42Right now, the entire AI economy is balancing on the head of a pin. The investments keep coming,

12:47because the companies spearheading the roll-out have convinced other companies that they’re

12:52the future. It doesn’t make sense for most companies to try to develop their own AI tool,

12:56so they fall back on working with one of the established big guns like OpenAI.

13:01But those investments haven’t delivered dividends for most of these companies yet.

13:05The bills keep racking up, and the layoffs keep hitting their employees.

13:09And it may all be about to hit critical mass.

13:12If 20 revolutionary projects are announced, and 19 of them wind up in the garbage can,

13:17that’s not sustainable. If AI continues to fail to deliver for its clients, the tech workers laid

13:22off might not be the only ones out of work. Investors are watching nervously. Meanwhile,

13:27laid-off tech workers are watching hopefully that the bubble might be about to burst.

13:32Which might not be that far off.

13:34Chapter 5: The Great Reversal

13:36There will always be early adopters, and most of the companies to adopt AI most aggressively have

13:42been tech based. But that makes them test cases… and those tests don’t always work out. Klarna,

13:48the digital bank and financial services company, was ahead of the curve. Its CEO,

13:52Sebastian Siemiatkowski, was confident in 2024 that AI could take over many human jobs.

13:59It was a good test case, because many of its functions are very repetitive and predictable.

14:04Then the ax started to fall.

14:06The company froze hiring for over a year. Its workforce was heavily slashed by almost 40%,

14:11dropping from 5,500 to 3,400. Their replacement? An AI chatbot who was

14:18supposedly doing the work of over 700 customer service agents, handling hundreds of financial

14:23transactions simultaneously. It was one of the first big tests of whether AI could actually

14:28take over mass numbers of jobs. The results soon started flowing in from Klarna customers…

14:33And they were not happy.

14:36The chatbot performed simple tasks fine, but it couldn't deal with complex issues.

14:40Customers grew frustrated and lacked trust in the company. It was one of the biggest

14:44embarrassments for a tech company in the new AI era. Klarna was soon forced to reverse

14:49course. Having laid off most of their customer service staff, they were forced

14:53to quickly pivot and train their other staff to handle these positions until they could rehire.

14:58That led to the spectacle of engineers and marketing staff answering customer calls

15:03and they might have done a better job than the automated version. It’s a pattern that’s

15:07been happening across the board. Companies that invested in AI are starting to perform u-turns.

15:12The only question is how low it can go.

15:15The tech research firm Forrester has been studying the shift to AI over the last few years,

15:19and their forecasts have rarely been positive. They’ve studied how unready employees are to

15:24adjust to the new AI paradigm, as well as how employees aren’t benefiting from the shift yet.

15:30But now they’re ready to make a big prediction. Companies have been firing employees en masse,

15:35hoping to replace them with AI, but that’s left them without the braintrust they need to know

15:40how to use new technology effectively. That’s like an airline firing the pilot to save money

15:45on cargo weight, and then realizing they need someone to fly the plane.

15:50So all those employees looking for new jobs… might want to look where they started.

15:55Forrester predicts that not only will many of these companies need to hire more humans,

15:59but that half of all AI-related layoffs will be reversed by 2027. 55% of employers

16:05already regret the decision to cut staff. That might put the axed staff back in the

16:10driver’s seat. These are people who built much of the modern tech infrastructure,

16:13and were forced out. And now, in order to avoid disaster, those same brains

16:18are needed to reverse the slide. Assuming that the CEOs know when disaster is about to occur.

16:23That’s the big x-factor in the current AI paradigm.

16:27AI hasn’t become profitable yet. It hasn’t made itself indispensable for the companies. But it

16:32has done an amazing job of convincing people it has - from the people pumping dozens of

16:36queries into ChatGPT a day, to the CEOs in the suite vibe-coding the next innovation. They’re

16:42primarily getting feedback from the AI, and it’s continuing to tell them everything is great. They

16:47keep investing, the numbers on the stock tracker keep going up, and so do the dopamine receptors.

16:52It’s all great… until it isn’t.

16:55Right now, the most likely outcome is that people fired for AI will be

16:59in the driver’s seat. The company needs their expertise, and they’ll be able to

17:03negotiate a new salary when they come back. Analysts know this is necessary,

17:08the CEOs might not. There’s a lack of leadership at the top right now, with some of the smartest

17:12people in tech taking their guidance from chatbots they coded themselves.

17:16And they might just keep doing so…until the whole house of cards comes crashing down.

17:21But it raises a much bigger question.What happens when that same tool moves beyond

17:26tech companies and into systems where the stakes aren’t profits, but consequences? Find out the

17:31terrifying truth in “AI Played a War Game. It NUKED Everyone”, or watch this video instead.

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The AI Gold Rush Is Dead. Corporate AI Is A DELUSION.

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