Everyone’s Pretending to Understand AI Stocks While Throwing Their Life Savings at Anything With “AI” in the Name

Why NVIDIA Is Worth More Than Canada’s GDP, How Every Company Became an “AI Company” Overnight, and What Happens When We Realize ChatGPT Can’t Actually Do Your Taxes

My brother-in-law just quit his job to become a full-time AI stock trader. His strategy? Buy anything that mentions “artificial intelligence” in their earnings call. He’s up 340% this year.

He doesn’t know what a neural network is. Can’t explain what GPT stands for. Asked me yesterday if “machine learning” and “deep learning” are the same thing (they’re not, but also kind of?). But his portfolio is absolutely printing money.

Meanwhile, actual AI researchers I know are keeping their money in index funds, terrified of what they call “the greatest misallocation of capital in human history.”

Welcome to the AI gold rush, where nobody knows what they’re buying, everyone’s getting rich, and companies are slapping “AI-powered” on everything from toothbrushes to toilet paper to juice their stock price.

NVIDIA: The $3.2 Trillion Company That Sells Fancy Calculators

Let’s start with the elephant in the room that’s worth more than most continents. NVIDIA’s market cap is now $3.2 trillion. That’s trillion with a T.

To put that in perspective:

Worth more than the entire GDP of France
Bigger than Amazon and Google combined
One NVIDIA = 5 Walmarts
Could buy every house in California (and still have money left over)

What do they actually do? They make GPUs. Graphics cards. The same things gamers use to play Fortnite at 240 fps. Except now those cards mine Bitcoin, train AI models, and apparently justify a price-to-earnings ratio of 65.

The insane NVIDIA math:

Revenue: $80 billion (projected 2025)
Market cap: $3,200 billion
That’s 40x revenue
Apple trades at 7x revenue
Microsoft at 13x

Everyone buying NVIDIA at these levels is basically betting that every company on Earth needs to spend billions on AI chips forever. Maybe they’re right. Or maybe we’re watching the Cisco of 2025.

The Great AI Rebrand: How Every Company Became an “AI Company” Overnight

Remember when every company added “.com” to their name in 1999? Or “blockchain” in 2017? We’re doing it again, but with AI.

Real examples from this quarter’s earnings calls:

Domino’s Pizza: Now an “AI-powered food delivery platform”

What changed: They use an algorithm to optimize delivery routes
What actually changed: Nothing, they’ve done this since 2008
Stock reaction: +12%

Coca-Cola: “Leveraging AI for flavor innovation”

What changed: They use computers to analyze taste preferences
What actually changed: They renamed their R&D department
Stock reaction: +8%

Waste Management: “AI-driven waste optimization”

What changed: Trucks have GPS and follow efficient routes
What actually changed: Literally nothing
Stock reaction: +15%

The word “AI” appeared in earnings calls 11,000 times last quarter. In 2019? 743 times. Did AI advance 15x in five years? No. But stock prices did.

The Magnificent Seven’s AI Arms Race (Where Everyone’s Winning Except Your Wallet)

The biggest tech companies are in a spending war that makes the Cold War look fiscally responsible:

Microsoft:

Dropped $13 billion on OpenAI
Building $100 billion data centers
Copilot in everything (even Notepad, seriously?)
Stock up 61% because “AI leader”

Google:

Panic-launched Bard, then Gemini
Spending $50 billion annually on AI infrastructure
Still can’t make an AI that doesn’t tell people to eat glue
Stock up 48% because “AI potential”

Meta:

Zuckerberg says AI 200 times per earnings call
Spending $40 billion on AI while firing thousands
Their AI: Makes weird images of you as an anime character
Stock up 89% because “AI transformation”

Amazon:

AWS AI services growing 300% YoY
Every product has “AI-powered recommendations”
It’s the same recommendation engine from 2010
Stock up 44% because “AI infrastructure”

Apple:

Finally mentioned AI (they call it “Apple Intelligence” 🙄)
Siri still can’t set two timers
Stock up 35% because “AI coming soon”

Combined, these companies are spending $500 billion on AI this year. That’s more than the GDP of Sweden. For comparison, the entire Apollo program cost $25 billion ($150 billion in today’s dollars).

The AI ETF Explosion: When In Doubt, Buy Them All

Can’t pick which AI stock will win? There’s an ETF for that. Actually, there are 47 ETFs for that.

The AI ETF Leaderboard:

ARKQ (ARK Autonomous Technology & Robotics ETF)

Expense ratio: 0.75% (highway robbery)
Holdings: Whatever Cathie Wood dreams about
Performance: +87% YTD
Risk level: YOLO

BOTZ (Global X Robotics & Artificial Intelligence ETF)

Expense ratio: 0.68%
Holdings: 50% NVIDIA, 50% prayer
Performance: +73% YTD
Risk level: High

CHAT (Roundhill Generative AI ETF)

Yes, they named it CHAT
Expense ratio: 0.59%
Holdings: Every company that mentioned ChatGPT
Performance: +91% YTD
Risk level: Meme stock

AIEQ (AI Powered Equity ETF)

The fund itself uses AI to pick stocks
The AI is underperforming the S&P 500
Expense ratio: 0.77%
The irony is delicious

Total assets in AI ETFs: $47 billion, up from $3 billion in 2022. That’s not investment; that’s FOMO with an expense ratio.

The Startups That Make No Sense But Are Worth Billions Anyway

The private markets have completely lost their minds:

OpenAI:

Valuation: $180 billion
Revenue: $3 billion
Multiple: 60x
Product: Chatbot that lies convincingly

Anthropic (Claude):

Valuation: $40 billion
Revenue: $500 million
Multiple: 80x
Product: Chatbot that lies but feels bad about it

Perplexity:

Valuation: $3 billion
Revenue: $20 million
Multiple: 150x
Product: Google but worse and with hallucinations

Character.AI:

Valuation: $5 billion
Revenue: $16 million
Multiple: 312x
Product: Talk to fake people (we used to call this schizophrenia)

VCs are throwing money at anything with “.ai” in the domain name. There’s a company that got $10 million in funding with no product, no team, just a landing page that says “AI-powered solutions coming soon.”

The Dirty Secret: Most “AI” Is Just Statistics and If-Then Statements

Here’s what they don’t want you to know: 90% of what companies call “AI” is just:

Linear regression (statistics from 1805)
Decision trees (if this, then that)
Pattern matching (computers have done this since 1960)
Random forests (sounds fancy, it’s not)

Real AI? The transformative, world-changing stuff? That’s maybe 10% of what’s being sold as AI.

Examples of “AI” that isn’t:

Your bank’s “AI fraud detection”: Rules-based system from 1990
Netflix “AI recommendations”: Collaborative filtering from 2006
“AI-powered” customer service: Keyword matching with extra steps
Most “machine learning” platforms: Excel with better marketing

But the stock market doesn’t care. Slap “AI” on your spreadsheet macro and watch your valuation double.

The Bear Case Nobody Wants to Hear

Let me play devil’s advocate for a second:

1. The Revenue Problem

OpenAI loses money on every query
Google’s AI costs more to run than it makes
Microsoft’s Copilot has <5% adoption after a year
Nobody’s figured out how to make AI profitable at scale

2. The Commodity Problem

AI models are becoming commoditized
Open source is catching up to proprietary
Why pay for GPT-5 when Llama-4 is free?
Racing to the bottom on pricing

3. The Regulation Hammer

EU AI Act just passed
US regulation coming
China banning foreign AI
One bad AI disaster and it’s game over

4. The Plateau Problem

GPT-4 to GPT-5 improvement: marginal
We’re hitting diminishing returns
Scaling laws might be breaking
What if this is as good as it gets?

5. The Energy Problem

Training one model uses as much energy as 1,000 homes for a year
Data centers consuming 2% of global electricity
It’s unsustainable
Carbon taxes will destroy margins

The Bubble Checklist: Checking All the Boxes

✅ Taxi drivers giving stock tips (my Uber driver recommended NVDA) ✅ Companies adding technology name to increase value (everyone’s an “AI company”) ✅ Analysts saying “this time is different” (they all are) ✅ Valuations disconnected from reality (P/E ratios in the 60s) ✅ Everyone’s an expert suddenly (LinkedIn is 90% “AI thought leaders”) ✅ Fear of missing out driving investment (check) ✅ Infrastructure spending exceeding demand ($500B for chatbots?) ✅ Retirement funds going all-in (CalPERS just allocated 10% to AI)

We’re speedrunning the dot-com bubble but with better graphics.

What You Should Actually Do With Your Money

If you’re a momentum trader:

Ride the wave but set stop losses
Take profits regularly
Don’t marry your positions
When your grandma asks about AI stocks, sell everything

If you’re a long-term investor:

Buy the infrastructure (NVIDIA, AMD, cloud providers)
Avoid the applications (chatbot companies)
Keep allocation under 20%
Diversify across the supply chain

If you’re risk-averse:

Buy QQQ and call it a day
You’ll get AI exposure without the concentration risk
Sleep better at night
Miss the top but also miss the crash

If you’re a contrarian:

Short the stupidest AI companies
Buy the “boring” companies AI will actually help (industrials, healthcare)
Load up on energy stocks (someone needs to power all these data centers)
Wait for the crash, then buy everything

The Uncomfortable Truth About the AI Revolution

Here’s what’s actually happening: AI is real, transformative, and revolutionary. It’s also overhyped, overvalued, and over-invested. Both things are true.

We’re watching the birth of a new technology platform while simultaneously experiencing one of the greatest speculative bubbles in history. It’s like if the internet revolution and the dot-com bubble happened at 10x speed.

Some companies will 100x from here. Most will go to zero. The technology will change everything. The stocks will crash. Millionaires will be made. Retirements will be destroyed.

The only certainty? Nobody knows which way their bet will go.

The Bottom Line: We’re All Gambling on Robots Now

My brother-in-law, the one up 340%? He just put his kids’ college funds into AI stocks. My AI researcher friends? They’re buying bonds and gold, preparing for “when this all goes sideways.”

Who’s right? Check back in five years.

But here’s what I know for sure: When everyone from your barber to your banker is an AI expert, when companies are worth trillions for selling chips, when chatbots that can’t do basic math are valued at $180 billion – something’s got to give.

Maybe AI really is different this time. Maybe we’re at the beginning of the greatest wealth creation in history. Maybe my brother-in-law will retire at 35.

Or maybe we’re about to learn the same lesson every generation learns: Trees don’t grow to the sky, even if they’re powered by artificial intelligence.

Either way, it’s going to be one hell of a ride.

What’s your AI stock strategy? Are you all-in on NVIDIA, betting against the bubble, or watching from the sidelines with popcorn? Drop your take below – bonus points if you can explain what a neural network actually is.

Follow Finance Vantage for more coverage of humanity’s latest get-rich-quick scheme disguised as a technology revolution.

Disclaimer: This is not investment advice. The author owns some AI stocks because FOMO is real, some index funds because he’s not completely insane, and some cash because bubbles always pop. Do your own research, and remember: If everyone’s getting rich, someone’s about to get poor.