Is the AI Bubble about to burst soon? Maybe. Sam Altman stated he’s preparing for the AI Bubble bursting”: "When bubbles happen, smart people get overexcited about a kernel of truth." Meanwhile, last week Meta froze AI hiring after offering city budget compensation packages on individual AI talent, and OpenAI is reportedly burning $8 billion annually while serving 700 million weekly users with break even not expected until 2029 (as they continue to build their infrastructure for new models and set to seek a new round of funding).
But here's what bubble talk misses: OpenAI isn't heading for a Pets.com flameout. They're sitting on the exact user base size that Google and Meta leveraged to build advertising empires, except OpenAI's current spending seems to be less focused on optimization and more like that of a college student with their first credit card. The uncomfortable truth? Bubble pressure will force them into monetization moves faster than Google took to perfect theirs (investors only like no-return investments for so long).
The Bubble Creates Urgency (And Smart Companies Love Urgency)
AI is still the core driver in 2025's economic growth, but when industry leaders start using "bubble" language, investors notice. Budgets for 2026 have already started, and companies are seeing less than stellar delivery on the AI hype promises that have been delivered - especially with ChatGPT5’s promise of Luxury Villa accommodations and delivering what more and more feels like FEMA tents. Giving access back to the 4o model proves this.
This isn't panic though, it's clarity. Unlike Google and Meta, who had a decade or more to optimize their ad strategies during growth phases, OpenAI faces a compressed timeline to prove unit economics work at scale - and with billions more at stake. That pressure creates three inevitable moves, I’d bet we’ll see at least one emerge in 2026.
Move 1: Ads - Where Intent Marketing Meets A Crystal Ball
Google built the greatest ad business in history by aligning ads with intent. You searched for "running shoes," Nike paid to appear, money printed for both Google and Nike by finding the right person at the right time.
OpenAI's version will be more insidious and capable: Predictive Experience Marketing (PX). Instead of reacting to intent, AI will compose experiences ahead of it. Ask for "best things to do in Paris" and a full plan including hotel, flight, restaurant, and activities will be shared while then sliding in ads that fit like a glove. It can even infer from adjacent signals such as recent health searches providing ads delivering walking tour on things that are of high personal interest, post-breakup energy points to solo-friendly venues or places to meet singles who are exactly your type. A woman asking for 'long-lasting lash extending mascara for a special event' gets an answer using collected data they've been asking about reunion planning sites, asked 'tips for how to look younger at 45,' and recently viewed photos from college friends' social media. The AI doesn't just recommend mascara, it crafts a complete 'reunion glow-up' strategy.
The response includes detailed application techniques for dramatic lashes, suggests a complementary nude lip color that photographs well, and recommends a setting spray for all-night wear. But here's where it gets sophisticated: alongside these organic recommendations appear sponsored ads that feel completely natural. The 'perfect nude lipstick' happens to be from a partner brand, A 'professional makeup artist tip' about primer links to a sponsored tutorial featuring specific products. The AI might even show an ad to schedule a 'reunion prep appointment' at a participating local salon.
She thinks they’re getting insider beauty advice from someone who understands her exact situation. Instead, they’re actually experiencing curated product placement where every suggestion feels like it came from her most knowledgeable friend, one who happens to know she wants to walk into that reunion looking like the successful, confident woman she's become.
This isn't search advertising. It's pre-intent persuasion where ads stop looking like billboards and start feeling like inevitabilities.
Here's the uncomfortable truth for Google: they know ads are OpenAI's kill switch, but they're trapped in an innovator's dilemma. Turn on ads too aggressively and users flee to Open AI, Perplexity or Claude. Wait too long and OpenAI captures the market while Google hesitates.
My bet: by 2027, PX-style ad units blend seamlessly into recommendations. At that point, the $20/month novelty becomes the most targeted persuasion engine in history.
Move 2: Enterprise Licensing - The Boring Move That Pays The Rent
The $20 ChatGPT Pro subscription isn't about revenue – it's a laboratory. A way to study thousands of use cases on how businesses use AI, where it fails, and where it hallucinates.
The real monetization shift: enterprise-grade federated models trained on company-specific data. When AI learns your contracts, customer history, and internal knowledge bases, hallucinations shrink and utility explodes.
Law firms eliminate phantom court cases. Hospitals avoid creative diagnoses. Corporates get internal AI that knows products, policies, customers and delivers consistently accurate insights and sales enablement assets.
That's not $20 monthly subscriptions. That's six- and seven-figure annual contracts with boring, predictable revenue that makes investors stop hyperventilating.
The good news? While consumer AI becomes commoditized, enterprise customization creates defensible moats. It's like selling shovels during a gold rush, except the shovels are custom-built and cost $500K each.
Move 3: The Platform Play - When Chat Windows Become Ecosystems
Apple didn't invent MP3 players. It perfected them with iTunes marketplace convenience, then rewired the music industry.
OpenAI's version: today's subsidized $20 subscription becomes the wedge for an AI-native ecosystem. The ChatGPT "store" looks gimmicky now, but so did the App Store in 2008.
When bubble pressure mounts, platform economics become critical. Instead of burning cash on compute for free users, OpenAI captures revenue from every transaction in their walled garden. It's like being the house in Vegas, except the house also writes your vacation itinerary and picks your dinner wine.
Why This Moment Is Different (And Why Google Should Lose Sleep)
Unlike the dot-com bust where the rush of .com brands had no proven scalable monetization models, OpenAI has three strategies that built the most profitable companies in history.
The dot-com parallel matters because it reveals different failure modes. Pets.com's brilliant branding, cultural dominance, but economics that collapsed when investors realized it solved no real problem – just added another option nobody actually needed.
eToys? More instructive. Worth $8 billion at peak with millions of customers (parents who love their kids) and a beloved product - toys! But customer acquisition costs outpaced profits, leading to 2001 bankruptcy.
OpenAI has what both lacked: 700 million weekly users and proven monetization playbooks. But here's the deeper parallel - they're at the same inflection point Google hit in 2015.
Google didn't abandon "Don't Be Evil" in 2015 because they were desperate. They had 900 million Gmail users and 3.5 billion daily searches - massive traction but needed to accelerate revenue growth to match their scale and ambition. Removing strict ethical constraints wasn't survival necessity; changing to "Do Only Good" was growth optimization that enabled more aggressive surveillance and ad targeting. The same focus on revenue to support user growth was also true at Meta to drive mass adoption of their Ad program. This can be seen in a number of examples including the launch of Beacon in 2007, the Cambridge Analytica debacle in 2015 and abandoning the core promise of What’s App’s privacy guarantee in 2021).
OpenAI faces the same choice: maintain their current approach or pivot to aggressive monetization that maximizes their 700 million user advantage. The question isn't whether these strategies work – Google, Apple and Meta already proved they do.
Here's what should keep Sundar Pichai up at night: if OpenAI nails ads, Google's two-decade dominance in the $800 billion advertising market faces its first real threat since, well, ever.
2026: When the Mask Comes Off
By 2026, investors won't fund a bonfire forever. The timeline isn't arbitrary – it's driven by corporate budget cycles demanding ROI proof, bubble skepticism creating pressure, and competitive positioning as Google hesitates.
It's an innovator's dilemma in real time. And for the first time in 20 years, Google isn't playing offense.
Meta? They'll play copycat or buy in after the market's established – that's their playbook for success with WhatsApp, Instagram, Reels, Stories. Grok? Nobody's buying ads next to Elon's content on X. Claude and Perplexity? Too small.
The ad war will be fought between OpenAI and Google. If OpenAI wins, the oxygen fueling Google's empire goes with it.
The Bottom Line (Because Someone Has to Pay for All This Compute)
AI isn't doomed, it isn't salvation, and depending on whether the economics catch up, it can be both. If OpenAI fails, it's Pets.com with millions of GPUs. If it succeeds, it forces the biggest shift in digital advertising since Google turned search into a money printer.
The bubble creates urgency without changing the fundamental opportunity. These three moves aren't speculative hopes – they're pressure-driven inevitabilities following proven playbooks.
The real takeaway isn't to cheer or panic. It's this: hype without economics is theater. But when companies with 700 million users follow the exact playbook that created Google and Meta's dominance, that's not hype.
That's history repeating itself at internet scale, just faster and with better user interfaces.