Let's be real about what's unfolding in AI today: it's a frenzy. Like every gold rush, most people aren't striking gold—they're selling shovels. We're deep inside a classic bubble, driven by FOMO, impatient investors, and a cycle of tech bros funding other tech bros to churn out fragile software.
The unfortunate part is that some truly impressive AI companies do exist, building tools that tackle meaningful problems. But they're being drowned out by the noise—a wave of hype and half-baked products.
The Dot-Com Déjà Vu
If this feels familiar, it should. Back in the late 90s, the dot-com craze hit its peak. Companies like Pets.com collapsed because the hype ballooned far beyond the actual value. Yet the crash didn't mean the internet was useless. It simply meant most of those early companies were. The hype died, but the utility endured.
What's happening in AI now mirrors that moment. The bubble doesn't mean AI is fake—it means the market is overheated and due for a correction. AI is powerful when it's built by smart teams solving genuine problems.
A Simple Filter for the AI Bubble
The biggest risk for marketers isn't AI itself—it's "hype fatigue." That's when budget and credibility get burned on empty solutions, leaving teams jaded about the tech that does work. To cut through, you need a filter. Here's a three-part framework to vet any new tool:
1. Utility over Buzz
Does it solve a concrete, unglamorous problem?
The most valuable AI products aren't shiny demos. They fix annoying, costly issues in your workflow—like ad testing, transcription, or sentiment tagging—and do it faster or cheaper.
If the use case is vague, hand-wavy, or sounds like "AI for everything," beware.
Ask:
- What exact task does this replace or improve?
- How much time or money does it realistically save?
- Can I map this to a specific line item in my budget or workflow?
2. Demo over Deck
Is it real or just a pitch?
Don't fall for slick videos or beautifully designed pitch decks. Ask for a live demo using your data, solving your problem.
This is a sharp, grounded take on the current AI landscape—and a useful lens for marketers trying to separate signal from noise.
Key Idea
We’re in an AI bubble that looks a lot like the late-90s dot-com era: massive hype, lots of flimsy products, and a handful of genuinely valuable companies getting drowned out. The bubble doesn’t mean AI is fake; it means the market is overheated.
The Dot-Com Parallel
- Pets.com and similar failures weren’t proof the internet was useless.
- They were proof that most early companies were.
- After the crash, the hype died but the utility of the internet only grew.
AI is in that same phase now: the technology is real, but the market is crowded with shallow, rushed products.
The 3-Part Filter for Vetting AI Tools
Use this as a practical checklist before you commit budget or reputation:
- Utility over Buzz
- Look for tools that solve a specific, boring, expensive problem.
- Examples: ad testing, transcription, sentiment tagging, QA, routing, data cleanup.
- Red flag: vague promises like “AI that transforms your marketing” with no clear workflow or metric.
- Demo over Deck
- Don’t trust pitch decks or polished videos.
- Ask for a live demo on your data, your use case.
- Can it:
- Generate on-brief ad variations from your existing campaigns?
- Analyze your real customer feedback or support tickets?
- If they can’t show it working end-to-end, assume it doesn’t.
- Founder over Funding
- Ignore the logo slide of investors for a moment.
- Ask: do the founders deeply understand the problem space (e.g., performance marketing, CRM, support ops, analytics)?
- Look for:
- Prior experience in the exact domain they’re serving.
- Clear, almost obsessive articulation of the problem and edge cases.
- Be wary of generic “AI for X” teams clearly chasing a trend.
Why This Matters for Marketers
The real risk isn’t AI itself—it’s hype fatigue:
- Budgets get burned on tools that don’t deliver.
- Teams become cynical about all AI, including the stuff that actually works.
- The next time a genuinely useful product appears, it’s harder to get buy-in.
Using this filter protects:
- Budget: You fund tools that tie to measurable outcomes.
- Credibility: You’re not the one who championed the shiny toy that flopped.
- Momentum: Your team sees AI as a force multiplier, not a distraction.
The Quiet Future
When the bubble bursts:
- Capital dries up for mediocre, hype-driven players.
- The loudest, flashiest products will disappear.
- The teams that survive will be the ones:
- Solving unglamorous, high-friction problems.
- Shipping real features, not just fundraising rounds.
- Grounded in customer outcomes, not valuation milestones.
In other words, the future of AI in marketing will be quiet and brilliant: deeply integrated into workflows, boring on the surface, and incredibly powerful underneath.
If you’re evaluating AI tools today, treat this as your operating rule:
If it doesn’t clearly solve a painful problem, work on your data in a live demo, and come from a team obsessed with the domain—walk away.
