I keep hearing the same question at meetups, in Slack channels, even over coffee: “Are we in an AI bubble?” It feels like everyone’s betting on AI to deliver tomorrow’s miracles—today.
So, let’s chat about it.
Why It Feels Like a Bubble
- Valuations are sky‑high. Companies promising AI-powered this and that are raising eye‑popping sums—sometimes before they’ve shipped a single product.
- Every startup slaps “AI” on its pitch deck. In 2010 it was “cloud.” In 2019 it was “blockchain.” Today? AI is the magic word.
- Hype can outpace reality. We all love a good vision of the future. But when expectations zoom ahead of actual results, you’ve got the makings of a bubble.
A Bit of History
Back in the dot‑com era, firms with no revenue hit billion‑dollar valuations. Then the crash came—hard. Today’s AI scene reminds me of those heady days: excitement, easy money, and optimism on steroids.
But here’s the difference: AI isn’t just a gimmick the way “.com” was for some. It’s a real technology with real promise. That’s why this feels trickier.
The Good and the Not‑So‑Good
I’m a fan of AI. It’s powering tools that help us write, design, and even diagnose medical scans. That’s exciting. But I also worry when:
- Investors expect overnight profits. Real businesses take time to build.
- Startups chase funding instead of customers. Growth should come from solving real problems.
- Big players hoard talent and compute power. Smaller teams might struggle to compete.
How to Navigate the Hype
If you’re considering investing time, money, or energy in an AI project, here are three quick tips:
- Look for real users. Are people paying for this product today?
- Check the roadmap. Does the team have a clear plan for revenue and growth?
- Stay diversified. Don’t put all your eggs in one AI basket—explore other tech trends too.
My Two Cents
I’ve seen buzz cycles come and go. Not every trend lives up to its promise immediately. Sometimes, you have to buckle in for the long haul. AI will reshape industries, but the ride may have bumps.
So next time someone tells you “AI is everything,” take a breath. Ask the simple questions: Who’s using it now? What problem does it solve? And—perhaps most importantly—what happens if it doesn’t deliver?
