So, about that "AI is cheaper" thing...

New blog post just dropped on the site, and I'll be real with you — the numbers in this one actually surprised me.

We've all heard the narrative. AI replaces people, cuts costs, transforms business. That's what every earnings call and tech keynote has been screaming for two years straight.

Turns out the math doesn't work yet.

The kicker? Nvidia's own VP of Applied Deep Learning — the guy at the company selling every GPU on the planet — said running AI costs his team more than paying the humans who build it.

Not a startup struggling with scale. Nvidia.

And they're not alone. Uber blew through their entire 2026 AI budget by Q2 — on tokens, not headcount. A four-person startup hit $113K in AI costs in a single month. An MIT study found AI is only economically viable in about 23% of vision-related roles. For the other 77%, humans are still cheaper.

So the companies that laid people off to "invest more in AI" may have just ended up with a more expensive system than what they started with.

Before you roll your eyes — I'm not saying AI is useless. Far from it.

What I'm saying is: the way you use it matters a lot more than the amount you spend on it.

The playbook that actually works (from the blog):

- 🎯 Use AI for specific bottlenecks, not entire workflows

- 💰 Track token spend like any other COGS — cap it, know your numbers

- 🧠 Optimize for augmentation, not replacement

Right now AI is a premium product, not a cost-saving one. That's fine — every new technology starts there. The mistake is pretending otherwise.

The full post has a five-step playbook and some genuinely useful breakdowns. Worth a read if you're trying to figure out where AI actually fits in your business right now:

🔗 amplifyaiworkshop.blog

👇 What's your take? Anyone else noticing AI costs creeping up faster than expected?

0 comments