I’ve been thinking about a number a lot this week.
Ninety percent.
That’s roughly how much the cost of serious AI capability has dropped in the past 12 months.
What cost entrepreneurs $500 a month last year in AI tools now runs about $50 for equivalent or better capability. The frontier models, the ones doing the serious work, have collapsed in price while improving in quality.
I’ve watched this happen slowly, then all at once. And I think a lot of entrepreneurs missed the “all at once” part.
Let Me Tell You What I Was Paying Attention To
Early 2025, I was having conversations with entrepreneurs who were genuinely interested in building AI into their operations, but kept running into the same wall.
“The math doesn’t work yet.”
Premium AI access cost enough that unless you were running significant volume through the tool, the ROI was hard to justify. You’d pay $50 to $100 a month just for a capable AI, before you even factored in the time to set it up and the overhead of integrating it into your workflow.
That created a real access problem. Not just a perception problem. An actual one.
For solo operators and small teams, serious AI implementation felt like something to revisit later when the economics improved.
Well. The economics improved.
What’s Actually Happened in the Market
Here’s the quick version.
Claude Sonnet 4.6 launched in February 2026 at pricing significantly below its predecessors. Gemini 3.1 Pro dominates benchmarks at commodity-tier costs. GPT-5 variants followed a similar pattern.
Every major AI lab is locked in a race where the pressure is to be the best AND the cheapest. That competition is paying dividends for anyone who pays for these tools.
The thing that strikes me most isn’t the absolute price. It’s the capability per dollar.
A year ago, $50 a month bought you limited access to good AI. Today, $50 a month buys you extensive access to excellent AI. The gap between what’s accessible to a solo entrepreneur and what’s accessible to a Fortune 500 company has narrowed dramatically.
That is a generational leveling of the playing field, and I don’t think it’s getting enough attention.
The Question I Keep Asking Entrepreneurs
When I’m talking with business owners about their AI strategy, I’ve started asking a specific question.
“What did you decide was economically out of reach in 2025 that you haven’t revisited?”
Because I watch people make decisions about AI adoption, let the economics change, and then keep the original decision in place. Not because they checked the new math. Just because nothing prompted them to revisit it.
The human brain is not great at going back and re-evaluating closed decisions. We make a call, file it away, and move on.
But the AI economics right now demand a revisit.
If you decided that a full AI-powered content pipeline was too expensive for your business, recheck.
If you decided that AI customer service was still too cost-prohibitive for your volume, recheck.
If you decided that building AI into your client deliverables wasn’t justified at the price point, recheck.
Some of those decisions will still hold. Some of them will not. But you won’t know until you look.
What I Did With This Realization
When I ran through this exercise myself, I found two use cases I’d put on the back burner that had quietly become financially obvious.
One was a content repurposing workflow I’d been doing manually, or skipping. The cost of building an AI-assisted version of it last year felt like it was chasing marginal efficiency. Today, the cost has dropped enough that it’s not a close call anymore.
The other was research. I’d been paying a VA a few hours a month to do certain competitive research tasks. Running the same tasks through AI now costs a fraction of that, with comparable output quality for the specific use case.
I’m not telling you to fire your team and replace them with AI. That’s not the takeaway.
The takeaway is: revisit the numbers with fresh eyes, because the numbers changed.
The Faith Angle I Keep Coming Back To
There’s something I find genuinely remarkable about this moment.
The tools that used to be locked behind enterprise budgets are now accessible to the small business owner, the solo operator, the entrepreneur building something meaningful on a real-world budget.
That matters to me. Not just as a business strategy, but as someone who believes deeply in the dignity and potential of people building things the hard way, without corporate backing, without massive capital, without an army of specialists.
The playing field isn’t level. It never is. But it got a lot closer to level this year. And I think that’s worth celebrating, not just noting.
One Practical Thing to Do This Week
Go back to your list of AI use cases you’ve dismissed or deferred.
Pick two. Run the current numbers. See if the math changed.
You might find what I found: that some of the things you filed away as “later” are actually “now.”
The tools are here. The prices are right. The only thing standing between you and a more capable, more efficient operation is the willingness to revisit a closed decision.
Do it this week.
If you want to think through the AI economics for your specific business, come find me in the community. That’s exactly the kind of conversation we have.
