There’s a fascinating New York Times article making the rounds about the “generative AI paradox” — the fact that corporate spending on AI is exploding, but the bottom-line payoff just isn’t there yet.
Big players like Microsoft, Amazon, and Google are raking in AI profits. Nvidia is selling chips like hotcakes. But for most companies, especially those outside the tech sector, AI is still in the “lots of money in, not much money out” stage. McKinsey says 80% of companies are using generative AI, but nearly the same number report no significant financial impact. That’s… sobering.
So if you’re a smaller firm, without billion-dollar budgets or a 60,000-person tech staff, how do you even begin to make AI work for you?
1. Think in Terms of Targeted Wins, Not Total Transformation
One big takeaway from the NYT piece is that the small wins are what’s sticking.
- USAA uses AI to assist (not replace) call center staff.
- Johnson Controls trims 10–15 minutes from repair jobs.
- JPMorgan automates report drafting and data retrieval.
Notice what’s missing? Nobody’s saying, “AI replaced half our workforce and tripled our profits overnight.” These are micro-efficiencies that add up — and they’re exactly where smaller firms should focus.
For you, that might mean:
- An AI tool that drafts first-pass proposals or reports.
- Customer service chatbots that handle basic queries before a human steps in.
- AI-powered search across your internal documents so your team stops reinventing the wheel.
2. Use the 80/20 Rule for Pilots
Here’s the trap smaller firms can fall into: thinking AI requires a big, complex rollout. It doesn’t. Start with one process where 80% of the work is repetitive and rules-based. Then, find an AI tool to chip away at that 80% — leaving your team to focus on the 20% that requires human judgment.
The NYT piece points out that 42% of AI pilot projects were abandoned last year. That’s not failure — it’s course correction. Shut down what’s not working quickly, but keep the lessons learned. Small firms can be nimbler than giants here, turning failed pilots into better second attempts.
3. Borrow the Big Guys’ Guardrails Without Their Bureaucracy
JPMorgan locked down security and data governance before expanding AI to 200,000 employees. Smaller firms can’t afford that scale, but you can still:
- Keep sensitive data off public AI tools.
- Choose platforms with strong privacy controls.
- Train your team on what AI shouldn’t touch just as much as what it should.
The less you have to unwind later, the faster you can scale what works.
4. Invest in People Before Platforms
One overlooked point in the NYT reporting: many AI failures come from “human factors” — employee pushback, lack of skills, customer distrust. For a small business, a \$50,000 AI investment can be sunk in six months if the team doesn’t adopt it.
Sometimes the best first “AI spend” isn’t the tool — it’s the training. Even a few hours of workshops on prompt writing, tool selection, and workflow integration can double your ROI.
The Bottom Line
Small firms have a hidden advantage: agility. You’re not burdened by legacy systems, sprawling compliance departments, or shareholder expectations of quarterly AI miracles. You can try small, learn fast, and scale the wins that fit your business.
The generative AI paradox isn’t a reason to avoid AI — it’s a reason to approach it with focus and discipline. And in five years, when the tech giants are still “optimizing their AI stack,” you might already have a handful of well-oiled AI processes quietly making you more efficient every day.
Memorable Takeaway:
You don’t need a billion-dollar AI budget — you need a billion-dollar habit of finding and scaling the little wins.