How Are Small Businesses Using Generative AI Without Huge Budgets?

Development & Technical
1

Generative AI is everywhere these days, but I’m curious how are small businesses really putting it to work without burning through huge budgets like big tech companies?

A few small founders I know have been testing practical ways to bring in generative AI development — things like using AI chatbots for 24/7 support, generating quick social content, or speeding up internal documentation tasks.

Some are working with custom generative AI services to adapt pre-trained models for their niche instead of building everything from scratch. It saves a ton on development costs and helps them get results faster.

Even companies like SoluLab, a leading AI consulting company, are working with startups and SMBs to prove ideas fast and keep the spend realistic — rather than investing in huge custom models right away.

So I’d love to hear from others here:

  • What’s actually working for you?
  • Are you using generative AI for content, marketing, customer service, or something else?
  • Did you hire a generative AI development company or keep it all in-house?

Any tips or lessons for other small businesses looking to experiment with AI on a budget? Let’s trade ideas — what’s working, what flopped, what’s next?

2

We’ve seen a lot of small businesses using generative AI in super targeted ways that don’t require massive budgets. At Fourchain, we recently developed an AI-powered solution for a client that automates inbound and outbound sales calls—the goal was to improve lead quality and sales team efficiency.

The total project cost was just $7,850, and we delivered it in 3 milestones, including 3 rounds of module revisions. The final system gives real-time call responses in under 30 milliseconds, and during testing, it was able to extract exactly what the client needed from each call—helping them better qualify leads and personalize follow-ups.

So yeah, small businesses can absolutely leverage generative AI—it just comes down to having a focused use case and a lean, well-scoped build.