By Ron Gustaveson, founder of DR Outsourcing
Goldman Sachs 10,000 Small Businesses survey, early 2026: “Only 14% of small businesses are fully integrating AI into core operations.”
It’s 10:40 at night. You paste a customer’s question into an AI chat, hit enter, and get back three polished paragraphs that could have been written for any business in America. Nothing about your pricing. Nothing about your return policy. Nothing about the fact that this customer has ordered from you for six years. So you rewrite it yourself, again.
Then you remember the AI tool you signed up for in March, and the one from June. You’re honestly not sure either one is still doing anything.
If that sounds familiar, you’ve got plenty of company. Goldman Sachs’ 2026 survey of small business owners found that 76% of small businesses use AI. Only 14% are fully integrating it into core operations. The survey, part of the 10,000 Small Businesses Voices program, polled 1,256 participants from January 27 to February 4, 2026, and was run by Babson College and David Binder Research.
Adoption is real. Integration is where it stalls.
Using AI and building it in are different things
Using AI looks like the scene above. You open a chat window when you think of it, and it helps with one task at a time. That’s worth something.
Integrating AI means it’s part of how the work actually moves. It knows your products, your customers, and your way of doing things. Repeat work runs on a schedule whether or not anyone remembers to start it. Nobody has to re-explain the business every time they ask a question.
Why the gap is so hard to close alone
Owners aren’t ignoring this. They’re saying exactly where they’re stuck. In the same Goldman Sachs survey, among owners already using AI, 49% cite a lack of technical expertise and 48% cite difficulty choosing the right AI tools. And 73% say their business would benefit from additional access to training and resources necessary to implement and evaluate AI.
Those are honest answers from people who are trying. And the ground keeps moving under them.
PwC’s 2025 Global AI Jobs Barometer, built on roughly a billion job ads, found that “the skills sought by employers are changing 66% faster in occupations most exposed to AI, up from 25% last year.” PwC’s 2026 analysis of job ads worldwide found that “the average wage premium for workers with AI skills continued to surge higher, hitting 62%, up from 57% last year.”
Put those together. The skills shift fast, and the people who have them are in demand. Now drop that into an owner’s normal week: customers, staff, cash flow, sales. Learning AI properly turns into a second job with no hours attached. The project slides to next month, and by next month the tools have changed again.
There are only so many hours in a week.
What scaffolding means, in plain words
Here’s the part that helps. You don’t need to learn all of it. You need scaffolding: a structure that holds the AI work up so it doesn’t depend on you finding a free evening.
It comes in two pieces, and the order matters.
First, a company second brain. A “second brain” is an organized, searchable home for what your business knows: price sheets, policies, past proposals, process notes, and the answers your best people usually give from memory. When your AI tools can read from it, they answer with your information instead of guessing. If your AI doesn’t know your business, every answer comes back generic or wrong. Garbage in, garbage out.
Then, automations on the repeat work. Once AI knows your business, you can hand it the tasks that come back every week. A follow-up that goes out on schedule. A summary that lands in your inbox Monday morning. Notes filed where your team can find them. Start with one. A single job that runs reliably beats ten half-built ones.
Neither piece asks you to become an expert. Both need someone to build them and keep them current, because tools change and files go stale. The scaffolding needs an owner.
Make it somebody’s whole job
You can build this in-house if you have someone with the time and the interest. That’s a fine route.
Another route is a dedicated AI Maestro: a team member whose whole job is running your tech stack and AI. That covers integrations, automations, AI agents, apps, scheduled jobs, and the company knowledge base. The role can be fractional (one to four days a week), part-time, or full-time, and it’s measured by outcome. The report back is simple: here’s what we got done for you.
To be clear about one thing: this role is there to make your current people faster. Your team keeps doing the work they’re good at, with better tools behind them.
Full disclosure
I’m not a neutral party. DR Outsourcing is my company, and we place AI Maestros as well as dedicated, trained, bilingual Dominican Republic team members with U.S. small and mid-sized businesses. I’ve spent 17 years managing Dominican Republic teams. The advice above holds whether you ever talk to us or not: someone has to own the AI work. Who that is, it’s up to you.
One thing to try this week
You don’t need to buy anything. The next time you paste a question into an AI tool and get a generic answer, jot down what it was missing. Your pricing. A policy. A customer’s history. The way you actually do things.
Do that for a week. That short list tells you what your AI needs to know about your business, and it’s where every second brain starts.
You’re already using AI. The next step is making sure it knows your business, and that someone owns it.
