Blog · · Benatar Brands
Most owners use AI. Few have it running the business. Here's the gap.
Ask a room of owners whether they use AI and most hands go up. Ask whether AI runs any part of the business without someone opening a chat window first, and most hands come down. That difference is the gap this post is about.
Using AI and having it run the business are different things. The first is a person asking a tool for help. The second is a process that happens every week, reads your real data, lands its output where the work gets done, and has someone responsible for checking it. The surveys published this year show plenty of the first and very little of the second.
What the surveys say
The clearest number comes from the Goldman Sachs 10,000 Small Businesses Voices survey, conducted by Babson College and David Binder Research among 1,256 program participants from January 27 to February 4, 2026. 76% said they currently use AI, and 93% of those users said it had a positive impact. Yet only 14% said AI is fully embedded in their core operations. 73% said they would benefit from more access to training and implementation resources.
The UK picture looks similar. Simply Business's 2026 SME Insights Report, a survey of 1,842 UK small business owners from July 30 to August 7, 2026, found 47% now use AI tools, up from 22% in 2025. Only 19% described themselves as very confident using AI day to day, and 33% said they use it only for routine admin tasks. 31% said they do not understand how to use AI or are wary of integrating it into their work.
The U.S. Census Bureau measures something narrower, and its numbers are lower. Its Business Trends and Outlook Survey gives a nationally representative view of U.S. businesses. Census's May 2026 summary reports that AI use hovered between 17% and 20% from December 2025 to May 2026. Use rose among firms with at least 20 employees but did not change significantly among firms with fewer than 20, and less than 20% of firms with four or fewer employees reported using AI.
A Census research paper on the same survey, The Microstructure of AI Diffusion, looks at depth. Among firms that use AI, 57% use it in three or fewer business functions, and about 65% of firms limit worker use to three or fewer task types. Writing, document analysis and information search lead the list.
Why the numbers disagree, and what they agree on
76%, 47% and under 20% look like three different worlds. They are mostly three different questions. Goldman surveyed owners who went through a business education program, a group likely to be ahead of average. Simply Business surveyed UK owners. Census asks whether a business used AI in a business function in the past two weeks, across U.S. businesses of every size.
So do not quote any one of them as "the" adoption rate. What all three agree on is the shape: AI use is broad and shallow. Many owners have tried it, a smaller share use it regularly, and only a small share have built it into how work gets done.
Using versus running: four levels
It helps to name the levels, because "we use AI" covers all of them.
- Ad hoc. Someone opens a chat when they remember to, and the result depends on who asked and how.
- Repeatable. The same task uses a saved prompt or template, so the output looks the same each time.
- Connected and scheduled. The task runs on a schedule, reads the real source (the inbox, the store, the calendar, the project board) and delivers its output where someone will see it.
- Owned. The process has a named owner, a written description of what it does and does not do, a review step before anything reaches a customer, and one number that shows whether it is working.
Most of the "using" in those surveys sits at level one. The 14% in the Goldman survey who say AI is fully embedded are describing levels three and four.
What is actually in the gap
The model is rarely what holds a business at level one. The usual blockers are more ordinary.
- Inputs. The data the task needs lives in places the tool cannot reach, so someone copies and pastes. Every paste is a chance for the routine to quietly stop.
- Ownership. Nobody's job includes keeping the process running, so it works until the person who set it up gets busy.
- Review. With no checkpoint, nobody trusts the output enough to let it run. Simply Business found 36% of owners cite accuracy concerns, and that is a fair worry when nothing is checked.
- Skills and time. The Goldman and Simply Business numbers on training and confidence point the same way: owners want help setting this up, not another tool to learn alone.
None of those is solved by a better chatbot. They are solved by treating one process as a small project.
Closing it, one process at a time
Pick one task you already do with AI at level one, ideally something that happens every week. Then move it up a level at a time:
- Write the steps down in plain language, including what the output should look like.
- Connect the one data source it needs, with the least access that does the job. Read-only is the right default.
- Put it on a schedule and decide where the output lands.
- Name an owner and a review step. For anything customer-facing, a person approves before it goes out.
- Choose one number to watch. Our 30-day rule covers how to run that trial and make the keep, fix or cut call.
When that process is running without reminders, pick the next one. Breadth comes from repeating depth, not from signing up for more tools.
The Census paper reports a robust positive correlation between firms' commercial performance and the breadth of their AI integration. That is a correlation, not proof that integration caused the results; firms that are already doing well may simply have more room to invest. It is still a reasonable signal that the businesses getting value are the ones that went past the chat window.
Where we come in
Moving processes from "someone uses AI" to "it runs, and someone owns it" is what our embedded AI partnership does. If you want to pick your first process and map it with us, book a free session.
Related service: embedded AI partnership.
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