Most small businesses are still just testing AI. The cost of staying there is real

Just over half of small businesses are still in "testing" mode with AI. That is the headline finding from a recent survey of about a thousand owners run by the Reimagine Main Street project at the Public Private Strategies Institute. The study sampled companies with annual revenue between 25,000 and 5 million dollars. Fifty-one percent said they were exploring the technology. Roughly a quarter said they were already using it in production. Another twenty-four percent said they had no plans to adopt it any time soon.

The numbers themselves are not new. They line up with most polls from the last two years. What is worth pausing on is what they actually mean for the businesses sitting in each category.

Two ways to read the split

Read it one way: three out of four small businesses are either tinkering or sitting out, which is striking given how loud the AI conversation has become.

Read it another way: 76 percent are at least in motion, either fully integrated or actively trying things out.

Both readings are honest. They also describe a market in which the gap between the top quartile and everyone else is starting to widen.

What the early adopters are actually doing

The 25 percent that count themselves "current users" did not pick exotic use cases. They went after the same work big companies went after first: repetitive, time-consuming, easy to measure.

Per the survey:

• 90 percent are using AI for marketing and content
• 76 percent are using it for general worker productivity
• 60 percent are using it on product and service innovation

The report lands on a clean summary: saving time is the strongest value proposition. The next layer up is what these owners want next, which is agentic tools that help drive profitable growth. Cash flow forecasting. Identifying customer trends. Better signal for resource allocation.

In other words, the early adopters started by using AI to take low-value hours back. Now they are asking it to help them make decisions. That sequence matters.

What is holding the rest back

The reasons cited by owners still on the sidelines are reasonable, not lazy. The top three from the survey:

1. Privacy and data security concerns
2. Limited bandwidth to learn the tools
3. Unclear benefit to the business

Each of these is solvable. None of them is solved by waiting.

Privacy and data security. The right answer is to use tools built for business use, not consumer chatbots. Vendors that will sign a real data processing or business associate agreement, store data inside your perimeter, and not train on your inputs already exist in every category small businesses operate in. The pool of viable options has grown faster than most owners realize.

Bandwidth. This is the harder one. Most small business owners do not have a free week to read product reviews, run pilots, and figure out which tool to standardize on. This is where outside help, whether a tech consultant, a peer who has done it, or a vendor with a real implementation team, makes the difference between testing forever and shipping something useful.

Unclear benefit. This usually traces back to evaluating tools in the abstract. The benefit becomes clear when a tool is pointed at a real workflow that takes hours every week. Picking the workflow first, then picking the tool, flips the calculation entirely.

The trend that should make this urgent

While owners debate whether and when to adopt, the workforce has already moved.

A Gallup poll released this month found the share of U.S. employees using AI on the job jumped from 21 percent in 2023 to 40 percent in 2024. Frequency of use roughly doubled in that same period. The pattern is not subtle. People are using AI tools whether or not their employer has a policy, a stack, or even an opinion.

For an owner, that is a quiet risk and a quiet opportunity at the same time. The risk is that staff are pasting customer data, financials, or proprietary information into whatever tool they downloaded last weekend. The opportunity is that the appetite is already there, and a sanctioned, well-chosen toolset will land on receptive ground.

Either way, the question shifts. It is no longer "should we adopt." It is "are we shaping our adoption or letting it happen to us."

What stopping testing and starting using actually looks like

The honest gap between the two cohorts is structural, not philosophical. The companies that moved past testing did three things:

They picked one workflow that consumed real hours, picked one tool that handled it well, and ran the tool against the workflow long enough to know whether it earned its keep.

That sounds obvious. It is also not what most "testing" looks like in practice. Testing usually means a junior staff member tries three chatbots for a week, none of them get integrated into anything, and the conversation moves on. Six months later the business is still in the same category on the same survey.

What is worth doing in the off-cycle of your year, whatever that looks like for your business:

1. Pick the two workflows that consume the most hours of your most expensive people. Document them.
2. Map each workflow to the category of AI tool that actually fits, not the one that is loudest. Marketing copy is one category. Document processing is another. Customer-facing chat is a third. They are not interchangeable.
3. For each tool, get answers to where data goes, whether it is used to train the underlying model, and what security posture the vendor maintains. Write the answers down.
4. Pilot one or two tools against the actual workflow for at least a month. Track the hours saved and the errors caught or introduced.
5. Standardize on what worked. Train the team. Retire what did not.

That is what moves a company from the 51 percent to the 25 percent. The 25 percent is where the operating leverage starts to compound.

The shift that is already underway

Rhett Buttle, president of the Public Private Strategies Institute, summed up the trajectory cleanly: small businesses are starting to recognize that AI is no longer a nice-to-have for saving time. It is becoming part of how a competitive business runs.

That shift will not happen evenly. The owners who stay in "testing" indefinitely will lose ground to peers who got out of testing and into using. The gap, like most operating gaps, will not close on its own.

The off-cycle of your year, whether that is the summer slow-down for retail, the post-tax-season window for accountants, or the slow stretch between projects for service businesses, is when this work gets done. Six months from now, the businesses that used the time will look meaningfully different. The ones that did not will look the same as they do today.

That is the choice on the table.