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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteYes—but the headline needs a precise denominator. In Pax8’s Q3 2026 SMB AI Pulse, 67% of businesses that were already engaged with AI said they had developed at least one AI solution in regular use. The survey does not show that two-thirds of all small firms build software, nor does it prove that custom AI improves profits or productivity.
What Pax8 actually measured
Pax8 published the finding on October 12, 2026, from an online survey of 1,150 owners, executives, functional leaders and managers involved in technology decisions. Their companies employed between 5 and 499 people and were located in the United States, United Kingdom, Germany or Sweden.
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The 67% figure applies to AI-engaged businesses—companies using, building or paying for AI—not to every small business in those countries. Within that AI-engaged group, 19% said they were prototyping and 13% relied exclusively on off-the-shelf tools. Percentages can differ slightly from 100% because of rounding and, for some questions, multiple answers were allowed.
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| Reported status among AI-engaged businesses | Share |
|---|---|
| Developed one or more AI solutions in regular use | 67% |
| Prototyping AI solutions | 19% |
| Using only off-the-shelf AI tools | 13% |
These categories describe reported business practice in one cross-sectional survey. They are not a controlled test of outcomes, and the release does not establish that building tools caused better performance.
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What “building their own tools” includes
Pax8’s definition is broader than creating a foundation model or training a large model from scratch. Among the businesses that identified as builders, respondents reported several kinds of work, often in combination:
- Automated workflows: 52% were connecting AI to other business systems so that tasks could run across applications.
- Multi-step agents: 46% were building or testing agents able to perform sequences of actions rather than answer a single prompt.
- API integrations: 39% had built custom integrations using an AI provider’s application programming interface.
Those percentages are separate activities, not mutually exclusive portions of a 100% whole. A company could, for example, connect an AI service to its customer database through an API and use that connection inside an automated workflow.
Adoption is moving faster than approval and review
The survey also points to a governance gap. Thirty-five percent of AI-engaged businesses said they had discovered AI running without approval during the previous six months. That result indicates unsanctioned use is not limited to isolated experiments; however, the survey does not identify which tools were involved or whether the activity caused an incident.
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Formal review of internally built AI varied by country. The share reporting a documented review process ranged from 23% in the United Kingdom to 45% in Sweden. In the United States, 36% of builders reported formal documented review, while another 41% said review happened consistently but was not documented.
| Market | Builders reporting formal documented review |
|---|---|
| United Kingdom | 23% |
| United States | 36% |
| Sweden | 45% |
“Documented” and “consistent but undocumented” are different controls. Without written records, a business may have less evidence of who approved a system, what data it uses, how it was tested or when it should be reassessed.
Unexpected bills and the human review burden
Cost and oversight were other recurring issues. Among businesses that paid for AI during the prior year, 49% received at least one bill or usage charge higher than expected. The proportion was 57% in the United States and 65% in Sweden. The release does not say whether the surprises came from subscriptions, API consumption, expanded usage or another billing structure.
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Human supervision also takes time. Fifty-five percent of decision-makers said they personally spent at least three hours per week reviewing, editing or fact-checking AI-generated work; 7% spent 10 hours or more. Those figures measure reported time, not a recommended staffing level or a productivity calculation.
Benefits reported alongside the risks
Sixty-nine percent of AI-engaged businesses said AI freed up at least some capacity. At the same time, data-security or privacy exposure was the top-cited risk of employee-built AI in every surveyed market, selected by between 30% and 35% of respondents.
The combination matters for small firms: an internal tool can remove repetitive work while also creating questions about confidential data, access permissions, vendor retention, audit trails and responsibility for errors. Pax8 President and Chief Commerce Officer Nick Heddy described the shift this way: “SMBs are moving from using AI tools to building AI into the way their businesses operate.” He added: “The opportunity is significant, but so are the new demands around governance, security, cost, and accountability.”
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How to read the country and historical comparisons
The combined survey reports a nominal margin of error of approximately ±2.9 percentage points at 95% confidence. Each country subgroup is smaller, so country-level estimates have larger margins and should be treated as directional. The four-market Q3 edition is not directly comparable with Pax8’s earlier U.S.-only editions.
For context, Pax8’s July 13, 2026 Q2 release surveyed 402 U.S. leaders at companies with 5–499 employees. It reported 61% actively using AI and 29% experimenting. That was a different wave, geography and question focus; it is not evidence that the current 67% builder figure rose from 61%.
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What the finding means for a small business
The practical message is not that every firm should develop custom software. It is that many AI-using firms are combining commercial services with their own workflows, agents or integrations. Before putting such a system into regular use, a business should establish:
- an owner accountable for the system and its outputs;
- a written description of permitted data, access and retention;
- testing against realistic failure cases and a process for human escalation;
- usage and spending limits, with alerts for unexpected charges;
- a documented approval and review schedule; and
- a way to disable the system and recover manual operations if it fails.
Pax8’s results show adoption, experimentation and governance happening at the same time. They do not show which approach is most profitable, safest or suitable for a particular company. Those decisions still depend on the firm’s data, staff, risk tolerance and ability to supervise what it deploys.
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