Yes—small businesses using AI were more optimistic about revenue and employment growth than non-users in the Federal Reserve Banks’ 2025 Small Business Credit Survey. The difference reflects expectations for the next 12 months, however, not proof that AI caused growth or that those expectations came true.
What the survey found about AI and growth expectations
A Federal Reserve Bank of New York analysis of the 2025 Small Business Credit Survey found that employer firms using AI had higher net expectations of revenue and employment growth than firms not using AI. A net expectation is the share expecting an increase minus the share expecting a decrease; it is not the percentage of businesses that forecast growth.
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| Expected outcome over the next 12 months | AI users | Non-users |
|---|---|---|
| Net expectation of higher revenue | 48 percentage points | 21 percentage points |
| Net expectation of higher employment | 33 percentage points | 15 percentage points |
These figures come from employer firms responding to the 2025 survey’s AI module, fielded September–November 2025, as analyzed by the Federal Reserve Bank of New York in 2026. The survey included 5,248 employer firms overall. Responses were weighted on several firm characteristics to match the national population of employer firms. Read the New York Fed analysis.
Do the differences remain after accounting for firm characteristics?
Yes. The New York Fed analysis found that the association persisted in statistical models that accounted for measured differences among firms and owners. After controls for owner, firm, and location characteristics, AI users had a 13-percentage-point higher net probability of expecting employment growth. The difference was 10 points after also accounting for past employment changes. For revenue, the adjusted advantage was 14 percentage points after accounting for firm and owner characteristics and past revenue changes.
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The controlled employment and revenue analyses included 4,769 and 4,698 firms, respectively. The estimates strengthen the case that the observed relationship is not explained by the measured factors included in those models. They do not establish that adopting AI caused firms to become more optimistic or will produce better results.
What the numbers do—and do not—say
The leading outcome is owners’ expectations for the coming year, not a verified forecast or a later measurement of revenue and hiring. The New York Fed authors explicitly leave open whether firms using AI will achieve the stronger outcomes they anticipate. Because the analysis is observational, it cannot rule out other explanations, including unmeasured differences between firms that adopt AI and those that do not.
Survey respondents also described their experience with AI, but these reports should not be treated as causal estimates. In the New York Fed analysis, 31% said sales had increased from their firm’s AI use, while 77% reported no change in current labor costs from AI. Those responses describe what participants reported, not what would have happened to the same businesses without AI.
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How common is AI use among small businesses?
The 2025 Small Business Credit Survey report, as cited by the New York Fed, found that 46% of firms with at least one employee used AI and another 15% planned to adopt it within 12 months. Among AI users, 63% said AI was somewhat or very important to production, and 51% said they had partially or fully integrated it into business processes. Use, importance, and integration are different measures: using an AI tool does not necessarily mean it is embedded in core operations.
Other 2026 surveys report higher adoption, but their samples are different and should not be read as a single trend alongside the Fed estimate:
| Source and population | Reported AI use | What to keep in mind |
|---|---|---|
| Federal Reserve Banks’ 2025 Small Business Credit Survey, employer firms | 46%; another 15% planned to adopt within 12 months | AI module fielded September–November 2025; national employer-firm population weighting. |
| U.S. Chamber of Commerce, surveyed small businesses | 66% | The 2026 report also says AI users were at least 7 points more likely to report sales, profit, and workforce growth. This is a reported association, not evidence that AI caused growth. See the Chamber report. |
| Goldman Sachs 10,000 Small Businesses Voices survey participants | 76% | Survey of 1,256 program participants conducted January 27–February 4, 2026; not a representative estimate for all U.S. small businesses. See the survey announcement. |
The survey populations, recruitment methods, dates, and definitions of AI use differ. These percentages therefore cannot be compared as if they tracked the same group of businesses over time.
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What small-business owners say AI helps with—and what gets in the way
The San Francisco Fed’s discussion of 2024 Small Business Credit Survey responses describes a broad range of uses: productivity improvements, content creation, business advice and planning, marketing, email, social media, financial analysis, and specialized industry software. It also records obstacles such as confidentiality concerns, accuracy, limited know-how, and difficulty finding a useful application. The authors caution that it is too early to determine AI’s overall effects on small-business productivity and employment. Read the San Francisco Fed discussion.
Goldman Sachs’ survey of its program participants offers a different view of perceived impact and implementation. Among participants who used AI, 93% reported a positive business impact, 67% expected AI to increase revenue, and 87% said AI augments rather than replaces employees. Fourteen percent said AI was fully embedded in core operations, while 73% said additional training and implementation resources would help. These are participant responses, not estimates for all U.S. small businesses.
That gap between adoption and integration helps explain why “uses AI” can mean very different things. A business may experiment with a tool for one task without changing its core workflow; another may rely on AI across operating processes. As Connie’s Chicken and Waffles co-founder Khari Parker put it: “AI is already helping small businesses compete, save time, and better serve customers — but many of us are still figuring out how to use it effectively,” as quoted in the Goldman Sachs announcement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why AI users might be more optimistic
One possibility raised by the New York Fed analysis is that AI may help some businesses address operational technology challenges. Among AI users, firms reporting such challenges had a 16-percentage-point higher net expectation of revenue growth than AI users who did not report them. That pattern is consistent with the idea that a firm facing constraints may see AI as a way to improve operations or find new capacity. It does not show that AI resolved the challenges or caused higher expected revenue.
Optimism could also reflect factors the analysis cannot fully separate, such as owners’ expectations, business plans, or differences in how firms choose to adopt technology. The evidence supports a relationship between AI use and more positive expectations; it does not identify a single mechanism.
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The survey offers a useful signal about how AI-using businesses view the year ahead, but it is not a promise of higher sales or a reason by itself to adopt a tool. A practical decision should begin with a business problem rather than the adoption statistic.
- Identify a specific task or bottleneck where a tool could help, such as drafting routine content, organizing information, or supporting analysis.
- Consider whether the tool can be used safely with the business’s customer, employee, and financial information, and check outputs for accuracy.
- Assess the time, skills, and process changes required to integrate it; occasional use and operational integration are not the same.
- Track concrete outcomes relevant to the task—such as time spent, error rates, sales inquiries, or labor costs—rather than assuming that optimism or adoption figures predict results.
These are decision considerations, not outcomes tested by the surveys. The sources do not establish which specific tool, implementation approach, or training program will deliver a return for an individual business.
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