Owners hear two stories. In one, AI is everywhere and you are falling behind. In the other, most companies are barely using it. The statistics seem to support both. They do, because the surveys measure different things on different groups.
The numbers
| Source | Who was surveyed | What it found |
|---|---|---|
| U.S. Census Bureau, Business Trends and Outlook Survey (data collected Dec. 2025 to May 2026) | Businesses across the U.S. economy, all sizes | 19.8% reported using AI as of May 3, 2026, and between 20% and 23% expected to in the next six months.[1] |
| Homebase (2026) | 750 owners and managers at small businesses with 5 to 499 employees and hourly teams | 74% using or piloting AI, up from 64% in 2025 (a different sample).[2] |
| Bluevine (April 2026) | 942 owners and financial decision-makers at businesses with 2 to 249 employees and $50,000 to $5 million in revenue | 74% using or actively testing AI; 33% use it regularly across multiple areas.[3] |
| McKinsey (May to June 2026) | 1,719 respondents in 97 countries | Nearly nine in ten report regular use of AI in at least one business function; 37% attribute some EBIT impact to AI.[4] |
Why they differ
- Different populations. The Census Bureau samples the whole economy, including sole proprietors and firms with a handful of people. The Homebase, Bluevine and McKinsey samples are narrower and tilt toward businesses already engaged with technology, finance software or large organizations.
- Different definitions. "Using AI" can mean a company-wide deployment, one person using a chatbot or "using or piloting." The Census supplement asks about use across 15 business functions,[1] while the private surveys count use or testing.
- Different respondents. Online panels reward people willing to answer a survey about AI. Sponsors, such as payroll and banking companies, also have reasons to find interest in technology.
- Different timing. Adoption moved quickly. A number from last year is a different number.
Neither side is lying. The Census figure is the better estimate of the whole economy. The private surveys are better windows into businesses that are close to your type of customer. Do not average them.
The detail inside the Census data
The Census Bureau reported that 37% of firms with at least 250 employees and 32% of firms with 100 to 249 employees used AI, compared with a national rate of 19.8%. Use did not change significantly among firms with fewer than 20 employees over the period, and fewer than 20% of firms with four or fewer employees reported using it. By industry, information was at 39.7% and finance and insurance at 33.9%, while retail trade was around 14%.[1] If you run a business with 10 to 75 employees, you sit in between: ahead of the smallest firms, behind the largest.
The number that matters more than adoption
Adoption tells you who tried. Results tell you who gained. In McKinsey's survey, 37% attribute some EBIT impact to AI, and about 6% of respondents were high performers, nearly three-quarters of whom report fundamentally redesigning workflows.[4] In the Bluevine survey, 52% of AI-using small businesses reported a return, and 24% had not yet seen one.[3] Plenty of companies use AI. Fewer can show it paid for itself.
What to do with this
- Do not decide on fear. "Everyone else is doing it" is not a business case. Many of them are testing, not benefiting.
- Do not decide on complacency either. If your competitors save time on quotes and follow-up, you will feel it.
- Compare yourself on workflows, not on the word "AI." Ask: how fast do we answer leads, how long does it take to send a quote, how many days to close the books? Those are the things customers and your margin respond to.
- Pick one workflow and measure it. Our articles on picking a first workflow and calculating return walk through the method.
- Take reported savings with salt. Survey respondents estimate their own gains, and survey sponsors often sell the tools being measured.
The real question is not whether you use AI. It is whether a specific process in your business is slow, costly or error-prone enough to be worth fixing, and whether AI is the cheapest way to fix it. Sometimes it is not.
Sources
- U.S. Census Bureau, "Large Firms With at Least 20 Employees Biggest AI Users" (May 2026)
- Homebase, "2026 Main Street AI Gap Report"
- Bluevine, "2026 Small Business AI Trends Report"
- McKinsey, "The state of AI in 2026: On the road to ROI"
Figures are quoted from the sources above and were reviewed in October 2026. Where a source is a secondary summary of other research, we say so in the text. Survey results reflect each survey's own sample and definitions. Examples labeled as illustrations use made-up numbers to show the method. Nothing here is a forecast or a guarantee of results.
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