Many small businesses are trying AI, but far fewer have made it a dependable part of core operations. The gap is not simply access to software: businesses also need time, training, workflow changes, integration, and safeguards to use AI effectively. The available surveys point to that implementation challenge, but their different samples and definitions mean no single figure represents every small business.
AI use is growing, but experimentation is not the same as integration
In a survey of 1,256 participants in its 10,000 Small Businesses program, Goldman Sachs found that 76% said their business currently used AI, while 14% said AI was fully embedded in core operations. The survey’s fieldwork ran from January 27 to February 4, 2026. These figures describe that program’s participants, not a nationally representative sample of all U.S. small businesses. Goldman Sachs 10,000 Small Businesses Voices
Other estimates use different methods and populations. The U.S. Census Bureau’s Business Trends and Outlook Survey (BTOS) showed overall U.S. business AI use ranging from 17% to 20% in data collected from December 14, 2025, through May 3, 2026; firms with four or fewer employees had use below 20%. The overall range covers businesses generally, not only small businesses. Census changed its question in November 2025 from asking about AI in producing goods or services to asking about AI in any business function, so comparisons across that change require caution. U.S. Census Bureau
The U.S. Chamber of Commerce reported that 66% of small businesses used AI in its 2026 report, but the summary available for that report does not provide enough methodological detail to reconcile its estimate with Census or Goldman Sachs. These figures should not be averaged or treated as equivalent. U.S. Chamber of Commerce
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International evidence has its own limits. The OECD’s 2026 D4SME survey covers more than 2,000 SMEs across 12 OECD countries, but its sample is explicitly non-representative. It describes use of off-the-shelf AI products alongside uneven strategic, targeted, and secure integration; it does not establish a universal adoption rate. OECD
What the services gap actually involves
The difference between trying a tool and relying on it in daily work is where practical implementation support matters. In the Goldman Sachs survey, 73% of participants said additional access to training and implementation resources would help. Respondents also cited difficulty choosing tools, insufficient technical expertise, and data privacy concerns. Goldman Sachs 10,000 Small Businesses Voices
The Chamber reported that 95% of its small-business respondents already using AI were working to upskill employees. That result comes from a separate survey and should not be combined with the Goldman Sachs figure. U.S. Chamber of Commerce
Other barriers are less about selecting a product than making it work in a real business:
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- Training and infrastructure: The Federal Reserve Bank of San Francisco’s qualitative review of the 2024 Small Business Credit Survey describes limits on staff time and capacity for training and system upgrades, as well as gaps in knowledge about implementation strategies. Federal Reserve Bank of San Francisco
- Trust and fit: Businesses raised concerns about accuracy and intellectual property, as well as privacy. Some chose not to adopt AI because human interaction was central to their work or AI did not seem applicable. Federal Reserve Bank of San Francisco Goldman Sachs 10,000 Small Businesses Voices
- Security and compliance: The OECD points to cybersecurity and secure integration as important digitalisation challenges. The Chamber reported that six in ten small businesses worried about increased litigation and compliance costs from a patchwork of state privacy and AI laws. OECD U.S. Chamber of Commerce
Where small businesses are applying AI
The San Francisco Fed’s qualitative review describes uses ranging from basic task assistance to complex, integrated systems. Examples include productivity tasks; marketing, social media, and search engine optimization; written communications; visual generation and graphic design; customer service; analytics and forecasting; programming machines and sensors; and custom AI tools. These are illustrations of reported applications, not a ranking of how common each one is. Federal Reserve Bank of San Francisco
That range helps explain why implementation can be difficult. A tool that drafts routine text poses different workflow, review, and data questions from one connected to customer service, business systems, or equipment. Support that helps one firm may not suit another.
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How to assess AI implementation help
There is no verified provider comparison or evidence that one implementation route is best. If you are evaluating a consultant, service, or internal project, use the documented obstacles to ask concrete questions:
- Workflow discovery: Will the provider first identify a narrow task and agree on a measurable outcome?
- Tool selection: How will options be assessed against your existing systems, budget, and data sensitivity?
- Staff readiness: What training is included, and where will a person review AI output?
- Integration and process change: Does the work cover system connections and the changes employees will need to make?
- Risk controls: How are privacy, security, accuracy, and intellectual-property concerns handled?
- Ownership after launch: Who maintains the system, handles problems, and measures whether it is delivering the intended result?
This checklist is a practical synthesis of reported barriers, not a tested standard. The available evidence does not establish market-wide provider counts, typical service prices, or comparable returns on investment, so those claims should be checked directly with prospective providers.
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Adoption is not automatically useful for every business. The San Francisco Fed’s review includes firms that held back because the work depended on human interaction or because AI did not seem relevant. A sensible decision starts with the business task and its risks, not with pressure to adopt a tool. If a use case is unclear, the workflow is already working well, or the required safeguards and upkeep are beyond the firm’s capacity, choosing not to use AI can be a reasonable outcome.
As Khari Parker, co-founder of Connie’s Chicken and Waffles in Baltimore, 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.” He added: “With the right guidance and training, AI can be transformational for Main Street.” Goldman Sachs 10,000 Small Businesses Voices
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