Small businesses can turn flexibility into an advantage when adopting AI: they can test a focused use case without waiting for a large-scale transformation. But speed alone does not make adoption successful. A clear business goal, a leader who owns the decision, employee involvement, and a plan for security and ongoing costs matter more than adopting AI for its own sake.
Why flexibility can help a small business adopt AI
A smaller organization may be able to choose a recurring task, try an AI tool, and decide quickly whether it helps. That can make a bounded experiment easier than coordinating a broad rollout across many departments. The advantage is potential, not a guarantee: limited staff time, technical skills, and maintenance capacity can also make implementation harder.
In an ITPro report on Dell Technologies research about UK small businesses, 66% viewed AI as a route to growth and 56% said it could provide a competitive advantage. The same report said around 7% of firms surveyed were “AI front runners” who reported freeing six or more hours each week with AI; more than half of those front runners had clearly defined use cases. These are findings attributed to Dell as reported by ITPro, not proof that a particular strategy caused the results or that they apply to all small businesses. ITPro’s report
The report also said 61% of larger firms viewed greater flexibility as a key advantage for small and medium-sized businesses. Dell Technologies UK small business country manager Brian Horsburgh told ITPro: “Smaller businesses can have an advantage because they’re often more flexible and can move faster than larger businesses, so starting with one or two key opportunities can potentially have an outsized impact.”
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Start with a business problem, not an AI tool
Before choosing a product, identify a task or customer need where assistance could make a difference. A useful candidate is specific enough to test and important enough to justify staff time. For example, a business might examine a repetitive drafting or information-sorting task—but it should first check whether the work is suitable for AI and whether the tool can handle the relevant data safely.
- Name the task and the people who do it.
- Describe the improvement you want, such as less time spent on a defined step or a smoother customer response.
- Decide how you will assess the result, including quality, human review, cost, and risk.
- Identify information the tool must not receive and any decisions that must remain with a person.
Horsburgh told ITPro: “Adopting AI means identifying ways it can help you do more of what helps your business grow and in fact, the number one piece of advice that came through from businesses of all sizes is to start small and iterate.”
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Make leadership accountable and involve staff
Leadership sponsorship means more than approving a subscription. Someone should own the goal, make time for a trial, and decide whether it is safe and worthwhile to expand. Horsburgh told ITPro: “Having the right strategy is critical. Our research shows that those who are gaining the most from AI today say that AI use is coming from leadership as a priority.”
Employees who perform the work can identify exceptions, quality problems, and risks that a manager may not see. Involve them in selecting the task and reviewing outputs; explain what the tool may and may not be used for. In a 2026 U.S. Chamber of Commerce report, 95% of U.S. small businesses using AI said they were working to upskill employees. That is a survey finding, not a guarantee that training alone produces better outcomes. U.S. Chamber of Commerce report
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Run a bounded pilot and decide what happens next
- Set boundaries. Define the task, users, duration, permitted data, and the human checks required. Avoid using sensitive customer or business information until the tool’s data handling and your obligations have been reviewed.
- Establish a baseline. Record how the task is handled now, including time, cost, quality expectations, and common failure points.
- Test with oversight. Have staff review outputs, correct errors, and note when the tool is unhelpful. Do not let a pilot silently become an unreviewed production process.
- Review the evidence. Compare usefulness and quality with the baseline, and account for setup, training, review, integration, and maintenance time.
- Choose deliberately. Continue or expand only if the benefit is meaningful and risks are manageable; change the workflow or stop if it is not. Reassess as the tool or business needs change.
Account for the work and risks beyond the trial
Access to an off-the-shelf AI product is not the same as securely integrating it into business operations. The OECD’s 2026 D4SME survey included more than 2,000 SMEs across 12 OECD countries, but the OECD explicitly describes the sample as non-representative. Its findings distinguish common use of off-the-shelf products from more uneven strategic, targeted, and secure integration. OECD, “Empowering SMEs in the age of AI”
Before expanding a pilot, account for the practical demands that can be easy to overlook:
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- Skills and time: Staff need time to learn the tool, check its work, and raise problems. Training and implementation knowledge are recurring constraints.
- Integration and upkeep: Connecting a tool to existing workflows may require system changes, ongoing maintenance, or support that a small team cannot absorb casually.
- Privacy, security, and intellectual property: Understand what data the service receives, how it is handled, and whether the use is consistent with your contracts and obligations.
- Accuracy and accountability: AI output can be wrong or unsuitable. Decide who reviews it and who is responsible for the final customer-facing or operational decision.
- Human interaction: Automation may be a poor fit where trust, judgment, empathy, or a personal relationship is central to the value being delivered.
These concerns are reasons to define safeguards, choose a different task, or wait—not reasons to assume every use of AI is unsuitable. The Federal Reserve Bank of San Francisco’s qualitative analysis of responses to the 2024 Small Business Credit Survey said nearly 40% of small-business respondents reported using or planning to use AI. That combined measure includes plans as well as current use; it is not the share already using AI. Federal Reserve Bank of San Francisco analysis
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Read adoption statistics in context
Reported AI adoption rates vary because surveys cover different populations, geographies, dates, and definitions of “using AI.” They should not be treated as a single trend line. For example, Goldman Sachs reported that 76% of respondents in its 10,000 Small Businesses Voices survey were currently using AI, 93% of AI users reported a positive business impact, and 14% said AI was fully integrated into core operations. The survey covered 1,256 program participants, was conducted by Babson College and David Binder Research from 27 January to 4 February 2026, and included all 50 U.S. states, Washington, D.C., and Puerto Rico. Its results describe those program participants, not a random sample of all U.S. small businesses. Goldman Sachs survey release
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The UK Government’s AI Adoption Research page describes work on how UK businesses are adopting AI, the barriers they face, and impacts across sectors; it was published on 28 January 2026 and updated on 13 February 2026. UK Government, “AI Adoption Research”
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