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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsNot overall. AI has made some useful capabilities easier for small and midsize businesses (SMBs) to access, and some firms report concrete benefits. But access to a tool is not the same as an equal ability to use it well. Adoption gaps remain, and larger firms may be better placed to combine AI with the skills, data, investment and operational changes that produce lasting gains.
What would it mean for AI to level the playing field?
For SMBs to compete more evenly with larger companies, AI would need to do more than make certain tasks faster or cheaper. Smaller firms would need to adopt it, integrate it effectively and turn the results into comparable improvements in productivity, service or competitiveness.
The evidence supports a narrower conclusion: AI can help some smaller firms close particular capability gaps, but it does not remove differences in resources or guarantee a competitive advantage. The OECD says AI has significant potential to improve productivity and innovation at SMEs, while warning that differences between leading and other firms could widen.
That distinction matters because many published findings describe adoption or what businesses say they use AI for—not a measured causal effect on profits or the competitive gap between small and large firms.
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What the evidence says—and what it measures
| Source and scope | What it reports | What the finding can establish |
|---|---|---|
| OECD, 2025; analysis of AI adoption by SMEs across G7 economies | Persistent AI diffusion gaps between SMEs and larger firms; productivity returns depend on complementary investment and effective integration into operations. | Adoption and the ability to benefit are not evenly distributed. The report does not provide a universal estimate of AI’s effect on the competitive gap. |
| U.S. Census Bureau, December 2024; U.S. firm-size analysis | Earlier survey data show AI use rising with firm size. In much of 2023 and 2024, very small firms also had relatively high use. | Adoption patterns vary by period and firm size. The source’s analysis does not establish a single current rate that can be generalized to all SMBs. |
| New Zealand Ministry of Business, Innovation and Employment (MBIE), July 2025; data collected April–June 2025 | Businesses reported using AI to improve efficiency, reduce administration and support day-to-day operations. | These are examples of reported uses among New Zealand businesses, not proof that those uses caused higher productivity or profits everywhere. |
| OECD, Generative AI and the SME Workforce, 2025; representative 2024 survey of more than 5,000 SMEs in Austria, Canada, Germany, Ireland, Japan, Korea and the United Kingdom | Six percent of surveyed SMEs reported increased staffing needs and 9% reported decreased needs. | These are survey responses from SMEs in seven countries, not a forecast of net employment effects across all businesses. |
| Singapore Infocomm Media Development Authority (IMDA), 2025; SMEs using AI-enabled solutions through the Productivity Solutions Grant | Average cost savings were 52% in 2024 among SMEs using AI-enabled solutions under the programme. | This is a programme-specific result in Singapore, not a typical return for SMBs generally or a direct comparison with survey findings from other countries. |
| Federal Reserve Bank of San Francisco, March 2026; summary of AI responses in the Federal Reserve’s 2024 Small Business Credit Survey | Owners described uses including individual productivity, content creation, business advice and planning. | Reported tasks illustrate how small businesses use AI; they do not by themselves show improved profit, productivity or competitive position. |
These findings should not be combined into one global adoption rate or trend. They cover different countries, dates, business populations and definitions of AI, and measure different things: adoption, reported use, reported savings or workforce responses.
Where AI can help a smaller business compete
Reported uses point to practical areas where AI may give a small team more capacity: drafting and adapting content, supporting planning, handling some administrative work and helping owners explore business questions. Such uses can make tasks more accessible to a firm with limited staff, but the available examples are not evidence that every business will save time or money.
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The U.S. Census Bureau captured the balance in its December 2024 analysis, Is AI Use Increasing Among Small Businesses?: “While generative AI may not necessarily level the playing field between small and large firms, it can give some small businesses a competitive edge and boost their productivity, resulting in higher adoption of AI among small businesses.” A potential edge for some firms is not the same as an equal advantage across the SMB sector.
Why access alone does not close the gap
The OECD’s central qualification is that productivity returns depend on complementary investment and effective integration into business operations. A tool may be available, but using it well can require changes to how work is organized and the capacity to put its output into practice.
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- Skills: Staff need to know where AI can help, how to review its output and how to apply it to the business’s work.
- Operational fit: A useful result depends on incorporating the tool into real processes rather than treating access as an outcome in itself.
- Investment: Firms differ in their ability to provide the complementary resources needed to capture productivity gains.
- Starting position: The OECD warns that AI may strengthen firms already in leading positions, potentially widening divides rather than erasing them.
The sources establish these as important conditions, but do not quantify how much each one contributes to the gap or provide a universal formula for closing it.
What the evidence says about jobs and staffing
The OECD’s 2025 SME workforce report found modest signs of reported staffing changes in its representative 2024 survey: 6% of surveyed SMEs said their staffing needs had increased, while 9% said they had decreased. These responses describe what participating firms reported; they do not show the net employment effect of AI across all companies or predict what will happen next.
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For an individual SMB, these figures are context rather than a hiring forecast. The broader evidence in this report does not establish a single workforce outcome that applies to every business or task.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What SMBs can reasonably conclude
AI is a potential way to increase capacity in particular tasks, not a shortcut to matching the resources of a larger competitor. The evidence is most useful when read with its scope intact: a local survey describes that place and period; a programme’s savings describe its participating firms; and a reported use does not prove a measured business gain.
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- Consider the task and the result you need, rather than treating AI adoption itself as a competitive outcome.
- Assess whether your team can review and apply AI output within its existing operations.
- Judge reported benefits against their source, population and measurement: adoption, self-reported use, survey responses and observed outcomes are not interchangeable.
- Do not assume that results from one country or public support programme predict the return another SMB will receive.
SMEs matter economically: they account for over 99% of companies and 60% of business-sector employment in OECD economies, according to the OECD’s 2025 report. That scale makes broad access to AI important, but it does not demonstrate that AI has made firms equally competitive.
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