Small businesses' increasing dependence on AI tools is necessary for their competitiveness against larger corporations

What's this about?

People disagree about whether small businesses need AI tools to keep up with big companies. AI can help, but we do not know that every small business must depend on it.

What supporters say

• AI can handle repeat jobs that might otherwise need more workers or costly support systems.
• It can help small teams make choices and offer services once easier for big companies.
• One study found AI raised work speed by about 14 percent in customer support.
• AI helped newer and weaker workers most, which may help teams with less training.

What critics say

• The proof does not show that every small business needs AI to keep up.
• Small firms use AI at different rates, especially if they already use many digital tools.
• Some firms may face problems if rivals use AI to reply faster or give better service.
• We still need more proof about which businesses gain most from AI tools.

The bottom line

AI can help small businesses work faster and close some gaps with big companies. But the evidence does not show that growing AI use is necessary for every small business.

Small businesses are increasingly turning to artificial intelligence to match the speed and scale of larger corporations. But while AI can be a powerful tool, the evidence does not show that growing dependence on it is required for every small business to stay competitive.

The case for

AI can help smaller firms fill gaps that would otherwise require more staff, specialist knowledge or expensive customer-service systems. It can automate routine work, support decisions and help businesses offer services that once were easier for large companies with deeper resources to provide. That gives AI real potential to narrow the capability gap between small firms and major corporations. 1

The clearest evidence comes from a field study of customer-support workers. It found that access to AI raised average productivity by about 14 percent, with the biggest improvements among less experienced and lower-performing employees. AI appeared to spread some of the methods used by stronger workers, which could be especially useful for small teams that lack specialist staff or extensive training budgets. 3

There is also a concern that slower adoption could leave some small firms behind. Small and medium-sized businesses generally adopt AI more slowly than large firms, and use is concentrated among companies that are already bigger and more digitally advanced. In industries where rivals use AI to respond faster, improve service or handle knowledge-heavy work, choosing not to adopt it may create a competitive disadvantage (see Figure 1). 2

Reviews of small-business AI use identify possible gains in automation, decision-making and new products or services. The OECD has similarly said AI could improve productivity and competitiveness for small and medium-sized enterprises. For firms in information-heavy or digitally delivered industries, the technology may therefore become strategically important.

The case against

The central problem with the claim is that using AI is not the same as being competitive. A company’s success depends on many other factors: its skills, data, digital systems, management, finances and ability to redesign work around new technology. Firms that are already stronger may also be more likely to adopt AI, making it difficult to say that AI alone caused their better performance. 4

AI’s benefits are also highly dependent on the task. An experiment involving consultants found that AI improved results when workers used it on tasks within the technology’s proven strengths, but made performance worse on tasks beyond those limits. In other words, blindly relying on AI can harm rather than help a business when the tool is used for the wrong job. 5

Small firms may face particular obstacles in putting AI to work. Research repeatedly points to the cost of tools, weak data, shortages of expertise, limited infrastructure, lack of trust and the complexity of implementation. Training employees, integrating systems, checking AI output and changing business processes all require time and money. For a resource-constrained company, those costs can outweigh the operational gains. 6

There are also risks around privacy, security and accountability. Guidance from the US National Institute of Standards and Technology and the Federal Trade Commission warns that AI can produce false information, encourage overreliance, expose private data and create cybersecurity, intellectual-property and data-protection problems. These risks are especially serious where businesses handle confidential information or make high-stakes decisions, and they create further costs for verification and incident response. 7

The bottom line

The evidence strongly supports a more limited conclusion: AI can be an important and sometimes competitively valuable tool for small businesses, but increasing dependence on it is not proven to be necessary for competitiveness against larger corporations.

The best-supported approach is selective and carefully managed adoption. Small firms are most likely to benefit when they use AI in workflows where results can be measured, the technology has demonstrated strengths, and people remain available to review its work. The customer-service study shows that substantial gains are possible, while the consultant experiment shows that poor task fit can reverse those gains.

Competitive pressure will vary by industry, country, business model and a firm’s own resources. Existing research is concentrated in specific settings, such as customer support and consulting, rather than across all small businesses. There is no evidence identifying a general point at which a company that does not become more dependent on AI necessarily loses its ability to compete. Confidence in this qualified conclusion is high, though unresolved questions about potential conflicts of interest and the limited reach of task-specific studies remain.