AI for small business growth: why more AI adoption may mean more staff, not fewer

Small businesses that adopt AI are more likely to hire additional workers, not replace them, according to testimony before the House Small Business Committee. The data challenges the common fear that AI will eliminate jobs and instead points to a pattern where AI for small business growth and hiring leads to staff expansion.

What happened

Jordan Crenshaw, senior vice president at the U.S. Chamber of Commerce’s Technology Engagement Center, told lawmakers that 58% of small firms nationwide reported using generative AI last year, up from 40% in 2024 and 23% in 2023. More importantly, 82% of small businesses using AI had increased their staff headcounts over the past year. “These businesses are not using AI to replace people,” Crenshaw said. “They’re using it to help employees focus on high value work that requires judgment, creativity and relationships.”

Qaiyum, owner of Merz Apothecary, a health and beauty retailer, testified that his company increased staff by 20%, from 50 to 60 employees, after adopting AI tools. He described building an AI agent to handle routine accounts payable work that previously consumed more than 20 hours per week of one employee’s time. The company also uses AI for cash flow analysis, inventory tracking, expense management, payroll, and risk monitoring.

Crenshaw warned that without federal AI regulation, a costly state-by-state patchwork could emerge. He cited an Information Technology and Innovation Foundation (ITIF) study estimating that lack of national AI data privacy rules could cost the U.S. roughly $1 trillion over the next decade, with $200 billion borne by small businesses. He also noted that California’s AI-related compliance costs under the California Consumer Privacy Act could reach about $16,000 annually per small business.

Why AI builders should care

For product teams building AI tools for small businesses, the hearing reinforces a critical design principle: build to augment, not replace. The witnesses framed AI as a capacity multiplier that lets employees focus on strategic work. Tools that automate routine tasks like accounts payable, cash flow analysis, and inventory tracking are in high demand, and they directly enable headcount growth.

The push for a national regulatory framework also matters. If state-level compliance costs rise, small businesses may delay AI adoption. Builders who design with governance in mind, such as transparent data handling and model explainability, will be better positioned as regulation evolves. The call for increased AI literacy funding through the SBA signals a growing market for training and onboarding tools.

Practical implications

Small businesses are already deploying AI for specific operational tasks. The Merz Apothecary case shows a pattern: automate repetitive finance and operations work to free staff for growth-oriented activities. Common use cases include:

• Accounts payable automation
• Cash flow analysis and forecasting
• Inventory tracking and reorder alerts
• Expense and payroll management
• Financial risk monitoring

These are not speculative applications. They are live implementations that have led to hiring. For AI builders, this suggests a clear product-market fit for vertical-specific agents that handle back-office tasks. The key is to position the tool as a team member that increases capacity, not as a cost-cutting measure.

Caveats

The evidence presented is primarily testimony and industry commentary, not long-run empirical data. The ITIF study cited by Crenshaw comes from a think tank that receives significant tech sector support. The $1 trillion cost estimate and $16,000 California compliance figure are projections, not confirmed costs. Additionally, the hearing did not result in any legislative action, so the regulatory landscape remains uncertain. Builders should monitor state-level developments but not over-index on any single forecast.

Despite these caveats, the core message is consistent: small businesses that adopt AI for augmentation tend to grow and hire. For AI builders, this is a strong signal to focus on tools that amplify human work rather than replace it.