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Small Businesses Are Using AI—Here’s What’s Actually Working

According to a recent whitepaper from the U.S. Chamber of Commerce Foundation and Hiring Our Heroes, small businesses are using AI to save time, streamline operations, and improve productivity. Here’s what’s working, what’s holding businesses back, and how to get started.

AI is delivering real, immediate value—but mostly through simple use cases like admin tasks, scheduling, safety monitoring, and reporting—not complex transformations.
Adoption is growing, but still uneven, held back by cost concerns, unclear ROI, fragmented data, and especially a lack of workforce training.
The most successful small businesses start small and focus on real problems, using AI to support employees (not replace them) and building from early wins.

Artificial intelligence is moving quickly from experimentation to real-world use among small and mid-sized businesses, particularly in industries like construction, manufacturing, and home services. While awareness is high—most business owners understand how AI could apply to their operations—many are still in early stages of adoption. That said, momentum is building: a growing share of small businesses view AI as essential to staying competitive, especially as they face ongoing pressures like labor shortages, rising costs, and increasing customer expectations.

Where AI is gaining traction, the impact is practical and measurable. Small businesses are using it to streamline routine tasks like drafting emails, generating marketing content, summarizing documents, and managing schedules—often saving hours each week. In more operational environments, AI is helping improve jobsite safety, optimize staffing and scheduling, and predict equipment maintenance issues before they cause downtime. These early wins show that AI can boost productivity, reduce errors, and improve efficiency, even without large investments or fully integrated systems.

However, scaling AI remains a challenge. Many small businesses lack the data infrastructure, internal expertise, and training needed to move beyond isolated pilots. Workforce readiness is the biggest limiting factor, with very few employees receiving formal AI training. At the same time, concerns around cost, unclear return on investment, and compliance risks continue to slow adoption. The clearest path forward, according to early adopters, is to start small—testing AI on real, day-to-day problems—while investing in training, leveraging trusted partners, and keeping humans in the loop to ensure accuracy, trust, and long-term success.

[Read the full report: AI in Action: Early Lessons from Small Businesses on the Front Lines of Adoption]

CO— aims to bring you inspiration from leading respected experts. However, before making any business decision, you should consult a professional who can advise you based on your individual situation.

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