For years, small businesses lagged far behind large corporations in adopting artificial intelligence. That gap is now closing — fast. What was once a multi-year divide has narrowed to roughly a year, thanks to more accessible AI platforms and a key structural advantage: fewer approval layers, faster decision-making, and the agility to experiment freely.
More remarkably, in areas like marketing automation, small businesses are deploying AI at rates that rival large enterprises — a reversal of the traditional pattern where major corporations adopt emerging technologies first.
According to a recent survey by Thryv, AI usage among small and midsize businesses in the United States jumped from 39 percent in 2024 to 55 percent in 2025, a 41 percent year-over-year increase. A separate McKinsey report found that globally, 78 percent of companies now use AI in at least one function, with those employing between 10 and 100 people leaping from 47 percent to 68 percent adoption in a single year. The numbers suggest that small firms are catching up to enterprise adoption levels much faster than any previous technological wave predicted.
The way small businesses are deploying AI also differs sharply from large enterprises. While corporate giants focus heavily on IT process automation and cybersecurity, smaller firms are placing AI directly in customer-facing functions — marketing, customer engagement, and service delivery. Many of them see AI as a growth engine. Nearly eight in ten small business owners believe that AI for marketing and customer engagement will have the greatest impact on their operations. Most are eager to automate marketing content creation, and many are already exploring AI-driven customer service tools.
By contrast, larger corporations tend to concentrate their AI efforts on the back end — IT systems, infrastructure, and threat detection. For small businesses, the focus is on driving revenue and improving customer experience.
For these firms, the payoffs are increasingly clear. Ninety-one percent of small businesses using AI report revenue boosts, while 87 percent say the technology helps them scale operations and 86 percent see improved profit margins. The typical business reports saving more than 20 hours per month and between $500 and $2,000 in monthly costs. And for those that have moved beyond experimentation into systematic AI use, the rewards are even higher: more than half of small businesses that adopted generative AI say their revenues increased by 10 percent or more.
“What sets successful SMBs apart is how quickly they translate AI from concept to daily utility,” said Anirudh Agarwal, the chief executive of OutreachX. “The ones integrating it into routine operations are not just saving time, they’re creating measurable, repeatable performance gains that strengthen long-term competitiveness.”
Contrary to widespread fears of AI-induced job losses, small businesses using AI report net-positive effects on employment. A third of entrepreneurs who use AI say they’ve upskilled existing employees, and more than 80 percent have expanded their workforce in the past year. Job postings from small and midsize firms seeking AI expertise rose 44 percent between January and July 2025. Rather than displacing workers, AI is functioning as a capacity multiplier, allowing small businesses to handle more work, serve more customers, and grow their teams.
Still, one major challenge remains: training. Ninety-five percent of small-business decision makers say they need more AI education, even though nearly three-quarters describe themselves as AI experts. The reality is that skill gaps persist across all industries, and small businesses are no exception. Among employees who have received formal AI training, nine in ten report improved performance, suggesting that education is a powerful but underused lever.
This training gap is what some analysts call the execution problem — the divide between early adoption and sustainable transformation. For small businesses, the difference between a short-lived experiment and a long-term competitive edge often comes down to whether they institutionalize AI knowledge. Those that build lightweight, role-based training programs and identify a few “power users” to lead implementation are the ones most likely to turn early wins into enduring operational advantages.
Whether the narrowing AI gap continues to close, stabilizes, or widens will depend on several shifting factors — how quickly enterprises ramp up their AI investments, how accessible advanced tools become to smaller firms, and which side solves the training deficit first. But what the current data makes undeniable is that small businesses are no longer merely catching up. They are, in many cases, leading the charge in using AI where it matters most: driving growth, serving customers, and building resilience.
In the age of AI, speed is starting to beat scale. And right now, the fastest movers are not the Silicon Valley giants — they’re small businesses quietly redefining what it means to compete.