Small Business AI Adoption Surges While Most Owners Admit Needing More Training
In the summer of 2026, something quietly shifted on Main Street. Across America's small businesses—from plumbing companies to boutique law firms—AI tools have become table stakes. Yet behind the headlines sits an uncomfortable truth: adoption is outpacing understanding by a signi
In the summer of 2026, something quietly shifted on Main Street. Across America's small businesses—from plumbing companies to boutique law firms—AI tools have become table stakes. Yet behind the headlines sits an uncomfortable truth: adoption is outpacing understanding by a significant margin.
New data from Thryv's 2026 AI and Small Business Adoption Survey reveals the scale of this disconnect. While AI adoption among U.S. small businesses has climbed to 66%, up from just 55% a year ago, an even more striking statistic emerged: 70% of business owners admit they need more training to use the technology effectively.
This paradox—high adoption coupled with high uncertainty—creates what experts are calling a "competence gap." The survey of 561 small and mid-sized business decision-makers (none Thryv customers) found that 86% feel comfortable using AI, yet seven in ten still want more education on how to deploy it productively.
Comfort Is Not Competence
The disconnect between feeling at ease with technology and actually wielding it well is at the heart of the problem. As Grant Freeman, President of Thryv, noted, "Being comfortable isn't the same as being effective—and that gap is starting to show."
Many business owners equate using AI with asking ChatGPT a question or generating a social media post. But true proficiency demands more: understanding how to craft precise prompts, protect sensitive customer data, evaluate output quality, and integrate AI into existing workflows without compromising privacy or accuracy.
The consequences of this knowledge gap are already appearing in real-world scenarios. A florist might use AI to speed up customer responses, only to accidentally share incorrect promotion dates. A roofer can generate a polished Google ad in seconds, but if they don't understand what matters to homeowners in their local market, that ad may sound professional while missing the things that actually drive conversions.
The DIY Training Trap
Perhaps most concerning is how small businesses are attempting to close this gap themselves. The survey revealed that training sources reflect a patchwork approach: 57% rely on YouTube and social media, 49% turn to online resources and webinars, while 31% ask AI tools themselves for guidance on using AI.
While this DIY mindset fits the entrepreneurial spirit, it creates vulnerabilities. Ken Cook of The Prepared Group warned, "The biggest mistake small businesses can make is blindly trusting AI. Use it only for tasks you already understand. Otherwise, you run the risk of moving faster in the wrong direction."
Without structured training, businesses may miss critical nuances around data privacy, hallucination risks, or industry-specific compliance requirements. They might also overlook how to verify AI-generated content before publishing it publicly.
The Path Forward
Despite these challenges, the rewards are real. The same survey found that 70% of AI users reported increased revenue over the past year, while 55% saw cost reductions. More than half spend at least $100 monthly on AI tools, and 92% say the technology saves them time—with many expecting to regain between 11 and 60 hours per month.
The businesses that will thrive are those recognizing that AI literacy is not optional. It requires moving beyond experimentation to intentional learning: identifying specific business problems before seeking solutions, establishing regular training schedules, maintaining a "trust but verify" mindset, and connecting with industry peers facing similar challenges.
AI isn't replacing small business workers—yet—but it is fundamentally reshaping how work gets done. As Freeman put it, "Businesses that invest in AI tools and the training needed to maximize them will define what Main Street looks like five years from now." The question isn't whether to use AI anymore. It's whether we'll know how to use it well enough to survive.