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For small businesses, AI is rapidly becoming a finance tool — helping them forecast cash flow, track payments, and generate reports in minutes rather than hours. And that poses a challenge for the community banks and credit unions that serve them, because much of this is happening outside their platforms, and outside their relationships.
Research tells the story of a fast-transitioning marketplace. In Intuit’s most recent Small Business Insights survey, more than 70% of small businesses reported regularly using AI tools. A smaller survey, by Small Business Expo, cites similar usage levels and notes that 79% of those using AI reported measurable reductions in costs or improvements in efficiency. Meanwhile, aiming squarely at the heart of the traditional lender’s value proposition, a recent Forbes article described how AI is helping small businesses identify new funding sources while enabling alternative lenders to assess creditworthiness more quickly — creating an opening for fintechs and others to bypass banks.
But the power of AI is equally at the disposal of those who traditionally serve these small business customers. For community banks and credit unions, AI’s strategic threat is also a strategic opportunity.
Financial institutions that integrate AI-driven financial insights into their digital experiences can remain central to their customers’ financial operations. But those that don’t may find small business customers moving somewhere else.
Why, and How, Small Businesses Are Leaning In
To understand what’s at stake for community banks and credit unions, it helps to start with what small businesses actually value about AI — because, for the moment at least, it’s less about transformation than about relief.
Small business finance teams are usually very small. In many cases, the entire financial operation may be handled by a single person, who is responsible for bookkeeping, financial analysis, reporting, forecasting, and vendor management. AI tools free these individuals to add value elsewhere and head off the need to add additional full- or part-time resources.
Use cases include analyzing transaction histories and forecasting cash flow, categorizing vendor spending, tracking supplier cost changes, and flagging upcoming payments. In many use cases, business owners find themselves routinely asking AI to confirm whether payments have cleared or a deposit has arrived, bypassing their banking portal entirely. Clients are also using AI for reporting, including to generate templated summaries needed for month-end close, and craft documents for shareholders or boards.
Such work previously consumed hours of manual effort and — traditional financial institutions take note — relies almost entirely on basic data pulled from a business banking account. To access it, some users are simply exporting CSVs and dropping them into AI. Others may be using QuickBooks’s built-in AI. And more sophisticated businesses are using MCP servers, granting LLMs access to read their account data.
Reasserting Primacy Amid AI’s Steady Advance
The growth of readily-available AI-powered financial analysis introduces a structural challenge for financial institutions because it positions the bank as a passive source of data rather than the center of the customer’s financial activities.
This dynamic has major implications for bank primacy. Historically, the primary financial institution was the one where customers logged in most frequently to review balances, monitor activity, and manage finances. As AI tools become more capable, customers may begin interacting more with external assistants than with their bank’s digital channels, reducing loyalty.
“Community banks and credit unions are now asking if this shift means they will have less traffic to their mobile app or digital banking platforms, and the answer is yes,” said Yaro Melnyk, Group Technical Product Manager, Narmi, in an interview with The Financial Brand. “In the same way that banks had to digitize and then create mobile apps, and there was a process for doing that, they’re going to have to adjust to this new reality where LLMs are a new channel to engage with customers.”
But community banks and credit unions can remain central to customer relationships by embedding purpose-fitted AI tools that help businesses understand and manage their finances.