Can AI Close the Small-Business Funding Gap Government Never Could?

Most Americans who start a business more or less do it on their own dime. They raid their savings, lean on family, maybe max out a credit card, and then hope. Kauffman Foundation research found that 83% of new employer businesses had no capital from banks or other funding institutions, and 65% tapped family or personal savings.

That says a lot about the can-do spirit of people who bet on themselves. It also says something less flattering about the system around them. Independent business is one of the great freedoms of a free economy, yet too many people who try it run out of runway before they find their footing.

Look at why businesses close. The Global Entrepreneurship Monitor reports that an inability to obtain financing drives 11% of exits worldwide, and lack of profitability another 23%. Those two are linked more often than not. Owners almost always need more time and money to reach their customers than they planned for, and a little extra capital buys that time. Think of the restaurant in your neighborhood you kept meaning to try. It's gone now, and you never got around to eating there.

The French economist Frédéric Bastiat warned us about this. In his essay on what is seen and what is not seen, he argued that we notice the visible results of economic policy and miss the businesses that never got to exist. Every closed storefront is the seen. The unfunded idea that never opened is the unseen, and we'll never know what it would have become.

The government patch

Government does sometimes fill the gap. New research shows disaster recovery loans cut the likelihood of business exits by 13 percentage points. That's a real effect, but those loans are for emergencies, not everyday growth and expansion.

The everyday option is the Small Business Administration's 7(a) loan, and it isn't always within reach. The paperwork burden alone shuts out many owners who'd rather spend their hours serving customers than filling out forms.

It's also gotten pricier. Rates are pegged to the prime rate, which was 3.25% in October 2021 and hit 7% in September 2026. In practical terms, the maximum rate on a loan up to $25,000 is now 13.5%, versus 7.5 to 8% in 2021. That beats most credit cards, but for a small operator it's still a heavy line item.

Ludwig von Mises argued that without genuine market prices and private ownership, planners can't calculate where capital does the most good. Friedrich Hayek made a related point in his famous 1945 essay on the use of knowledge in society: the facts that matter most are scattered among millions of people, and no agency can gather them in one office.

Murray Rothbard went further and called the state a coercive monopoly that has no incentive to improve. You don't have to go too far to see the pattern. When one monopoly supplier sets the rules, applicants get paperwork and eligibility boxes, and the customer service is something less than stellar.

Enter the private market, and AI

The encouraging news is that the private market isn't waiting around. Founders and owners may soon find loans, grants, and investors much more easily, because existing platforms are building AI into nearly every step. They're streamlining applications, gathering different information than banks do, introducing proprietary screening, and speeding up communication.

Hello Alice, a funding platform founded in 2017, uses an "AI advisory board" to match owners with grants, accelerators, and capital they qualify for. It starts with a Business Health Score that weighs industry, revenue, stage, and goals.

Lendio, founded in 2011, now uses "AI-driven matchmaking" to connect businesses with the best deals among its 75 financing partners. Its proprietary model analyzes recent deals to suggest offers that fit a business's profile.

Swoop, launched in 2018, connects businesses with grants, loans, equity, commercial real estate financing, and tax credits. Its website says it uses AI to refine cash flow projections, draft eligibility workflows, and build due diligence checklists.

A match isn't a payday, but it's a start. More important, AI lets platforms and funders look past credit scores and collateral, the two blunt instruments that have always kept otherwise  good risks off the approved list.

Mona, a newer AI-powered platform backed by Sheryl Sandberg's venture fund and Eric Schmidt, built a common application that matches businesses to "best fit" loans, grants, and incentives.

CEO and co-founder Andrew Leon Hanna highlighted the importance of these initiatives while speaking for the Mastercard Center for Inclusive Growth Forum in September. "Small businesses generate two-thirds of net new jobs in the US and are the most inclusive pathway to economic mobility," he said. "Yet about 50 to 60% don't get the capital they need because of outdated underwriting standards that look only at credit scores." Better data, he argued, helps lenders see a track record and evaluate owners who have no credit score at all.

The catch: what AI can't see yet

A recent San Francisco Fed report says AI handles "hard" data like credit scores, financial statements, and formal credit histories far better than "soft" data like borrower relationships and local knowledge. It also warns that because soft information is harder for current tools to process, AI adoption might tilt bank lending away from small and medium-sized enterprises.

That's Hayek's knowledge problem showing up in a new form. The most valuable information in lending, like whether the owner always pays suppliers first or the neighborhood is about to boom, lives in people's heads and relationships.

The good news is that these sorts of markets are competitive. If one lender's model misses this, another can build one that catches it and profit from the difference. Private lenders have to answer for their mistakes with their own money, and that discipline is something no government program has ever replicated.

A view from the field

After years of reporting on solo and micro-business owners, here's what I keep noticing: the people who build the most resilient businesses often possess great ideas and sufficient market knowledge to take a shot. They may have been recently downsized and have no collateral to pledge.

A traditional underwriter sees risk. I see someone with a loyal customer list, tight costs, and no layers of overhead to hide behind. If AI can finally learn to read that story, it'll unlock capital for the very people the old system keeps turning away, and likely will be able to do it without a single new federal program.

The bottom line

Private-market AI won't solve everything overnight. The tools still favor tidy data over the messy, human kind, and it will be a few years before we know how big the impact is. Even so, the direction is encouraging.

Capital is finding entrepreneurs through competition and innovation, not through another form to fill out. When AI can finally weigh the nuances that tell a lender whether an owner will pay back on time, that will be the Holy Grail. It looks more likely to come from the free market than from Washington.