The AI Lift for New Businesses

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The AI Lift for New Businesses

AI is making it easier to start and test out small firms

Jun 10, 2026

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[Insight] AI’s lift for small businesses

Advanced AI tools are making it easier than ever before to launch a new business. Entrepreneurs are quickly adopting AI for capabilities they previously would have struggled to afford without significant venture capital: research, writing, coding, design, customer support, market analysis, product specifications, and basic finance, all of which are among ChatGPT’s most popular capabilities.

The latest US numbers point to a large AI lift. Census data show 5.65 million business applications in 2025, up from just over 5 million in 2022, the year ChatGPT launched. The latest monthly release, for May 2026, recorded over half a million applications, up 17% from May 2025 and on pace for over 6 million new applications in the course of this year. Not all of these applications lead to new businesses, and not all of these businesses will succeed, but the sheer increase in new entrepreneurial activity – which coincides with three full years of ChatGPT, wider AI adoption, and ever-increasing AI capabilities – is worth a closer look.

AI tools appear to be helping sustain a much higher level of experimentation and risk-taking. They lower the cost of trying to start a business: writing a plan, testing a market thesis, building a website, creating a pitch deck, drafting ad copy, answering basic regulatory questions, or prototyping software. For many people, the gap between, “I have an idea” and, “I can test this” has become much, much smaller.

The pattern seems to be true in other countries, too. A recent study of Chinese firm registrations also found that, after ChatGPT’s launch, places with more AI talent saw a sharp rise in new firm creation, driven entirely by small firms. The European Union shows a similar, if less, dramatic rise. Eurostat’s business registration index for the EU rose to 108.6 in 2025 from 100.3 in 2022, suggesting registrations were about 8% higher over the period. This is an index rather than a raw count, so isn’t directly comparable to US business applications, but it points in the same direction: new business formation has increased since ChatGPT’s launch.

These new firms are also starting smaller and staying smaller than before. Stripe data for new “C” corporations shows that so far, in the second quarter of this year, 63% of these new businesses were solo-founded, an all-time high. Stripe found that these solo start-ups were increasingly “AI-native,” with core products that depend on advanced AI models, and that these founders are now much more competitive with larger, better-staffed startups.

All told, this has interesting implications for jobs and how our economy evolves with AI. People increasingly seem willing to take a risk and start something new – potentially leaving a salaried job at a larger company to do so. It’s certainly easier to take this leap than it was just a few years ago.

There also might be fewer early hires per startup or later hiring as firms attempt to scale and succeed. A founder who can use AI for coding, design, support, sales copy, analytics, and operations may not need to build a traditional team as quickly. Europe’s business demography data points in the same direction: the average newly born EU enterprise in 2023 had just 1.06 people employed. So the future of work may involve more tiny firms, more solo founders, and more businesses that begin with one person plus highly capable AI tools.

That doesn’t necessarily mean fewer jobs overall. It means work may show up in different places: specialist contractors, AI implementation experts, customer-success teams, compliance support, infrastructure providers, and later-stage hires once the best companies start to scale. The big question is whether AI mainly helps companies do the same work with fewer people, or whether it creates enough new companies and markets to expand work overall. The optimistic case is that AI widens the startup funnel: more people can try, more ideas can reach customers, and the firms that break through can create new kinds of work around smaller core teams. – Adam Cohen, Head of Economic Policy

[Data] Via Codex: Tracking America’s views on AI

This week, we’re launching a new AI Sentiment Tracker built with an apropos research assistant: Codex.

The assignment was straightforward: apply publicly available polling from Gallup, Ipsos, Pew Research Center, Quinnipiac, NBC News, and other reputable survey firms to create a single directional benchmark for how Americans feel about AI over time.

The challenge is that AI polling is abundant, but often difficult to compare. Many surveys focus on the intersection of AI and issues such as jobs, elections, misinformation, national security, creativity, or education. Those polls are valuable, but don’t necessarily measure broad public sentiment toward AI itself.

Using Codex, we reviewed hundreds of public polling questions and narrowed the dataset to surveys that asked respondents – all gen pop – to choose between paired positive and negative views of AI: benefits versus risks, good versus harm, favorable versus unfavorable, optimistic versus pessimistic, trust versus distrust, or excitement versus concern. We excluded issue-specific questions that could distort the broader picture and documented cases where topline results came from reputable polling roundups rather than standalone poll releases.

The result is intentionally modest. Each point represents a published poll result. The trendlines are a smoothed benchmark based on the available paired-response questions over time. This is not a polling average, nor does it imply that every survey asked the same question. Instead, it provides a directional view of how public attitudes toward AI have evolved across multiple high-quality surveys.

We’ll continue updating the tracker as new polling becomes available, and we’re grateful to the pollsters, researchers, and the Roper Center for Public Opinion Research, all of whose work makes projects like this possible.

[Insight] The power of utility

So contrary to what we might expect, sentiment about AI itself seems to have improved over the past year. Granted, AI is a foundational technology that will touch or impact much of our economy and society, and considering it distinct from those kinds of impacts – AI and jobs, AI and kids, etc. – comes with caveats. But the obvious explanation for the apparent improvement is that more people are using AI and finding use cases for it.

Which is noteworthy, especially given how AI, unlike recent new technologies, probably started off underwater. People are considering AI with years of cultural conditioning – literature, movies, television, video games – that has primed them to expect more harm than benefit. This pull from the Roper Center archive, a Cambridge Reports survey from 1987, shows that nearly 40 years ago, Americans were 19 points more inclined to say that AI would likely do more harm than good.

For context, Brett M. Powell, Roper’s Associate Director, offered a point of comparison between interest in public attitudes about AI and drones: “If, for example, you look at drones, you can see that in the early 2000s Roper Center archived five questions on the subject. Then, in the 2010s, we recorded 155 questions, and in the 2020s, we’re back down to seven questions (albeit we are just over halfway through the decade).” Drones are popular, he said, and society has learned how to live with them.

Whereas Roper’s archive includes four questions on AI in the 1980s-1990s, 32 in the 2010s, and 630 so far in the 2020s.

[Event] ChatGPT for midterms coverage

Tomorrow, June 11, we’re hosting a small OpenAI News Academy at our DC Workshop that’s focused specifically on election coverage.

The session is designed to help political and campaign reporters, editors, and producers get beyond the basics of ChatGPT and Codex to learn practical ways these tools can support the work they already do.

The instruction covers source-first workflows, research and reporting use cases, prompting techniques, and ways to turn dense documents and polling into structured briefs, first draft interview questions, and reusable newsroom tools.

Here’s one of those newsroom tools we’ll be demonstrating: an AI-created app helping you find the exact politician quote you’re looking for.

[About] OpenAI Forum

Explore Forum programming by and for our community of approximately 75,000 AI experts and enthusiasts from across tech, science, medicine, education, government, and other fields.

11:00 AM – 1:30 PM EST on Jun 15

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