Startups working with artificial intelligence and looking for a home while they work through accelerators or incubators likely are headed to California—but many other states not only have strong levels of activity but may feature better market fits for certain entrepreneurs. For example, over the past five years Minnesota has nearly matched California’s rate of follow-on investment, Oregon has achieved one of the highest rates of M&A exits, and Tennessee has realized one of the fastest rates of total exits.
California and other leaders
The Golden State is a prime location for startups working with AI and at the accelerator/incubator stage (hereafter just “accelerator stage”) of development.
From 2021-2025, California had 2,973 companies participate in an accelerator or incubator, leading all states (and with 36% of the U.S. total). This mass is not only a product of the state’s overall position in startup activity—the state’s accelerator-stage companies over this period were 40% more likely to be working with AI than the national average.
Among all California-based AI companies at this stage, 3% have already had a merger, acquisition, or gone public (because only four of the 8,189 companies from this cohort have gone public at this point, these are referred to as “M&A exits” only). The state has seen 6% of the companies go out of business, and, over the same 2021-2025 period, experienced 1.04 investment deals (angel, seed, or venture capital).
New York’s AI accelerator-stage performance is excellent. The state ranks second in total companies at this stage (with 13% of the U.S. total) and has rates of positive exits and follow-on investment that are above the U.S. average. (New Jersey, with 104 AI companies at this stage, may be hoping to leverage some of its neighbor’s success by launching a $20 million fund in partnership with CoreWeave.)
Delaware also rates strongly on many of these metrics: it is 3rd among all states for companies at the accelerator stage, is 50% more concentrated than average in companies working with AI, and has a comparable rate of positive exits to California. However, it is unclear how many of these companies are operating in Delaware or are simply incorporated there.
Other strong markets
Massachusetts (422 accelerator-stage companies in AI) and Texas (419) have similarly-sized total activity, but with lower levels of concentration than in California or New York. Nearly 7% of Texas companies at this stage have already had a positive exit, nearly doubling the rate in Massachusetts. However, startups in Massachusetts see stronger rates of follow-on capital, with 1.15 investments (compared to 1.02 in Texas).
Massachusetts continues to offer one of the most thorough slates of startup support initiatives in the country, including MassTech’s recent AI Hub.
Florida (305) and Washington (246) are on the next tier of states by raw activity. Florida’s AI accelerator-stage cohort of its overall market (27%), and these companies have had a lower rate of total exits than the U.S. average (8% vs. 10%) and have a lower rate of follow-on investment (0.88 deals vs. 0.97). Washington, on the other hand, is relatively concentrated in AI (36% of its companies at this stage) and is seeing high rates of positive exits (6% in Washington vs. 3% in the U.S.) and better than average total exits (13%) and follow-on investment (1.03).
States with specific advantages
Minnesota is 4th for rate of follow-on investment among all states with at least 50 AI startups that participated in an accelerator or incubator from 2021-2025. This places the state behind only Massachusetts, New York, and California (and on-par with Washington), with a rate of 1.03 investments per company. The Gopher State boasts a sizeable level of startup resources, including accelerators, particularly relative to its overall volume of activity. Minnesota’s pace of positive exits (3%) also in on-par with the national average, while its rate of companies going out of business also is higher (10% vs. 7%). These high rates come from a much lower base of activity, of course, and the state had 58 of these companies during the period.
For entrepreneurs seeking quick action, Tennessee may be the best bet. Among all of its companies in AI that participated in an accelerator or incubator in just the past five years, 20% have already exited (6% positively and 14% closing shop). While entrepreneurs would rather exit with a positive financial return, a quick decision to fold facilitates capitalizing on new opportunities (or, at least, not wasting time and resources). Tennessee’s 51 companies at the accelerator stage also have attracted an average of 0.98 follow-on investments, sitting just above the national average.
Oregon has a similarly-sized market (57 companies) but that seems particularly geared toward M&A activity.
Oregon’s rate of exits through mergers and acquisitions nearly triples the national average (9% vs. 3%), the best among all states with at least 50 such companies.
Relatively few companies are closing shop for other reasons. Oregon has an out of business rate below 4%, which is good if these companies are viable but may mean too many companies are holding on to unrealistic expectations. More clearly, follow-on capital is not a strong suit in Oregon, with just 0.86 investment deals for each company. Notably, Oregon created an AI accelerator last year as a partnership among regional groups, universities, trade associations, among others.
Understanding regional startup markets
These indicators of recent performance raise important question for state and local economic development leaders: Is your region capturing its fair share of AI startup activity? Are your accelerator programs providing sufficient support to advance startups toward additional investment and successful exits?
If you are interested in exploring the competitive landscape for your region—relative to the AI market or another sector—I welcome the conversation. Understanding a region’s activity and support structure is a critical step toward driving the outcomes that matter to the local economy, to entrepreneurs, and to investors.
Data notes
The data in this article was pulled from PitchBook on February 16, 2026. Companies working in artificial intelligence are defined by the platform’s industry vertical tag: this means that the startup may primarily operate in a sector outside of IT (e.g., healthcare) but contributions to, or use of, AI is a significant element of the company’s work. See PitchBook’s explanation for details.