Examining the geographic concentration of VC investment in AI

The dominance of artificial intelligence (AI) investments in venture capital (VC) has been a consistent storyline in the first half of 2025. PitchBook, Carta, Crunchbase, and many others have all pointed to the significant portion of investment dollars and deals flowing to AI companies. With the volume of companies, deals, and dollars involved, it is more than a spike in the usual cyclic nature of  VC investment.  

As SSTI wrote in our review of Q1 venture capital investment activity, VC has been concentrating in larger deals. With market trends and mega deals in AI so well documented, we explore investment concentration from  deal size and geographic perspectives. As with prior analyses, we focus on deal sizes more relevant to TBED initiatives to help regional innovation leaders identify where they might find opportunities, face challenges, or set priorities in such a dynamic environment. Excluding the largest deals from our analysis appears to be increasing important, considering  PitchBook’s findings that just ten companies accounted for 41% of all venture dollars so far this year.  

SSTI used PitchBook data to examine VC investment activity for transactions under $100 million in the first half of 2025. AI deals were identified using Pitchbook’s AI and machine learning vertical.  

In reviewing investment deal count (Figure 1) and dollar totals (Figure 2) for deals under $100 million across all industries, there were over 5,400 venture capital deals totaling $54.6 billion in the first half of 2025. There were 1,959 AI deals totaling nearly $21 billion.
 

Figure 1: Count of U.S. deals less than $100M across all industries and in AI for the first half of 2025.

Figure 2:  Total dollars invested in deals less than $100M across all industries and in AI for the first half of 2025. 

From a distribution standpoint, AI deals made up 36% of all VC deals and almost 40% of investment dollars under $100 million (Figure 3).             

Figure 3: Distribution of VC investment activity in U.S. for deals less than $100M across all industries and in AI for the first half of 2025. 

Figure 4 shows the relative distribution of investment activity for all deals and for AI deals. What we find is that the pattern for investments is similar for AI and all deals. Both the AI subset and total VC investment pool  show the highest portion of deals in the $1-5 million range and aggregate dollars increase to similar levels with round size. Figure 5 shows the percentage of AI deals and dollars across the investment size spectrum. Investment in AI is consistently 35%-40% of all activity other than reduced presence in the $0-$500,000 size range where AI investment activity drops to approximately 25% of the total. While the stories referenced above point to extraordinarily large investments in AI, when limited to deals less than $100 million, the distribution of AI investment activity follows that of the market as a whole.

Figure 4: Distribution of investment activity within deal size ranges for total VC market and AI market vertical.  

Figure 5: Percentage of AI investment activity in total VC market across deal size ranges. 

Next, we examined the share of AI investment activity within each state. Most states have notable representation of AI investment activity. Figure 6 shows the distribution of AI venture capital investments and companies by state. The trend line reflects national numbers, states below the line are weighted toward the proportion of AI companies, and those above the line are weighted toward the proportion of capital invested in AI companies. The size of the circle represents the total number of companies securing VC capital. 

Figure 6. Proportion of VC investment activity <$100M within states going to AI companies. 

One obvious finding is that California investments heavily influence the national investment picture. California’s total investment was 1,648 deals totaling $20.9 billion, with 822 AI deals totaling nearly $10 billion. California’s investment totals translate to 30% of all U.S. VC deals and nearly 40% of all dollars under $100 million. California also leads states in the share of AI investments, with 42% of all U.S. AI deals and 47% of AI dollars going to California companies. Nearly 50% of California deals and over 47% of dollars went to AI companies. California investment in AI is over 15% of all U.S. VC deals and nearly 19% of all U.S. dollars went to California AI companies. 

Even with California’s dominance of overall investment activity, we see strong representation of investment in AI across the country. Washington, well known for its tech industry, shows significant emphasis on investment in AI with 44% of companies and 51% of capital going to the sector. Utah also shows heavy AI investment with 59% of capital going to 29% of the companies. Midwestern and Great Lakes states show somewhat lower, yet still significant, shares of AI investment activity, perhaps due to economic bases rooted in physical technologies and manufacturing. States with significantly higher or lower shares of AI investment seem to be influenced by smaller numbers of deals where one significant investment can dramatically change the outcomes. Overall, the data shows that while the overall volume of activity continues to be concentrated in a few states (and metros), the vast majority of states are seeing significant investment in AI companies.    

From a policy perspective, the data showing widespread investments in AI companies could lead TBED organizations in a few different directions. For states with limited investment in AI companies, TBED practitioners may want to understand if the limitation is related to the number of companies seeking capital, the interest of local investors in AI, or a combination of these and other factors.  

Is a selection bias creeping into TBED and private portfolio selection because of AI saturation of relevant media?  For states that are seeing significant shifts toward AI investment, considering the finance gaps companies in more traditional technologies and markets may be facingf could be a beneficial exercise. Even with differences in state and local markets, a common thread seems to be that the nascent opportunity of AI is widespread and consistent with broader market behavior for all but the largest deals. Looking forward, TBED organizations need to investment in AI as the new norm and understand how their strategies and resources are prepared to operate in this new market.  

This page was prepared by SSTI using Federal funds under award ED22HDQ3070129 from the Economic Development Administration, U.S. Department of Commerce. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the views of the Economic Development Administration or the U.S. Department of Commerce.