The Series A — traditionally a startup’s first significant institutional round, often measured in the single-digit or low double-digit millions of dollars — is being redefined.
So far in 2026, global startups have secured at least 114 Series A rounds of $100 million or more, according to Crunchbase data published on Wednesday, September 23. That is the highest annual total in years and puts 2026 on track to surpass the all-time peak for such deals.
Many of those rounds far exceed the $100 million threshold. Collectively, this group of Series A recipients has raised around $33 billion this year, with at least 12 rounds valued at $500 million or more, Crunchbase reported.
An AI phenomenon
The surge is overwhelmingly driven by artificial intelligence. More than 70% of Series A rounds of $100 million or more have gone to AI-focused startups, according to Crunchbase.
The list includes some of the year’s largest early-stage financings. Silicon Valley-based River AI, a platform that allows developers to train and serve custom models, raised $1.2 billion, while China-based Xpeng Robotics, a developer of AI-enabled humanoid robots, raised $900 million, Crunchbase noted.
Those figures would have been unthinkable for a first institutional round only a few years ago. They reflect how AI has changed the economics of company-building: training and serving models requires large investments in computing power, specialised talent and data, and investors are willing to fund those costs early for teams they believe can lead new categories.
Part of a broader AI boom
The concentration at Series A mirrors trends across the venture market. In the first half of 2026, venture and growth funding to AI startups totalled an estimated $394 billion, roughly 77% of all investment capital, according to Crunchbase. Most of that went to later-stage companies, but the Series A data suggest that early-stage investment looks similar in its heavy tilt towards AI.
The broader market has been dominated by extraordinary deals. Crunchbase has reported record global startup investment of $510 billion in the first half of 2026, driven in part by massive rounds for frontier AI labs.
The US leads — but less dominantly
Roughly half of this year’s $100 million-plus Series A rounds and funding went to US-based startups, according to Crunchbase. That amounts to about 62 deals worth around $15 billion so far in 2026, putting the US on track for a record tally.
Notably, megaround funding at Series A is more globally dispersed than overall venture investment. In the first half of 2026, more than three-quarters of global seed-through-growth-stage financing went to American companies, largely because of megarounds for San Francisco-based Anthropic and OpenAI, Crunchbase noted. At Series A, by contrast, companies outside the US — including in China and Europe — are capturing a larger share of the largest rounds.
Why investors are writing bigger early cheques
Crunchbase pointed to several factors behind the rise in Series A megarounds beyond AI growth alone.
First, leading startup investors have exceptionally large capital reserves to deploy. Funds raised in recent years need to be invested, and large cheques allow firms to put significant amounts to work in a single company.
Second, exit multiples — historically, and to an even greater extent recently — reward those who are anything but modest in their ambitions. If a small number of companies generate the vast majority of returns, investors have an incentive to concentrate capital in those they believe can become category leaders.
Third, investors seem to agree more than usual on the sectors, business models and founding teams they want to back, according to Crunchbase. As a result, capital is converging on perceived early leaders. As Crunchbase put it, a pricey share of a winner still beats a discounted share of a laggard.
The shift also changes how founders approach fundraising. A startup that can credibly claim leadership in a fast-growing AI category may be able to skip traditional seed-stage milestones and raise hundreds of millions of dollars at the outset, while companies without that perception may find early capital harder to secure.
That dynamic can create a self-reinforcing cycle. Well-funded companies can hire the best talent, buy more computing power and move faster, strengthening their lead — and making them even more attractive to investors in subsequent rounds.
The risks of early megarounds
The trend carries risks. Large early rounds typically come with high valuations, which set demanding expectations for future growth. If a company fails to meet those expectations, it may struggle to raise its next round at a higher valuation, potentially leading to down rounds or difficult restructurings.
Concentration can also crowd out competition. When investors pour capital into a few perceived leaders, promising companies with different approaches may find it harder to raise money, reducing diversity in the startup ecosystem.
And the dependence on AI creates sector-specific risk. If returns from AI investments disappoint, or if technological shifts erode the advantages of early leaders, the capital committed in these rounds could prove difficult to recover.
Implications for India
India has produced a growing number of AI startups, but megarounds at Series A remain rare in the Indian ecosystem. Indian startups raised about $17 billion across roughly 1,520 equity rounds in 2026 through September, according to Tracxn — a healthy total, but one spread across many smaller rounds.
The global trend nonetheless matters for Indian founders. Investors increasingly compare opportunities across borders, and Indian AI startups competing for global capital must show that they can build category-leading businesses. For Indian-origin founders building in the US and elsewhere, the environment offers access to unprecedented early-stage capital — along with the pressure that comes with it.
The bottom line
The rise of the $100 million Series A is one of the clearest signs of how artificial intelligence has reshaped venture capital. Whether these large early bets produce the outsized returns investors expect will become clear only over several years. For now, the message from the market is unambiguous: for startups seen as potential AI leaders, capital is abundant from the very first institutional round.
