345 VC Funds Worldwide Are Betting on AI, Data Driven VC Report Finds

Venture capital funds are increasingly treating artificial intelligence not as a side tool for analysts but as part of their core investment infrastructure. The latest Data Driven VC Landscape 2026 report, compiled by Andre Retterath, a partner at Munich-based Earlybird Venture Capital, counted 345 so-called Data Driven VCs worldwide, funds that build or actively use in-house AI and automation tools for their investment work.

What the report shows

The number of funds describing themselves as data driven has grown for three years running in the report, and in 2026 it more than doubled the 2023 level. The author splits them into two groups: Workflow Builders, smaller teams relying on off-the-shelf tools and no-code platforms, who make up 42 percent of those surveyed, and Fullstack Builders with their own engineering teams building solutions from scratch, who account for the remaining 58 percent.

Fullstack funds are also statistically larger: the median holds $800 million in assets under management, 23 employees, and two engineers. Workflow Builders typically manage $151 million, employ seven people, and most often have no dedicated engineer on staff, relying instead on outside tools.

From assistance to autonomy

The report points to a clear shift in how funds describe AI's role in their work. In 2024, 86 percent of funds described their approach as Augmented, meaning AI-assisted, and 14 percent as Quant, based on quantitative models. By 2026 the split looks different: 61 percent still describe their approach as Augmented, but 39 percent have moved into the Agentic category, where AI runs investment processes and a human merely oversees the outcome. The Quant category as a separate label has effectively disappeared, absorbed into the agentic approach.

The report's author sums up the shift succinctly, noting that industry discussion has moved on from whether to adopt AI at all to where to invest resources to gain a real competitive edge.

AI in venture capital has moved from a concept to a distinct category - Andre Retterath, Earlybird Venture Capital

Hiring and budgets

The shift is also visible in hiring plans. Nearly half of the funds surveyed, 49 percent, intend to hire at least one engineer within the coming year. By comparison, only 2 percent plan to add junior investment analysts to their teams, while as many as 45 percent intend to cut such positions. The report also points to a budget shift: the ratio of spending between engineers and data and tools moved from roughly 2 to 1 in favor of engineers in 2025 to about 1 to 1 in 2026.

Resources remain the biggest obstacle to AI adoption: 49 percent of funds cite time and staffing constraints, and 41 percent cite the quality of available data. Even so, 57 percent of firms say they are currently scaling up their use of in-house tools, up from 37 percent a year earlier.

Where AI is actually working

The report rates AI adoption levels across individual fund functions on a scale of 1 to 5. Sourcing new companies for investment and due diligence, the vetting of startups before a capital commitment, score highest at 3.4 points each. Close behind is in-house engineering work at funds, with a score of 3.3. The legal and compliance area scores lowest, at just 1.8, suggesting funds remain reluctant to hand AI decisions carrying regulatory risk.

On perceptions of the trend itself, 72 percent of respondents place the current phase of AI in venture capital before the bottom of the so-called trough of disillusionment on the hype cycle curve, up from 55 percent a year earlier. Fewer than a third believe the industry has reached a stage of mature technology use, and none of those surveyed rated the market as having reached full productivity.

Relevance for Poland

The report does not name Polish funds directly, but the trend matters on the Vistula too. Polish VC funds, like the rest of the European market, compete for access to the best deals with global players using automated sourcing and due diligence. The growing pressure to hire engineers instead of junior analysts is a signal that may also reach local investment teams looking for ways to stay competitive with a smaller capital base.

Data on Claude's dominance among tools used by investment funds confirms a broader trend seen in other corporate surveys, in which Anthropic's model is gaining ground on ChatGPT in analytical and research use cases, even though ChatGPT still holds a larger user base in consumer applications.