The upward trajectory is reinforced by significant recent developments such as Databricks poised to secure $10 billion in funding¹ – one of the largest venture rounds in history that will help drive creation of innovative AI offerings.
That trend is primarily driven by significant funding rounds by LLM developers such as Mistral AI alongside AI companies like Waymo and xAI. Notable transactions include OpenAI’s $6.6 billion funding round in October², Glean’s $260 million round in September³, Moonshot AI’s $300 million round in August⁴, Waymo’s $5 billion round in July⁵, Mistral AI’s $651 million round in June⁶ and xAI’s $5 billion round in May⁷. Among the more prominent late-stage rounds were cloud computing platform developer Lambda, who raised $800 million in August⁸, valuing the company at $1.5 billion. Scale AI too raised $1 billion in a late-stage VC round⁹.
A significant trend in the market during the year has been the degree to which hyperscalers and tech giants are increasingly partnering with leading LLM startups.
US leads the way
The US continues to lead the way both in terms of deal count and deal value in the GenAI space and accounts for nearly 70% of the deal count and 85% of value. VC activity there has been bolstered by US tech companies and hyperscalers who have been investing heavily in the space. Europe (EMEA) is a distant second.
APAC and Oceania have seen quite rapid growth in GenAI deal value, albeit from a lower base, with the 2023 total of $1.1 billion more than doubling to $2.7 billion by November 2024.
Key drivers of VC investment in GenAI
The key factors driving VC investment growth in GenAI include advancements in AI core technologies, natural language interfaces, and specialised applications. At a more basic level the high adoption rates of AI / GenAI by organisations and the falling cost of training models have been other contributory factors.
The increased targeting of specific industries by vertical AI companies has also fed into the market. In the fintech sector, for example, AI is being leveraged for fraud detection, compliance automation, and operational excellence while in digital commerce it is being used for customer support, conversational commerce, and AI-core services. AI is already reshaping how value can be created.
A significant feature of the market during 2024 has been an apparent change in strategy on the part of VCs. During the first eleven months of the year, the average deal size for GenAI companies in late-stage VC rounds has seen a significant surge increasing from $48 million in 2023 to $327 million in 2024. By contrast, the average deal size for early-stage and angel/seed remained relatively stable.
While the total deal value remains high by historic standards, the data suggests that investors are increasingly focusing on comparatively lower risk, more established companies while startups focused on narrower application-level solutions are encountering a more difficult environment for securing funding and achieving commercial success. It is also likely that the dominance of the big tech players in the GenAI space is having a deterrent effect on VC investment in startups which aim to compete in that area.
Rapid expansion of GenAI pure play companies
The key driver for increased VC investment in the GenAI space is likely to be the continued development of new platforms and innovations, particularly those targeted at specific industries. For example, in the biopharma sector an AI-driven drug discovery platform attracted substantial interest and a remarkable $1 billion Series A funding round earlier this year.
In addition, unicorns such as Hugging Face are providing access to tools and natural language processing (NLP) models which the biopharma industry can use to analyse scientific literature and clinical trial data which may make the entire trial process more efficient and data driven.
In another area, Inflection AI’s conversational models can streamline communication with customers while its sentiment analysis functionality provides insights into public perception of products, which can be of high value for marketing. Similarly, Anthropic’s capabilities of integration of human feedback into development and deployment of systems can be extremely useful for e-commerce.
Harvey AI can be a game-changer for legal research and compliance. It can assist in drafting legal documents, conducting in-depth research on legal matters, and keeping users up to date with the ever-evolving regulatory landscape, which is crucial for avoiding legal pitfalls.