The amount of funding dedicated to early stage technology has ballooned over the last two decades. While statistics of the funding volume flowing into startups are being published on a regular basis very few data is being released on the number of individual firms behind that funding. In this post we use Crunchbase's database to deep dive into the number of Venture Capital and Private equity firms operating in the market and we analyze how this number has grown over the last two decades.
The tech industry is experiencing significant disruptions, with the rise of AI agents at the forefront of this transformation. With widespread layoffs and automation altering the landscape of traditional white-collar jobs, Software as a Service (SaaS) companies must adapt their pricing models to the new paradigm. AI agents will take over many tasks that white-collar workers perform today. However, to do this effectively, they will need access to the same systems and repositories as humans. For example, AI-powered SDRs should have access to CRM systems to perform effectively. Similarly, AI-powered developers will need access to code repositories, development environments, ticketing systems, and more.
There were $13.1 trillion in Assets Under Management in the Alternative Assets Industry as of June 30, 2023. The AUM has grown nearly 20 percent per annum since 2018. Institutional investors spend approximately $13 billion per annum on technology (0.1% of their AUM or 5% of their budget). The same firms dedicate $170 billion per annum to personnel costs (1.3% of their AUM or 65% of their budget). The TAM of AI is somewhere between the total spending in technology (lower bound) and the total spending in salaries (upper bound).
Today we are launching our first AI Agent in closed beta. Our first AI Agent is specialized in due diligence tasks. In its current version the Agent searches for all available data of a given company in the web and also queries private databases via our partnerships with data providers. Using RAG for LLMs it then answers the most relevant due diligence questions within seconds that a research analyst would usually work on for days: Who are the competitors? How big is the market? What is the product USP? How much have they raised and who are the investors? Etc etc
AI systems for asset management in general and, in particular, for private equity, venture capital or private credit are not considered high-risk applications in the final version of the AI Act. Limited risk AI systems only have to make sure that users are informed when they are interacting with AI. As an example, an AI Agent that would interact with founders in a Q&A session, should inform the founders that they are dealing with AI. For systems used internally, the employees must know that they interact with an AI application but that is usually the case. In some cases such applications could be deemed as high-risk if a large asset manager deploys AI solutions that affect consumer’s access to basic needs such as housing, telecommunications or credit.
We are thrilled to announce the launch of CarriedAI, The Home of AI for Institutional Investors. At CarriedAI we believe that AI will fundamentally change how capital allocation decisions are made. In a few years' time, we will be surrounded by AI systems that either make allocation decisions autonomously or give humans superpowers to do it. Our mission is to build the Operating System for engines that are capable of making such capital allocation decisions governed by AI.