Does that include the use of AI to originate VC investments?
“Some VCs have exceptional quantitative capabilities that they use to identify potential investments. Of course, that is often helped by the digital footprints tech-centric companies tend to leave.”
Joshua Lowe
““It can be hard to quantify just how widespread the use of AI is in VC. A 2018 survey by PitchBook indicated that around 22% of VC firms were incorporating machine learning in their investment decision-making. But my research, which takes the hiring of data scientists and engineers into account, suggests the adoption of data technologies in VC is hovering at around 4% to 5%, with a more pronounced adoption among early-stage investors. Looking ahead, however, projections from Gartner suggest that by 2025, more than 75% of VC investor reviews will be informed using AI and data analytics.”
Maxime Bonelli
“There has always been a spectrum in the VC world, with some firms more focused on number-crunching and others openly relying almost entirely on gut feeling.”
Léa Stern
“I am surprised to hear that the use of AI is more prevalent for deal origination among early-stage venture capitalists. I know some firms are using AI to support origination, but they tend to have a later-stage strategy. These things are only worth doing where sufficient data is available, and in private markets that data is tightly held. Certainly, the companies we go after have no data. There are no revenues or costs. It is just a group of people and an idea.
“I am also aware of growth investors attempting to harness public data to help prioritise which deals to go after, but the quality of the available data is questionable. One of the problems with AI, as with all computing, is the old maxim of garbage in, garbage out. If you don’t have a clean set of data to begin within, I am not sure how helpful AI can be.”
Anne Glover