Even as artificial intelligence pioneers such as former Google AI guru Geoffrey Hinton and OpenAI chief executive Sam Altman sound alarms about the potential for AI tools to run amok and the need for regulation, the technology has reinvigorated the venture capital market, discarding a gloomy outlook for one of new possibilities.
AI is not only serving as the foundation of new products and services being developed by emerging founders with ambitious plans to disrupt future work processes across industries. It is already transforming how venture fund managers themselves source deals, underwrite investments and track talent moves. AI is also freeing VC firm employees from repetitive tasks to pursue more creative thinking.
In the following stories, we delve into the three major areas where venture firms are applying AI now: deal sourcing, operations and due diligence.
Based on our conversations with various venture capitalists and queries to ChatGPT, we expect to see even more processes being handed off to AI or bolstered by it. When queried about how VCs are using the technology, ChatGPT replied: “Venture capital firms could use AI-powered chatbots to communicate with their limited partners (investors) and provide regular updates on fund performance, investment strategies and other relevant information.”
How soon before AI will be applied widely to venture workflows? “In the next 18-24 months, you’re going to see something that probably is pretty impactful and starts to get some traction, beyond raising a lot of money, beyond some easier venture metrics,” predicts Jeff Grabow, US venture capital leader at EY.
“EY believes there is a huge opportunity for enterprises to reimagine the way they leverage technology end-to-end, with generative AI at the center of that. We are spending a lot of energy on how we think about how we help our clients through that journey.”
AI primer and glossary
Artificial intelligence is computer software that imitates human cognition to perform complex tasks such as decision-making and data analysis that only humans were capable of previously
Programmed to execute tasks requiring human reasoning, AI systems can learn from their interactions to continuously improve their performance and efficiency. Where traditional AI models are mainly used to analyze data and predict outcomes, generative AI takes that up a notch by creating new content resembling data it is trained on.
Machine learning is a subset of a lesser form of AI, dubbed narrow AI, which mimics intelligence by relying on programmed responses to perform specific tasks. Unlike general AI, it is not meant to think on its own. The aim of machine learning today is twofold: to classify data based on models that have been built and to predict future outcomes based on these models.
Supervised machine learning algorithms use labeled datasets and start with an understanding of how data is classified, while unsupervised models discern patterns and characteristics from unlabeled data without instructions or categorization. Reinforcement learning, a third subset, learns by trial and error and with feedback from data analysis instead of being trained on a lone dataset. The most advanced type of machine learning is deep learning, which is built on very complex neural networks that simulate how the human brain works. Deep learning, together with computer vision, allows a driverless car to recognize someone crossing the road.
No one has yet produced a detailed study about how venture capital firms are using AI. Broadly speaking, corporations are rapidly adopting it.
Consulting firm McKinsey & Co surveyed nearly 1,700 companies worldwide this year and found that 55 percent have already adopted AI for one or more functions, such as operations, HR or product development. The survey also found about one-third of respondents are specifically using generative AI for at least one business function.
“Amid recent advances, AI has risen from a topic relegated to tech employees to a focus of company leaders: nearly one-quarter of surveyed C-suite executives say they are personally using gen AI tools for work, and more than one-quarter of respondents from companies using AI say gen AI is already on their boards’ agendas,” McKinsey’s 2023 AI report states. “What’s more, 40 percent of respondents say their organizations will increase their investment in AI overall because of advances in gen AI.”