Gartner research shows the effectiveness of AI for the venture capital investor
Venture capital investments are provided for the long term to young companies in the early stages of development. The decision about which startup to invest in is most often made by businessmen based on a thorough analysis of the market, the product’s prospects, and a number of other factors. However, modern technology has all the potential to help investors diversify their portfolios profitably.
Gartner research predicts that by 2025, venture capitalists will outsource most of their tasks to artificial intelligence. About 75 percent of decisions will be made with the help of AI, so the role of product presentations and assessment of the financial condition of companies will go into the background. New technologies will allow the venture capital sector to move away from the intuitive component to a more analytical one. Businessmen will be able to use complex platform solutions based on the collection and processing of quantitative data. Information for this is gathered from a variety of sources, including Crunchbase, LinkedIn, Owler and others. These data sets are used to develop comprehensive models that demonstrate a project’s viability and prospects. They also define a startup’s strategy and its effectiveness to achieve results in a short period of time. With such innovative systems, investment decisions can be applied in a short period of time and almost automatically.
And AI technology makes it possible to assess the key qualities that are necessary for success in each case. This parameter is just as important as analyzing the size of the market or the financial capabilities of a startup.
AI solutions know how to create unique profiles, and human intervention in this process is almost minimal. So far, this technology is used for marketing purposes, but it has every chance of becoming a useful tool for venture capital investors.
Signalfire already uses innovative IT solutions in its work. It created its own platform Beacon, which tracks the results of 6 million startups from different market sectors. It gathers information from 10 million sources, including academic publications and licensing and patent registries. Companies that have potential are flagged on a special dashboard, so deals and news about them are tracked first.
Of course, introducing artificial intelligence and machine learning technologies into venture investing processes does not mean that traditional approaches will have to be abandoned. Innovative solutions will be a great help for specialists, but they cannot replace them. Experience and emotion are just as important as mathematical calculations, so the best option would be a hybrid model that combines AI analysis with the analysis that investors are currently applying.
