Canny investors and their financial advisors will do the necessary research before committing to an investment decision, but there are times when “gut feel” is the driving force.
Sometimes, you just seem to know that it’s the right choice – even when it turns out not to be!
But for technology investors, who have been among the big winners in the past year, they will rely less on their human instincts and more on technology itself.
Artificial intelligence along with data science will be increasingly important for tech investors’ decisions in the years ahead according to new research from Gartner.
It forecasts that, by 2025, three quarters of tech investment decisions made by venture capital and early-stage executive reviews will be informed by AI and data science.
“Successful investors are purported to have a good “gut feel” — the ability to make sound financial decisions from mostly qualitative information alongside the quantitative data provided by the technology company,” said Patrick Stakenas, senior research director at Gartner. “However, this “impossible to quantify inner voice” grown from personal experience is decreasingly playing a role in investment decision making.”
This shift from the traditional pitch experience will demand that tech CEOs face investors with AI-enabled models and simulations as traditional pitch decks and financials will be insufficient.
Using the tech
The use of data science will draw on information gathered from sources such as LinkedIn, PitchBook, Crunchbase and Owler, along with third-party data marketplaces, which can be leveraged alongside diverse past and current investments.
“This data is increasingly being used to build sophisticated models that can better determine the viability, strategy and potential outcome of an investment in a short amount of time. Questions such as when to invest, where to invest and how much to invest are becoming almost automated,” said Stakenas.
Meanwhile, the part that AI will play includes the already-available analysis and prediction of consumer desires and future behaviour.
The ability of AI’s natural language processing technology will also be used to determine whether firms are likely to be a good bet.
“The personality traits and work patterns required for success will be quantified in the same manner that the product and its use in the market, market size and financial details are currently measured,” said Stakenas. “AI tools will be used to determine how likely a leadership team is to succeed based on employment history, field expertise and previous business success.”
This article originally appeared on WP.
