Originally posted on N2 Technology on the 14 March, 2021
By 2025, more than 75% of venture capital firms' investment decisions will be informed using artificial intelligence, says Gartner. Data science and analytics will inevitably be prioritised over decision making traditionally based on “gut feelings.” This means that artificial intelligence might be determining whether a company makes it to a human evaluation at all. This essentially devalues the importance of pitch decks and financials.
And surely that’s a good thing, right? Based on our last report, only 0.66% of startups have a chance of actually receiving any funding - the rest are either being found too late or going completely unnoticed. So what if AI could shift the heavy reliance on personal networks, augment the gut instinct of a successful investor, and avoid the incorrect filtering out of hidden gems that get lost in the massive volume of applications? Ultimately, AI has the capability to place greater precedence on a potential companies’ offerings, and allow perfectly matched investors and startups more likelihood of finding each other.
Successful investors purport to possess a good “gut feeling” when it comes to making sound financial decisions. However, these “feelings” are based mostly on qualitative information infused with quantitative data provided by the technology company, says Gartner’s senior research director, Patrick Stakenas. He believes investment decisions will move towards a more “modern platform-based quantitative process” that includes information gathered from multiple sources. LinkedIn, PitchBook, Crunchbase, and Owler, along with third-party data marketplaces can then be leveraged alongside diverse past and current investments.
Therefore, Stakenas suggests that technology service providers who are seeking investment should build an accurate digital presence. This can be done by updating and correcting quantitative metrics on social media and business sites to ensure that the company's information and financials are correct. He explained that “personality traits and work patterns required for success will be quantified in the same manner as the product and its use in the market, market size, and financial details are currently measured. 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.”
But this is nothing new - data like this is already being used to build more sophisticated models that better determine investment viability, and let’s face it; AI has long been providing insights into customer desires and predicting their behaviour in marketing and sales. They've been monetising from data for years, so what’s stopping the same utilisation of AI in the investment process?
Read more: The Big AI Con: Are You Really AI?
Some VCs are already using proprietary platforms to track the performance of millions of companies. For a small cost of over $10 million per year, the Beacon platform draws data from 10 million sources, including academic publications, patent registries, open-source contributions, regulatory filings, company web pages, sales data, social networks, and even raw credit card data. This intel can then flag outperforming companies on an investors’ dashboard, allowing them to see deals ostensibly earlier than traditional venture firms.
This isn’t to say that AI is - or will be - the be-all and end-all. After all, algorithms - like humans - are not immune to biases. Perhaps the way forward is a hybrid-approach, or AI-informed human decisions? This might be a way to ensure fairness and efficiency. Regardless, there’s no escaping the fact that it’s about time we leaned into tech and embraced the opportunities it can afford both investors and startups!