How AI will affect jobs in the Investment Fund sector
Where we have seen the most enthusiasm recently for the use of AI in venture capital is in the secondary market.
Some people try to scare us about the impact of artificial intelligence (AI), telling various versions of the Terminator story. If the machines are not cybernetic androids that riddle us with bullets, they at least make our jobs redundant. This, it seems, applies to all companies and all professions, including venture capital.
Consider the following, written as part of an opinion piece by the Commercial Director of a private equity digitalization consultancy:
“To put it bluntly, [venture capital] companies that don’t embrace [artificial intelligence] are giving themselves a built-in expiration date.”
Statements like this will send many private equity managers into existential panic attacks.
But rather than risk large sums to stay on the frontier of artificial intelligence, which is still in its wild early days of trial and (many) errors, venture capital firms and their investors should keep calm and move forward. The only good advice is to stay aware of the changes, adapt cautiously, and let others make the mistakes .
It is unlikely that a cybernetic android , no matter how friendly or intelligent, will ever replace the power of human touch in venture capital . It will also likely take a decade or more of false dawns to eliminate the related problem of AI’s tendency to make things up, known as «hallucinating» in AI circles. Even the best AI programs today (trained to use deduction and inevitably educated on sources, especially the Internet, where false information exists) combine a lack of awareness of biases – some say human ethics – with the mission of filling gaps. with answers. The most technologically advanced AI has created fake Ebitda figures for Tesla, invented fake quotes, quotations and even books attributed to real experts, and provided spurious evidence that dinosaurs left carvings in stone and that churros are proper tools for home surgery.
Programming AI with the equivalent of a coherent and unwavering sense of fiduciary duty to eliminate the hallucination problem is likely to be costly, time-consuming, plagued by failure, and ultimately a distraction to investment firms. in general.
Additionally, private equity is likely to be the most difficult of all investment areas when it comes to developing AI systems that can actually identify winning investments. There are at least a couple of reasons for this.
First of all, venture capital is precisely that, private. There is no standardized disclosure of numbers that can be fed into a venture capital AI filter as is the case for publicly traded companies. In fact, the most successful venture capital investments are often made with what in the stock markets would be considered illegal, inside information. Access to this type of information will likely always be the domain of carefully cultivated human networks. Another reason – related to the first – is that no one in venture capital wants to use the same methods as their counterparts , which greatly increases the cost and maintenance burden of what will necessarily be bespoke venture capital AI systems.
Where we’ve seen the most excitement recently about the use of AI in venture capital is in the secondary market , where rumors abound about new funds planning to use the technology to analyze cash flows and ultimately price assets. existing venture capital funds. But unless these AI systems propose prices that are actually higher than historical averages (and I’m willing to bet that systems designed by buyers will have a bias – conscious or not – towards lower prices), it will be very difficult to convince sellers. , who in this market are rarely in trouble and have typically designed their portfolios to hold to maturity, that the AI justifies a different price than the one they want to accept. Skepticism regarding AI-inspired secondary pricing will be even greater, given the serious issues noted above regarding the reliability of AI.
The bottom line is that AI is likely to have minimal impact on how venture capital investments are chosen or priced , thus preserving many high-paying venture capital jobs. Where it will have a real impact is on the efficiency of processes , which can be standardized more easily (and examined and therefore improved more quickly). Above all, standardized systems should be able to free executives – especially junior analysts – from time-consuming tasks such as collecting data and writing quarterly investment reports for investors, conducting due diligence and even writing letters of approval. request for proposals and all other documents related to sales or purchases of portfolio companies.
Managers will be able to monitor, visit and future-strategize a broader range of companies in what remains a notoriously inefficient market where highly viable opportunities remain more likely to fall by the wayside than to be picked up by investors. . This should increase profitability rather than reduce it.
As AI reduces the costs associated with simpler analytical tasks, it should raise employment levels and even change skill sets. The premium on quantitative skills for those entering the lower ranks of private equity will be replaced by a new emphasis on qualitative judgment and the ability to ask insightful questions. Rather than decimating jobs in venture capital, AI will usher in an era of greater and more consequential human input in a sector that will grow even more rapidly.
