Will AI revolutionise private equity?

Experts weigh in on the potential, challenges, and differing perspectives on AI's role in the PE industry.

Artificial intelligence (AI) seems to be the topic du jour. With ChatGPT’s controversial introduction to the public sphere, and its seemingly endless use cases, there’s renewed focus on what this technology could potentially mean for the future of many industries.

Likewise, there seems to be a fair bit of hype around what AI can do for private equity (PE). From monitoring portfolios and generating leads to optimising back-office operations, there’s a heap of potential applications.

But is it really as much of a panacea as some analysts are making out? Or will it end up like other, much-lauded innovations – say carbon sequestering or autonomous vehicles – forever being that game-changing advance that’s always just out of our reach?

To be sure, there are concrete use cases that funds can start taking advantage of. One expert, who works in venture capital in the field of AI, robotics and computer vision, points to various niche applications. “AI can of course, enhance the decision-making process by analysing large amounts of data available on platforms like PitchBook, Crunchbase, etc, very quickly. This can of course allow any fund manager to identify trends, assess market dynamics, and assess the competitive landscape.”

Added to this is the potential to facilitate and accelerate internal processes, he continues. “AI can of course streamline routine tasks, such as due diligence, data collection, [and] in some cases portfolio management” And the result of this? It can “[free] up human professionals to focus on [the] more strategic and creative and important aspects of their work.”

For Steve Goldberg, a partner at Finistere Ventures, its biggest potential comes earlier than that. As someone who works in the early stage of the market, it’s “very noisy, meaning there's just lots and lots and lots of companies in many, many sectors. And using AI to help parse or narrow down the search space is certainly interesting and would be welcome for identifying the most promising companies.”

Really, the applications can be divided into two parts. There are those specific to private equity professionals – say, risk assessment, crunching data and identifying targets. On the other side, it has potential for revamping how departments across the rest of the organisation work – say, customer service, human resources, IT, and so on. Let’s take a look at marketing, for example. Here, AI could already feasibly help with lead prioritisation, content creation or even as chatbots for dealing with new leads or existing customers.

Opposing views

There was a divide among the experts we interviewed for this article whether people’s expectations of AI were overhyped.

The robotics and AI expert took more of a negative view, highlighting the fact that many variables are involved with investment decisions. “While AI can assist in data analysis and pattern recognition and aid the decision-making process, the qualitative factors that play an important part in PE and VC investments rely a lot on the nuances of human judgment and intuition.”

Added to this is the problem of sourcing sound data. “AI models often require substantial historical data to make accurate predictions. In the case of startups or new investment opportunities, historical data is obviously limited, making it challenging for AI to provide any realistically applicable insights.”

However, Akshay Padmanabha, head portfolio manager at Tower Research Capital, had more of a positive view, pointing to the fact that many new technologies go through cycles of being hyped up before their actual potential is uncovered. “I think we're in the over-hyped phase for now, but that doesn't necessarily mean that the impact AI will have on PE or any other industry is not going to be meaningful and material.”

On a similar note, Jacob Krogh, an institutional private market investor, adds: “I think AI has a lot of potential to add to the PE investment process and the entire value creation cycle. However, it will take time before it becomes an integrated part of the investment process… and there's likely to be a lot of trial and error in that process.” He adds that technologies being hyped up can even turn out to be a good thing, focusing people’s attention on its applications and getting the general market interested.

A balancing act

Certainly, there is plenty of potential, but there are still significant challenges that must be tackled first. Regulations and ethical concerns are a big one. In the black box of an AI’s judgment making process, who is to blame when things go wrong? AI is also notoriously bad at understanding context and ethical considerations. We’ve also seen time and time again how AI can incorporate biases in unforeseen ways depending on its source data.

People also almost seem to trust in AI too much, Padmanabha comments. “If you get to the point that you're really relying on AI and assume that everything it says is the truth, you're going find yourself in a tricky situation.” A recent case of two lawyers being fined for ChatGPT in court – which was discovered after it created fake citations – underlines his point.

It seems that, at least for now, AI should be seen as a supporting tool. “For now you will always need a human overlay to any analysis of historical information, no matter how big the data set is. So it'll be an important supplement, but it'll not be able to replace the interpersonal trust and the human decision-making in the PE industry,” Krogh comments.

Goldberg agrees, adding that, “until we get to a point where we have sentient behaviour by AI and it's literally same as a human, I think it's going to be hard to think that these kinds of decisions – that ultimately relate to thousands, millions, or billions of dollars – will be done by machines.”

As with many discussions of technological advances that are still in flux, there is only so much that can be said at the moment. Added to this, other emerging technologies, like quantum computing and robot processing automation, could hold similarly interesting possibilities for the future of PE. It’ll be interesting to see how these two alone will fit in with the intersection of PE and AI.

However, for now, it seems to be a balancing act. AI has its limitations and restrictions. “Intuition and judgment are predictive metrics that out of, as of 2023, AI is not at par with human judgment and intuition,” the AI and robotics expert states.

One of its biggest strengths appears to be in freeing up the people at PE companies and giving them deeper insights into their markets. Ultimately, there should be a symbiotic relationship between humans and computers that can let each side do what it does best.

*The expert insights for this article were collected via video using ArbolusCanopy. If you’d like to see an AI summary of this Canopy, you can view it here.

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