Hamish Paget-Brown recently spoke to The Drawdown about what the explosion of LLMs tells us about how tech performs compared to investment teams, and what are the associated risks to consider as AI impacts the private equity sector.
How is AI being used to source potential deals?
Hamish states: “Sourcing potential targets has been the obvious place to start for a lot of companies, because at this stage you are looking at large volumes of high level statistics and not drilling down into the details of a potential investment.”
A good example of this is ECI’s proprietary AI platform Amplifind™ which surfaces businesses that look like typical ECI deals. This tool has led to an eightfold increase in lead-sourcing efficiency, as quality and speed both increases. Hamish continues, “AI cannot necessarily say ‘this is a good investment’, it can certainly say: ‘Based on what you have invested in before, this is likely to be a good investment – so why don’t you take a further look’”?
What are some other AI use cases in private equity?
Pipeline management is another area that has potential, given pipelines are increasing in size and lead time. For Hamish, this is all about helping to prioritise opportunities. “This might be through automating processes such as news monitoring, business updates and communications with the potential investment.”
A lot of research has historically been done by people within investment teams to get under the skin of potential businesses. AI opens more opportunities to automate this, with Hamish saying: “We have recently integrated OpenAI’s Davinci into Amplifind™ to provide users with automated business descriptions, reducing the need to leave the app to provide additional context.” Generative AI means you can also go beyond looking at financials or simple keyword tags when mapping a market.
Should investment teams be worried about robots doing their job?
Hamish comments, “Private equity is a people industry, with relationships at the heart of a lot of the decisions that are made. For example, feeling you would be able to work with a management team for the foreseeable future, and vice versa, is an important factor in deciding whether to invest, and it’s not something that AI will be able to decide for you.”
Assessing potential companies requires interpretation and a complex contextual understanding of business models, sectors, markets, and processes. Generative AI can help here by streamlining those processes, for example by summarising DD, which gives investment teams more opportunity to focus on the growth and value creation opportunities ahead of them. Having a view of the future which is beyond just statistical probability is part of what makes the job unique. As Hamish comments, “Intuition and experience both play a role in their decisions and while AI may be able to accurately replicate the latter, it will have a hard time replacing the former.”
What are some risks of using AI for decision making?
There are questions around accountability that needs to be considered. Hamish states, “While AI might tell you to follow a certain course of action, the reasoning behind that decision will likely be unobtainable. This lack of accountability and understanding is a huge risk when it comes to making such consequential decisions.”
By their nature, LLMs are trained on historic data, so there is also a risk that they won’t be able to keep up with emerging trends, which is a key part of understanding future opportunities.
Lastly, Hamish states that as many use cases are still emerging, there are questions around compliance and data security that are not yet fully ironed out. “As it isn’t fully regulated, private equity firms will need to be careful that they consider the potential legal implications of its use, both now and in the future.”
So, can investment teams rest easy? There is no doubt that AI will play an important role in private equity, particularly around the more manual processes of origination and sourcing, pipeline management and prioritisation, document summarisation and drafting, and various other workflows. However, while private equity remains a people industry, there are aspects to the decision making that AI will be unlikely to be able to replicate soon. What you may see is investment teams freed up to spend more time on adding insight and value to the companies they’re working with.
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