When ChatGPT exploded onto the scene in November 2022, it quickly captured global attention, reaching one million users within just five days of its launch. As a result, Artificial Intelligence (AI) was catapulted into the mainstream as firms across all industries started to pay closer attention to AI and its impact on their business, sparking a ‘Generative AI arms race’.
Private equity has been no exception, as firms now more than ever are clamouring to understand whether – and how – to make use of artificial intelligence. Generative AI, of which ChatGPT is an example, has opened up a wealth of possibilities and use cases in private equity already – but this is only scratching the surface. As the technology develops other forms of AI – like Generative AI’s forward-looking brother, Causal AI – will, in time, prove to have even more far-reaching implications for the industry. Simply put, AI has become too big to ignore.
Where are most firms now?
The use of AI in private equity isn’t new, but its application within PE has generally been poorly understood beyond a small handful of large, technology-savvy and forward-looking firms. Some firms are further ahead in their understanding and use of AI than others. For example, Swedish firm EQT Ventures uses its proprietary AI platform for deal sourcing, market analysis and to provide benchmarking. The vast majority, however, are still in exploration mode, figuring out how and where it makes sense to leverage AI in their operations.
Common use cases
One of the most commonly discussed use cases for Generative AI in private equity is document extraction; the ability to extract data from complex and disparate documents in a variety of formats – think financial statements from portfolio companies, market reports, or legal documents – and structure the information into a single document. These tools are ideal for helping businesses complete manual, time-intensive work and free up time to focus on other higher-value activities.
Another relatively near-term use case is knowledge sharing, such as managing LP queries. A generative AI chatbot could be trained to answer a lot of the questions a potential investor might have during due diligence, or that an existing investor might have about fund performance. A similarly manual and often repetitive task, AI can free up valuable time, reduce costs and improve efficiency as well as improve the relationship between GP and LP through enhanced responsiveness.
More involved and far-reaching applications for AI include deal origination and the operational side of the business. For example, there are products available that will trawl the internet for companies that match or display desired characteristics in line with your search criteria – a task junior analysts are paid to do for hours on end day in and day out. AI may not discover a sure-fire bet, but it can serve to narrow the funnel.
AI can also be used to tackle inefficiencies and improve effectiveness through the finance and operations of a firm, to reduce costs and provide a better quality of service to investors. By their nature, such applications tend to be more bespoke, require more expertise and so tend to incur higher up-front costs to resolve but could yield benefits that may make it a worthwhile investment.
As the technology develops, the potential applications for AI in private equity will increase. One particularly exciting area is Causal AI. This emerging technology looks at past correlations in data to identify patterns that explain the true relationship between cause and effect. Ultimately it will add a predictive dimension to further enhance human decision making. Causal AI has the potential to revolutionise everything from informing investment decisions and risk management to determining the optimal time to exit an investment or even succession planning.
For those just starting out on their AI journey, it’s important to recognise that AI isn’t a panacea. It won’t solve all of your problems at once. Firms should start by identifying a single use case and test it in a confined environment before moving on to the next application and potentially broadening its use. It is also important to recognise that in many instances, AI doesn’t replace human involvement, rather it enhances the capacity of the human.
When spreadsheets entered widespread usage in the 1980s, they didn’t replace accountants – rather, it was the accountants who didn't use spreadsheets that were eventually replaced.
It’s helpful to think of AI as augmented intelligence – this is especially true in private equity where human skills and decision making will always be vitally important.
A final consideration is to recognise the importance of safeguarding data. In leveraging third party tools, particularly when feeding proprietary and sensitive data, it’s vital to understand who owns and can access the data. This is less of a problem when using publicly available data sources, but in the case of using or supplementing with your own data, it becomes a different matter.
Advice for getting started
Whether you’re still in the early stages of investigation or have a robust AI strategy in place, AI is here to stay and the number of use cases in private equity will continue to increase. To simply ignore it would be a shortcut to obsolescence and those that stand still for fear of “getting it wrong” will fall behind their competitors who take the time to understand and implement it where it makes most sense for them. If you’d like to better understand where AI can fit within your business now, or how to use AI powered platforms such as Lantern to enhance your performance and operations, please get in touch – our team of data and AI gurus would love to help.
Originally posted in The Drawdown.