Private equity is undergoing an artificial intelligence-driven transformation. While investment managers may have already dabbled with integrating AI into their processes and portfolio companies, the emergence of more advanced and easily accessible AI has supercharged what they can now do.
In fact, PWC research forecasts that assets managed by algorithm-driven and AI-enabled digital platforms will surge to almost $6tn (£4.6tn) by 2027, nearly double the figure for 2022.
This trend aligns with an increase in PE firms experimenting with the use cases of AI in their transactions and trading strategies.
Over the next five to seven years, Deloitte predicts that 25 per cent of PE firms will be using AI to augment their portfolio valuations.
It makes sense. With generative AI’s remarkable ability to analyse large unstructured data sectors, identify patterns and extract valuable insights that can impact investment theses, many things that were difficult to do have become much easier.
Cultural shift: understanding the how and why
But this transformation is not merely about adopting new technologies, it is also about reshaping the culture of investment itself and re-defining the art of the possible.
Historically, investors have wanted visibility into core financial trends.
Now they have much higher expectations for transactions on a data front row, and are much more interested in understanding the how and why certain financial and operational trends are occurring.
This is redefining the investor’s decision-making process.
PE firms have typically relied on experience, intuition and their own network intelligence to find and create value, usually supplemented by a basic level of analysis.
But rising asset prices and competitive markets can make it risky to rely solely on these methods.
With the speed of change that the latest developments in AI are causing in markets, there is a far greater likelihood that a good investment could turn bad during a hold period.
Investment committees are acutely aware of this and are demanding an even greater level of granularity before backing investment theses that might previously have been considered safe bets.
While traditional skills remain valuable, interpreting data quickly and at scale is helping investment managers de-risk investments and optimise value creation and returns.
Shaping the equity narrative
This shifting buyer behaviour is creating a growing expectation for management teams to provide broader and deeper datasets at exit.
It is now critical for management teams to place greater emphasis on data and analytics to support their equity story, to give investors comfort on past performance and future returns.
Again, investors are even more concerned with evidencing the how and why when it comes to performance and trends; just saying that we have grown profitably by X per cent year on year is now not enough, it needs to be evidenced by granular data and solid analytics.
This also allows management to showcase opportunities for further future growth, with investors being able to leverage these data assets to underpin their investment cases.
Management teams are expected to be using these assets to run the operation and the platforms must be able to scale with future growth, especially if mergers and acquisitions is a strategy that an investor would like to pursue.
