The answer is far from straightforward. It will depend on the commercial strategy of individual firms and their portfolio companies.
What is universally true, though, is that taking full advantage of AI’s rapid progression requires a solid data and cultural foundation.
Far too many businesses invest in experimenting with, or applying, new innovations when really their resources would be much better applied ensuring the infrastructure they use is up to scratch.
Even to this day, the data exchange process between PE firms and their portfolio companies – extraction, analysis and reporting – can take months. This is far too slow and can seriously undermine decision-making and value creation.
But establishing a well-defined data strategy is not just about numbers. There is a significant opportunity for firms that harness data to craft a compelling equity narrative for portfolio companies that resonates with stakeholders, investors, and potential buyers.
Whether considering an acquisition, implementing a value creation strategy, monitoring performance, or planning an exit, more than ever leveraging data-driven insights will enhance the clarity and attractiveness of the investment proposition.
As investors get more familiar with what is required to drive value from AI, investment theses underpinned by a solid data strategy will become a necessity as opposed to a nice-to-have.
It also necessitates significant cultural and organisational changes, such as up-skilling and retraining staff, restructuring teams, and evolving business models.
Looking forward
The opportunity for investors is less likely to be in the buying of AI organisations themselves – of which there will be a plethora and of whom a handful will be winners – but rather how to transform existing businesses to become enabled by AI and data.
This is a hugely exciting time for PE funds who really engage with the latest trends in AI.
They are more agile in their ability to respond than the large PLCs and should be able to take advantage of the ability to rapidly transform business models driving a significant investment return in a short hold period.
However, none of this is possible without having the right data foundations in place, and many still do not have this.
Finally, as with all exciting disruptions, the increased reward is mirrored by increased risk; both PE funds and management teams should be simultaneously assessing the commercial opportunities to leverage AI, as well as the risks it poses to legacy business models – are your competitors adapting faster than you, are new players entering the market, are consumer behaviours changing as a result of easier access to AI tools?
