AI reshapes investing in private markets

Wealth managers that integrate AI with human expertise will gain a competitive edge, while others risk being left behind.

Private equity firms are sitting on record levels of dry powder yet face increasing pressure to deploy capital wisely in an uncertain economic climate. Meanwhile, family offices and wealth managers are allocating more to private markets, creating additional complexity in deal flow, due diligence and reporting.

This has opened the door for artificial intelligence (AI) to play a transformative role in private markets — not by replacing human judgment, but as a catalyst for sharper, faster decision-making.

These technologies are transforming everything from deal sourcing to portfolio management. Such is the pace of innovation that even the makers of AI solutions are forced to regularly reassess what is possible.

For private markets firms, however, the most immediate impact is in accelerating time-consuming processes that traditionally created bottlenecks. The average due diligence timeline has expanded to 203 days compared to 123 days a decade ago, an increase of 64 per cent, research by Bayes Business School found. With AI, it’s possible to shrink that down from months to weeks, and complete initial due diligence questionnaires in just a day.

For example, firms can use AI to analyse thousands of documents across multiple data rooms simultaneously, flagging key risks and opportunities that merit human attention. Global real estate investment firm GTIS Partners previously spent five to 10 days completing due diligence questionnaires (DDQs) as part of the investor acquisition process. By leveraging AI, GTIS now completes DDQs in just one to three days.

This also gives private equity firms a way to deal seamlessly with global transactions, by using either AI software directly or purchasing managed services solutions powered by AI, to ensure round-the-clock coverage. For family offices, the enhanced efficiency of AI is democratising access to deals that were previously difficult to evaluate with limited resources.

Advising allocations

Beyond speed, we’re also beginning to see the impact of AI’s depth of insight. Specifically, AI is moving into the front office and playing a role in informing the investment decisions themselves.

Machine learning algorithms can identify patterns across vast datasets that humans simply can’t process. This can be especially valuable in areas like deal sourcing, where AI can screen thousands of companies against investment criteria, highlighting opportunities that might otherwise be missed. For wealth managers advising on private market allocations, this technology enables more sophisticated portfolio construction and risk assessment.

Firms are even leaning on AI to help generate conclusions and predictions — as Lisa Weaver Lambert, author of the AI Value Playbook, notes, investment committees are increasingly soliciting AI’s ‘opinion’ or ‘vote’ as part of the evaluation.

However, it is important to be clear-eyed about the challenges. AI is only as effective as the data which it is given.

AI buyers need to put a premium on finding trusted partners capable of keeping their data secure and supporting the granularity required for their use cases. For private markets, this means vendors that can extract information such as dates and percentages buried inside contract texts, and structure it in tables so that it can be analysed and compared.

Tipping point

In the financial world, generational and cultural challenges may also exist in AI adoption. Many successful investors built their careers on relationship-building and intuition, making them naturally sceptical of technological solutions.

The key to overcoming these obstacles lies in taking a measured approach. Rather than rushing through attempted wholesale transformation, successful firms are the ones starting with specific use cases where AI demonstrates clear value, such as automating routine contract review or streamlining investor reporting. This creates quick wins that build confidence.

It is also crucial to maintain a ‘human-in-the-loop’ approach. The most effective implementations combine AI's processing power with human judgment and experience. For instance, while AI can rapidly analyse historical deal data to identify success factors, it is still human investors who must evaluate whether these patterns will hold in current market conditions.

We are approaching a tipping point where AI adoption will become a key differentiator in private markets. Those who master the integration of technology while preserving their human edge will gain significant advantages in both deal execution and value creation. Those who wait for the perfect moment to try AI will be left behind.

The stakes are particularly high for family offices and wealth managers, who must compete with larger institutions while maintaining lean operations. AI helps to level this playing field, providing sophisticated capabilities without requiring massive infrastructure investments.

The message to the industry is clear: AI in private markets isn't about replacing human expertise — it's about amplifying it.

The future of private markets will belong to those who can successfully blend technological capability with traditional investment acumen. In this environment, it is not the biggest players who will necessarily win, but rather those who can most effectively harness AI to enhance their natural strengths.

Freddi Muelke, head of alternative assets, Robin AI