Top-tier alternative asset managers are already implementing AI. Mid-market will soon follow this trend. BeBeez supports its readers in this moment of labour’s pivotal transformation
On 15 September, Monday, it will expire the early bird discount for signing up to BeBeez Academy and Digitiamo (Lio Factory) course for practical use of artificial intelligence in private equity investment processes and management of portfolio companies (click here for classes programme and enrollment by 30 September, Tuesday).
This online course will be available on Excellence MaiHub platform of Digitiamo where 4 sessions of 2 hours each will take place in live streaming and recorded on 2, 9, 16, and 23 October, Thursday.
At the end of 2023, almost 10% of private capital firms started using artificial intelligence-based solutions for relatively complex tasks, such as identification of investment opportunities, research, deal origination, contract management and due diligence. By 2028, this share could rise to 25%, a May 2024 Deloitte Insights said. The item also pointed out that, given the adoption curves of recent technological advances, the percentage of companies active in private market investments using artificial intelligence for relatively complex applications will increase by at least 30% over the next five to seven years. Furthermore, 40% of companies that use artificial intelligence for complex tasks each year may also decide to use it for even more complex tasks, such as portfolio valuations.
In March 2025, Chris Sparenberg, the head of S&P Global’s operating system for private markets iLEVEL, said to the company’s blog that the expansion of private capital led to strong pressure on asset managers and allocators to provide more transparency and granularity in data: traditional reporting sources (PDFs, Excel sheets) are no longer sufficient and the demand is now for analytical standards similar to those in public markets. The AI makes it possible to automate the manual processes of data collection, cleaning and analysis, increasing efficiency and accuracy, and will therefore also be instrumental in improving data quality, identifying errors and enhancing process repeatability.
Bain & Co March 2025 Private Equity Report (see here a previous post by BeBeez) reported the results of a survey of private investors representing 3.2 trillion US Dollars in assets under management as of September 2024, who said that most of their firms portfolio companies were in the testing and development phase of generative AI, and that nearly 20% of them operationalised generative AI use cases and were achieving concrete results. Bain & Co’s report delves into what giants such as Vista Equity Partners, Apollo Global Management and Hg Capital have been doing on this front for some time.
In July 2025, London-listed Schroders Capital, a private markets player that has 99.3 billion US Dollars of aum, expanded its advanced AI tools and implemented a virtual investment committee agent for further strengthening the decision-making process (press release). (see here a previous post by BeBeez). Schroders Capital data science team developed such a proprietary technology for supporting the Generative AI Investment Analyst (GAiiA) that launched in June 2024 (press release). The latter tool allows Schroders Capital to efficiently sift through large amounts of data, accelerate due diligence and generate first drafts of investment summaries. Since its introduction, GAiiA helped the private equity team for the generation of investment committee memoranda first drafts and for responding to specific requests related to target during the due diligence phase. GAiiA already assisted in more than 40 investment cases and Schroder’s primary and secondary markets teams use it for all types of private equity investments.
The course of BeBeez Academy and Digitiamo will provide Italian and European professionals with an operative roadmap with scalable models for the implementation of the same technologies that large global asset managers already integrated for their portfolios.
Programme Key Contents:
- Automated deal sourcing via semantic text screens, social big data and market signals
- Automated evaluations on multiples and performance forecasts of target companies
- Assistance tools for document due diligence and financial modelling
- AI driven operating models for investee governance
- Construction of predictive pipelines for exit and valuation benchmarks
