February 10, 2026- Although private markets are at the cutting edge of today’s financial markets, private capital firms themselves have been surprisingly slow to innovate internally, with fragmented systems slowing the adoption of artificial intelligence (AI) and many workflows still reliant on Excel spreadsheets.
Private equity and credit firms expect advanced technology investment and fundraising strategy to be the dominant forces shaping their operating models in years to come. However, to fully unleash those forces, firms will have to overcome some persistent structural challenges, including low organizational readiness for AI, siloed data and technology environments, and a stubborn dependence on manual processes.
The Biggest Obstacle to AI Innovation: Fragmented Data
To be sure, private capital firms are leveraging AI to improve efficiency across operations, from document data extraction and processing to the organization of complex datasets. They are also extending AI into higher-impact areas, including deal sourcing, opportunity identification and critical due diligence workflows.
Nevertheless, according to the results of a new study by Crisil Coalition Greenwich, in a collaboration with Allvue Systems, only 22% of participants rate their firm’s investment in AI above the industry average.
For most firms, data fragmentation remains the biggest obstacle to operational scale and effective AI deployment. Nearly half of firms, and 66% of larger firms, cite a lack of system integration as a headwind.
External data fragmentation is also a problem. Only 12% of firms that work with fund administrators say they have the flexibility to choose a new provider without an expensive data migration. Elsewhere, firms are emphasizing high-quality investment performance benchmarking data, with 44% of firms ranking the integration of these datasets as a top priority.
“Overall, less than 10% of private equity and credit firms say they have achieved a high degree of data maturity,” says Audrey Costabile, Senior Analyst in Market Structure & Technology at Crisil Coalition Greenwich and author of The Future of Private Markets: AI, Data and Human Adaptation.
The challenges are not merely technological. Almost two-thirds of private capital firms cite a lack of internal expertise and training as a significant barrier to AI adoption.
“For private capital firms and other financial services firms, future success will require a dual investment in both modern technology and the talent needed to upskill the workforce and leverage AI and other innovations effectively,” says Audrey Costabile.
An Achievable Short-Term Goal
In the short term, private capital firms looking to upgrade their technology infrastructure and pave the way for broader AI-driven enhancements are prioritizing what seems to be an achievable goal: reducing their dependence on traditional tools. Despite investments in purpose-built systems, 56% of private capital firms say a heavy reliance on Excel remains a top technology challenge that introduces data-integrity risks and limits scalability.
“Most private capital firms are finding ways to become more data- and technology-forward to enhance workflows. They’re picking their spots to make this happen. Although this may be piecemeal, these strategies do seem to be pushing the needle in the right direction,” says Audrey Costabile.
The Future of Private Markets: AI, Data and Human Adaptation presents the full results of the Q4 2025 study assessing AI readiness and adoption among private capital firms, examining the key challenges firms will have to overcome to fully leverage AI at scale, and identifying areas such as portfolio management and valuation in which private capital firms believe AI and technology innovation will have the biggest impact.