Organizational maturity with Artificial Intelligence (AI) and Generative Artificial Intelligence (GenAI) is growing as asset management firms focus on change and knowledge management, according to KPMG 2025 Asset Management Industry Outlook.
When asked about their organization’s priority initiatives, 61% responded with broader awareness and education, followed by empowering employees to experiment in using AI with enterprise guardrails, at 49%.
These priorities are helping drive the shift in AI maturity, from the conceptual stage (39% in KPMG July pulse survey; 33% in this survey) to the developmental stage (26% in the July pulse survey; 39% in this survey), indicating progress is being made to advance their AI capabilities and coordinate efforts across the organization.
Despite this progress, asset managers are still struggling to achieve full maturity due to a lack of clear vision, as the tactical approach of focusing on specific use cases rather than end-to-end processes hinders capabilities being fully integrated into business operations across the enterprise.
This survey also revealed that GenAI is still primarily being used for back-office functions, including information technology (44%), routine communications (36%), and finance and accounting (24%).
According to the findings, it has yet to make significant headway into front-office functions.
The same perceived challenges continue to prevent organizations from embracing AI, including the risk of data integrity, statistical validity, and model accuracy (53%), lack of awareness and training on AI (45%), and risk of security vulnerabilities (35%).
Commenting on the findings, Colin Clunie, Head of EMEA operations at Clearwater Analytics, said: “It is clear that the industry is leaning towards AI adoption, with successful use cases demonstrating the power of AI in transforming operations and creating efficiencies by simplifying entire investment life cycles.”
For example, he said, it can be used to rapidly produce risk exposures, to help investment managers understand how their portfolio is impacted by breaking events such as elections, or geopolitical disturbances.
“As clients seek quicker data delivery and greater accuracy, particularly during periods of market volatility, AI can be a panacea for meeting these needs,” Clunie told Traders Magazine.
“This isn’t to say there aren’t risks attached to any new technology, which is why human oversight is such a crucial factor in successfully applying AI, as it can control and verify results, detect anomalies, and provide a clear view of decision-making processes,” he commented.
To address these challenges and accelerate “time to value,” 63% of organizations are increasingly leveraging third-party platforms and their built-in capabilities, while another 20% use third-party platforms with added modifications.
This could be due to factors such as rapid acceleration of new technologies, high development and maintenance costs, and resource and talent shortages.
On the other hand, only 21 % are building their AI capabilities in-house.
Organizations are choosing to adopt models that align with their unique organizational cultures, similar to their approach to data management.
KMPG said that given the limited understanding and resources within many asset management firms, a “strategic approach to GenAI adoption is critical”.
“Firms that can effectively integrate GenAI across their entire operation are poised to outperform their competitors,” KPMG said.
