The Dutch asset management sector is on the verge of a large-scale transformation driven by artificial intelligence (AI), but the path from experimentation to real added value is proving difficult in practice. New research by KPMG, entitled'State of AI in Asset Management', shows that although 80% of organizations see AI as a strategic priority, the sector is still largely stuck in the start-up phase.
Although there is broad consensus on the urgency of the matter—92% of respondents believe that the adoption of AI should be accelerated—implementation is lagging behind. KPMG states that three-quarters of Dutch asset managers are still in the early adoption phase, with the focus mainly on small-scale pilots and proof-of-concepts.
A notable bottleneck is the lack of concrete objectives: nearly 60% of institutions have not yet formulated measurable goals for AI projects. This makes it difficult for many organizations to demonstrate the actual business value of their AI initiatives.
At present, asset managers are primarily focusing on improving operational efficiency. The most important applications identified by KPMG are:
In order to be able to use these technologies on a large scale, 75% of efforts are currently being invested in laying a solid foundation in the areas of data, technology, and governance.
Another crucial theme in the report is 'Responsible AI'. All organizations surveyed recognize the importance of ethical frameworks and guardrails when deploying AI. However, 84% indicate that they are currently unable to fully control all AI risks. Rapid technological developments often outpace internal control mechanisms and the development of regulations, such as the EU AI Act.
KPMG concludes that the sector must make a "free translation" from experimentation to integration into core processes. When asked what advice they would have given themselves five years ago, many asset managers replied: "move faster and act more courageously."
"Success with AI depends not only on data and technology, but above all on bridging skills gaps and building a culture of collaboration," according to the report. The challenge for the coming years will therefore be to scale up AI initiatives and transform organizational structures in order to exploit the full potential of the technology .
