Global asset managers to raise AI budgets by at least 50 per cent
A majority of global asset management firms intend to increase their artificial intelligence spending by at least 50 per cent over the next year, signaling a major shift in how funds approach data management and portfolio operations.
Global asset management firms are preparing to significantly increase their artificial intelligence spending, with a majority planning to boost budgets by at least 50 per cent over the coming year. The surge in investment highlights how rapidly the technology is reshaping the financial sector and altering traditional workforce dynamics.
These findings come from a new study released on Tuesday by US fintech company Clearwater Analytics. Titled “GenAI and the Data Divide,” the research surveyed 178 senior executives working across hedge funds, private credit, and institutional asset management in Europe, the US, and Asia.
The respondents indicated that the technology will heavily influence labour-intensive operations. Specifically, 62 per cent of the polled fund managers anticipate transformative changes in how data is generated and summarised. This shift will directly affect the daily workflows of investment teams.
Beyond basic data handling, the technology is expected to upgrade core investment functions. Some 58 per cent of executives pointed to significant effects on decision-support systems, such as portfolio rebalancing, while 57 per cent highlighted advancements in predictive modelling and stress-testing.
This shift means that artificial intelligence is moving beyond simple automation to tackle historically complex operational tasks. Souvik Das, chief technology officer at Clearwater Analytics, noted the profound impact this has on the underlying infrastructure of investment firms.
“What’s striking is that AI adoption is forcing fund managers to confront the fundamentals of data management in a way nothing else has,” Das stated. For investors and market professionals, this suggests that future competitive advantages will rely heavily on how effectively firms can integrate these advanced tools into their core data architectures.
