Asset Managers Plan 50%+ AI Budget Hikes as Clearwater Study Reveals Data Divide

Global asset management firms are pouring money into artificial intelligence at an unprecedented pace. A new study from US fintech firm Clearwater Analytics reveals that a majority of firms plan to raise their AI budgets by at least 50% within the next year, and 63% have already done so over the past 12 months . Yet beneath the headline spending surge lies a paradox: two-thirds of fund managers fear they are over-investing, and the firms that see real returns are those with the strongest data foundations, not the largest budgets .

The findings come from Clearwater's 2026 global report, "GenAI and the Data Divide," which surveyed 178 senior executives — including CEOs, CFOs, CIOs, and CROs — at asset managers, hedge funds, and private credit firms across Europe, the United States, and Asia Pacific .

The AI Spending Paradox

AI budgets across the industry are rising at an extraordinary rate. According to the study, 63% of firms increased AI spending by more than 50% in the past 12 months, and no firm reported cutting its AI budget . But this rapid acceleration has created a sharp divide in sentiment:

• 66% of fund managers worry their firms are already over-investing in AI .
• 25% believe their organisation is still not investing enough .

"A striking investment paradox is emerging at the heart of the asset management industry’s AI revolution," the report notes . While budgets are climbing, there is no consensus on what the right level of spending actually looks like .

Which Operational Areas Are Most Impacted?

The study identified three operational areas where AI is expected to deliver major or transformative change within the next year:

• Data generation and summarisation — 62% of respondents expect transformative impact here, making it the area most poised for disruption .
• Decision-support systems, including portfolio rebalancing — 58% .
• Predictive modelling and stress-testing — 57% .

These numbers reflect a clear shift: AI is moving beyond experimental projects and into the core workflows of investment management. Two-thirds of fund managers also reported that their AI tools now effectively manage alternative data, an area traditionally difficult to scale . Additionally, 62% reported success with multi-agent orchestration — autonomous operations triggered by specific data thresholds .

The Real Differentiator: Data Quality

The study's central finding is that the gap between AI leaders and laggards is not about budget size or speed of adoption. It comes down to the quality of the underlying data foundation .

"AI adoption is forcing fund managers to confront the fundamentals of data management in a way nothing else has," said Souvik Das, Chief Technology Officer at Clearwater Analytics .

The data divide is stark: 44% of firms with good or excellent data accuracy say their risk management has become much more proactive, compared with only 17% of firms that rate their data as moderate or poor . Almost all surveyed executives (95%) have increased their AI budgets in the past year, but bigger budgets alone aren't translating into better results for firms with weak data .

Broader Industry Context

The findings align with trends seen across financial services. A separate KPMG survey found asset management and private equity organisations projecting average AI spending of $148 million over the next 12 months — up nearly 1.5x from the previous quarter . Data and analytics, along with research and development, were the top investment categories .

The report also reflects a wider industry dynamic: while GenAI investment in enterprises has reached $30-40 billion, a significant number of organisations are seeing little to no return, a pattern Clearwater calls the "GenAI Divide" .