BOISE, Idaho, NEW YORK, CHICAGO, LONDON and HONG KONG, July 28: A global study of 178 senior fund manager executives released today by Clearwater Analytics finds a decisive shift in the asset management industry: the majority of fund managers now expect AI to deliver major or transformative change across critical front-, middle-, and back-office functions within the next year.
The study, "GenAI and the Data Divide," finds 62% of fund managers expect AI to transform how firms generate and summarize data, 58% expect it to transform decision-support and portfolio recommendations, and 57% expect a transformative impact on predictive modeling and stress-testing. Adoption is accelerating alongside it: 95% of firms raised their AI budgets in the past year, and 85% plan to raise them by at least 50% more over the next 12 months.
But the study also identifies what will determine which firms actually capture that transformation. A 23-percentage-point gap exists between how firms rate the completeness of their data versus its accuracy. While 79% believe their data is complete, only 56% consider it accurate. This gap is emerging as a key differentiator between firms seeing measurable returns from their data and those still waiting for theirs to realise value.
A Year of Operational Transformation
The research reflects a significant consensus among investment professionals regarding where AI will deliver the most profound impact over the next 12 months.
Leading the charge is the automation of content and data synthesis: 62% of fund managers expect AI to facilitate a major or transformative change in creating standardized written outputs and condensing complex data into concise summaries.
The industry’s reliance on predictive modeling is also set for an AI-driven overhaul. 57% of survey respondents anticipate a transformative impact on how their firms analyze historical and current data to forecast outcomes and evaluate stress-test scenarios, for example. Close behind, 58% of fund managers expect AI to revolutionize decision-support systems, specifically in proposing potential actions or parameter changes such as portfolio rebalancing based on specific objectives and constraints.
Souvik Das, CTO of Clearwater Analytics, said: “Our data shows that the global investment community is no longer just curious about AI. They are deploying it to solve the most labor-intensive aspects of asset management. By automating the heavy lifting of data synthesis and scenario modeling, firms are reclaiming thousands of hours that can now be redirected toward alpha-generating activities.”
Tactical Success in Day-to-Day Operations
The study also provides a status report on the effectiveness of AI tools currently in use. Far from being a theoretical benefit, AI is already delivering measurable tactical advantages in day-to-day tasks:
· Natural Language Interaction: 73% of fund managers surveyed describe their use of AI natural language agents as “effective” for querying data-intensive investment platforms, risk management, and reconciliation.
· Deep-Dive Analysis: 62% of respondents find AI agents effective for delving into complex topics such as regulatory compliance, with nearly half (47%) describing these tools as “very effective.”
· Workflow Automation: The push toward straight-through processing is gaining momentum, with 63% of managers successfully using AI to automate repetitive workflows such as daily report generation.
· Multi-Agent Orchestration: 62% of firms report success in using AI to trigger operations based on specific data thresholds or schedules, indicating a move toward more sophisticated, autonomous system behaviors.
Solving the Data Dilemma
Data quality has always been the industry’s hardest problem. This study shows fund managers now understand why it matters more than ever.
70% of fund managers surveyed say deploying AI has sharpened their focus on data management, with 8% calling the shift in attention “dramatic.” Two thirds (66%) of fund managers now feel their AI tools are effective at managing the unique challenges of alternative data, an historically difficult area to scale.
That progress on alternative data is real. But as noted above, it hasn’t closed the gap that matters most. Only 56% of firms rate their data as accurate or reliable, against 79% who call it complete. AI is sharpening firms’ attention on their data. It has not yet solved the trust problem underneath it.
“What’s striking is that AI adoption is forcing fund managers to confront the fundamentals of data management in a way nothing else has,” added Souvik Das. “The confidence we see in managing alternative data is particularly telling. It suggests that firms that invest in AI are also the ones investing hardest in getting their data right, and that the two have to move together. This is a fundamental shift in the industry’s awareness of complexity.”
The Divergence in Adoption
While the majority of the industry is bullish, the study also highlights a growing gap between leaders and laggards. In several categories—including software delivery and workflow coordination—roughly 12% to 18% of managers still expect “minor or little impact” from AI. This divergence suggests that while the technology is ready, the internal infrastructure and cultural readiness of firms vary significantly.
