AI adoption is growing quickly in wealth management, but a new HCLTech study suggests the bigger question is now how much of the industry needs to change around AI. Released on September 28, the “Hidden In Pl(AI)n Sight” synthetic research report is based on 1,066 AI personas modeled on senior wealth management decision-makers across 17 global markets. Conducted with Evidenza, the study combines AI-generated representative personas with human review and validation.
84% say their operating models need a major redesign
According to the research, 84% of global wealth management firms believe their operating models require fundamental redesign to fully realize AI’s potential. At the same time, 98% of industry leadership teams are actively pursuing an AI agenda.
The gap appears when companies move from AI adoption to more advanced forms of automation. HCLTech says only slightly more than 7% are actively building agentic AI capabilities, suggesting that widespread interest in AI has not yet translated into equally broad preparation for more autonomous systems.
research identifies three blind spots behind this gap.
Three key AI blind spots are also highlighted in the research. Many firms are using AI mainly to improve efficiency instead of changing how their businesses work. At the same time, they are investing in new technology but may not be making enough use of their own client data and knowledge. Another concern is measuring results. While companies are tracking AI adoption, fewer are checking whether it is helping increase revenue, improve client value or create new services. Only 12% are measuring new revenue linked to changes in their operating models.
Client data could matter more than another AI tool
Client data is also emerging as an important part of the AI race. Executives ranked first-party and behavioral data as more valuable for standing out than technology infrastructure, cloud platforms or AI partnerships. Nearly 80% believe future industry leaders will be those that can combine AI with their own client knowledge, human expertise and outside partners. Confidence also varies by region, reaching 89% in APAC, 84% in North America and 38.3% in Europe.
Why the research method matters
Synthetic research was used to carry out the report, with AI personas created to represent different people in the wealth management industry. These personas helped explore industry views on a larger scale, while human experts reviewed the findings and added real-world context. For wealth management firms, the bigger message is simple: AI is not just about adding new tools. It also needs to work with client data, business operations and clear goals to create real results.
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