HCLTech has released an AI-based synthetic research study of the global wealth management industry, finding that 84% of wealth management firms believe their operating models require fundamental redesign to fully realise the potential of artificial intelligence.
The study, titled “Hidden In Pl(AI)n Sight,” is based on a survey of 1,066 representative AI personas modelled on senior wealth management decision-makers across 17 global markets.
Despite the widespread focus on AI, the research found that fewer than 10% of firms are prepared for the operating model shift required to translate AI investments into broader business outcomes.
AI adoption outpaces agentic AI
The research found that 98% of leadership teams in the wealth management industry are actively pursuing an AI agenda. However, only slightly more than 7% are actively building agentic AI capabilities.
HCLTech said the findings indicate that the industry’s AI challenge is moving beyond adoption towards fundamentally changing how wealth management firms operate, compete and generate growth.
Three blind spots identified
The research identifies three key blind spots that could prevent wealth management firms from converting AI investments into measurable business outcomes.
The first is an ambition blind spot, where firms recognise the need for transformation but continue to primarily fund AI initiatives for efficiency gains.
The second is an execution blind spot, where investments in technology are not matched by investments in proprietary client data and insights that can create competitive differentiation.
The third is a strategy blind spot, where firms track AI adoption but do not adequately measure its impact on growth, revenue and client value.
Growth outcomes remain under-measured
“The industry doesn’t have an investment problem. It has a choices problem,” HCLTech, Chief Growth Officer and Global Head of Financial Services, Srinivasan Seshadri, said.
“Nearly every wealth management firm is spending on AI. Far fewer can say which programs they are funding, how far AI actually reaches into the operating model, or whether they’re measuring the outcomes that matter, new client value, growth and revenue models,” he said.
Seshadri added that the research found 84% of leaders want a fundamental redesign, yet just 12% are measuring the new revenue that the redesign should produce.
Proprietary data emerges as key differentiator
The research indicates that wealth management firms view their proprietary client knowledge as an important source of future competitive advantage.
Executives ranked first-party and behavioural data as a more valuable differentiator than technology infrastructure, cloud platforms or AI partnerships.
Nearly 80% of respondents also believe future industry leaders will be those that effectively orchestrate AI, human expertise and ecosystem partners.
Regional readiness varies
The study found significant differences in confidence around AI-led transformation across regions. APAC recorded 89% confidence, followed by North America at 84%, while Europe stood at 38.3%.
HCLTech said the differences highlight varying levels of readiness and the pace of AI-led transformation across global wealth management markets.
AI combined with human expertise
The research was conducted in partnership with Evidenza and uses synthetic research to increase the scale and speed of industry analysis while retaining human oversight.
Industry practitioners, researchers and subject matter experts participated in persona design, research development and validation of findings.
“This study represents a new model for how we generate insights, one where AI gives us scale and speed while human expertise ensures every finding is credible and trustworthy,” HCLTech, Global Chief Marketing Officer, Jill Kouri, said.
She added that the study demonstrates the potential of combining AI with human expertise and reflects the kind of capability HCLTech intends to develop further in-house.
AI at scale with human judgement
HCLTech said the methodology reflects its broader approach of using AI at scale while retaining human judgement at critical points.
The company said the study demonstrates how AI-driven analysis can be combined with domain expertise to scale intelligence while maintaining trust, rigour and transparency.
The research concludes that long-term competitive advantage in wealth management may depend less on the volume of AI deployed and more on how effectively firms combine AI with proprietary client knowledge, human expertise and ecosystem partnerships.