An HCLTech study reveals that while virtually every wealth management leadership team is pursuing artificial intelligence, very few are currently developing systems capable of executing multi-step tasks with minimal human intervention. This highlights a noticeable disconnect between corporate AI ambitions and actual operational transformation.
AI Plans Outpace Agentic AI Development
According to HCLTech, 98% of wealth management leadership teams are actively advancing an AI strategy. Yet, just over 7% are developing agentic AI capabilities—tools designed to pursue an objective across a series of tasks rather than simply answering isolated prompts.
Furthermore, the study indicates that 84% of respondents feel their operating models require a complete overhaul to fully leverage AI. Despite this acknowledgment, fewer than 10% are actually prepared to make that shift, pointing to an industry that understands the magnitude of the task while remaining in the early phases of implementation.
Titled Hidden In Pl(AI)n Sight, the report was produced by HCLTech in collaboration with Evidenza. Together, they generated 1,066 synthetic AI personas that mirrored senior wealth management decision-makers across 17 markets, with industry practitioners, researchers, and subject matter experts assisting in the design and validation process.
HCLTech characterized this approach as synthetic research, noting that the statistics reflect outcomes from these modelled personas rather than traditional interviews conducted with 1,066 distinct executives.
Firms Focus on Efficiency While Revenue Goes Unmeasured
HCLTech highlighted three distinct gaps separating firms’ AI objectives from their commercial strategies. Companies frequently finance initiatives targeting operational efficiency even while acknowledging the necessity for systemic transformation, and technology spending often outpaces investments in proprietary client data and actionable insights.
The third disconnect lies in metrics. While firms routinely track AI adoption, they frequently fail to evaluate whether these projects actually generate revenue or enhance client value. For instance, although 84% support a comprehensive redesign of their operating frameworks, only 12% track the new revenue those transformations are intended to yield.
Srinivasan Seshadri, chief growth officer and global head of financial services at HCLTech, emphasized that institutions must exercise greater precision regarding the initiatives they finance and the outcomes they anticipate. “The industry doesn’t have an investment problem. It has a choice problem,” he remarked.
Additionally, executives indicated that direct insights gathered from clients and client behavior represent a more significant competitive advantage than cloud platforms, underlying tech infrastructure, or external AI partnerships. Meanwhile, nearly 80% anticipate that future industry leaders will successfully integrate AI with human expertise and third-party collaborators.
AI Readiness Varies Across Regions
Confidence in AI readiness and transformation varied geographically, with the Asia-Pacific region reporting the highest sentiment at 89%. North America trailed at 84%, while Europe registered 38.3%. However, the report clarified that these regional percentages do not quantify how many individual firms have actually deployed agentic AI.
HCLTech noted that the findings underscore an urgent need for organizations to align their AI budgets with daily operational updates and tangible performance metrics. The data outlines where these simulated decision-makers currently identify shortcomings, though it does not predict the speed at which firms will address them.
Ultimately, the research distinguishes between simply integrating software tools and fundamentally altering the underlying workflows. While HCLTech’s metrics demonstrate widespread enthusiasm for AI, the actual creation of agentic capabilities stays restricted.
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