Most firms acknowledge the need for an operating model reset, but few are building the capabilities to make it real
A new study of senior decision-makers across the global wealth management industry has found a clear disconnect between ambition and action: firms are investing heavily in artificial intelligence but overwhelmingly failing to measure or generate the new revenue they say AI should produce.
The findings are pointed. According to the report, 84 per cent of wealth management firms globally believe their operating models require fundamental redesign to fully capture AI's potential. But just over seven per cent are actively building agentic AI capabilities (tools that can act autonomously on behalf of clients or advisors) and only approximately 12 per cent are tracking whether AI efforts are generating new revenue. For an industry that has spent years talking up AI transformation, those numbers suggest execution remains a significant weak point.
Three blind spots slowing the industry
The study identifies three structural gaps it describes as critical blind spots. The first is an ambition gap: firms understand that transformation is necessary but continue directing AI budgets toward efficiency projects rather than business model change.
The second is a data gap: significant technology spending is not being matched by investment in the proprietary client data and insights that would create genuine competitive differentiation. The third is a measurement gap: firms are monitoring AI adoption rates but not the outcomes - client growth, revenue generation, new business models - that adoption is meant to produce.
"The industry doesn't have an investment problem. It has a choices problem," said Srinivasan Seshadri, Chief Growth Officer and Global Head of Financial Services at HCLTech. "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."
Wealth Professional has reported, the question of how AI is changing advice is already reshaping the conversation at the senior levels of the industry globally, with firms wrestling with where the technology adds durable value versus where it creates noise.
Data over technology
One finding likely to resonate with practitioners is the report's conclusion on competitive advantage. Executives surveyed ranked first-party and behavioural client data as a more valuable differentiator than technology infrastructure, cloud platforms, or AI partnerships. The message is that the tools themselves are increasingly commoditised; what firms do with their client knowledge is not.
Nearly 80 per cent of respondents in the study believe that future industry leaders will be firms that can effectively orchestrate AI, human expertise, and ecosystem partners together — rather than simply deploying more technology. That framing aligns with what many Canadian wealth management firms are grappling with as they navigate the challenge of integrating AI tools into existing advisory practices.
Regional variation is notable. The study found APAC markets (89 per cent) and North America (84 per cent) show the strongest confidence that human-AI orchestration will define future winners, while Europe lagged considerably at approximately 38 per cent. The report does not break out Canadian data separately, but North American results provide a relevant directional signal.
Methodology sets study apart
The research itself represents an unusual approach to market intelligence. Rather than conducting a conventional survey of human respondents, HCLTech and Evidenza built AI personas modelled on real wealth management executives, then surveyed those personas at scale. Subject matter experts - practitioners, researchers, and industry specialists - were involved throughout, both in designing the personas and in validating the findings.
HCLTech describes the process as consistent with the same AI-at-scale, human-judgment-at-critical-moments model the firm advocates to clients. It is also, the company acknowledges, a deliberate demonstration of what synthetic research can deliver: the speed and scale of AI, grounded by human expertise at each decision point.
As Canadian advisors and wealth management executives consider where to focus their own AI investments, the study's central argument is a useful benchmark. Building AI capability is only part of the challenge. Translating it into measurable client and business outcomes and knowing how to track the difference, id where most of the industry, according to this research, still has meaningful ground to cover.
For advisors curious about how generative AI is reshaping the Canadian wealth management landscape, the HCLTech study adds a global dimension to a conversation that is increasingly local. And for firms wondering whether they are ahead or behind, the numbers offer a sobering reality check: 84 per cent say transformation is necessary; fewer than one in ten have built the capabilities to execute it.
The full report is available via HCLTech's financial services resource page.
