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AI Shifts Advisor Time From Administration To Client Relationships
Editorial Staff
14 October 2026
The following article comes ahead of a forthcoming report, by the publisher of this news service, about the specific ways that AI affects the wealth management value chain, its processes, applications and use cases. Kevin Teng, the chief executive of Asia-based WRISE Private Singapore, discusses how reducing routine work can create more capacity for client engagement. He talked to this publication in a recent interview. This article is part of conversations in a research report this news organisation is producing in partnership with . Arta Finance is an AI-driven wealth and fintech firm headquartered in Silicon Valley and Singapore. Its rapid ascent reflects how technology is reshaping the wealth management sector worldwide. For Kevin Teng, the practical value of AI in wealth management is tied closely to how advisors spend their time. This article is part of a series drawing on interviews for the AI in Wealth Management Research Report, produced in partnership with Arta Finance and due for publication in Q4 2026. The report will bring together survey findings and further interview insights. Professionals working in private banking and wealth management are invited to contribute their views by completing the survey.
In responses for WealthBriefing’s forthcoming AI in Wealth Management Research Report, Teng said the firm had embedded AI into its operations, including proprietary tools supporting investment research, portfolio analysis and client reporting.
The most tangible impact, he said, has been greater productivity in administrative work such as data consolidation and report generation. Teng said the time released had been reallocated to deeper client engagement and more informed advice.
“Removing the administrative burden saves time, and frees our advisors to focus on tasks requiring human judgment, establishment of relationships and complex planning,” Teng said.
That places advisor capacity and the client experience at the centre of WRISE’s approach. Teng said AI helps advisors prepare more personalised advice, while understanding a client’s financial needs and providing counsel on complex matters continue to depend on human judgment.
The connection between a tool and an advisor’s daily work is critical. In Teng’s view, adoption is strongest when AI is embedded in existing workflows. A separate system that employees must learn and manage can create additional demands; a tool that brings together relevant information or removes repetitive work gives them a clearer reason to use it.
“AI should be used to remove friction, improve productivity and ultimately give advisors more time to focus on clients and the business,” he said.
He also described implementation as a continuous process. Feedback from employees helps identify where a tool is useful, where it needs improvement and how it can support their work more effectively. Deployment is therefore followed by refinement, rather than treated as the end of the exercise.
Teng’s account suggests that the test of an AI initiative extends beyond its technical capabilities. For WRISE, its usefulness depends on whether it fits the work advisors already do and creates capacity for the parts of the relationship that require their expertise.
That does not shift responsibility for advice to a model. Teng said advisors remain accountable for the advice and decisions they provide, with validation and human oversight necessary where AI-generated information could influence financial decisions.
The experience offers a practical starting point for the wider research: when routine work becomes faster, what changes for the client? The forthcoming report will examine how institutions translate AI capabilities into service improvements, alongside the barriers they encounter in moving beyond experimentation.