In an industry where relationship managers are stretched thin and client expectations are rising, the most consequential question around AI may not be what the technology can do, but where it should be pointed first. For independent wealth managers and family offices in Hong Kong, the answer increasingly lies not in headline-grabbing innovation but in the unglamorous work of streamlining workflows, reclaiming adviser time, and serving the full depth of the client book with a consistency that was previously impossible at scale.

At the recent Hubbis Independent Wealth Management Forum in Hong Kong, Alexander Kearns, CEO and Co-Founder of DataDasher, offered a sharply focused perspective on how AI tools are delivering measurable impact in the advisory workflow. Speaking on the second panel of the day, Kearns drew on direct experience working with wealth managers and financial institutions across the region to make a case for disciplined, narrowly defined AI implementation over broad experimentation, and for treating the existing client book as the single most valuable growth asset a firm possesses.

Key Takeaways


Adviser Time Is the Scarcest Resource: The most effective AI deployments are those that give relationship managers back the hours lost to administrative work.
The Biggest Growth Opportunity Is Already In-House: Firms are underserving the lower tiers of their client books, creating a consolidation risk that technology can help address.
Define the Problem Before Selecting the Tool: Firms that fail to articulate what success looks like before implementation risk getting stuck in perpetual experimentation.
Pre- and Post-Meeting Workflows Are the Highest-Impact Starting Point: Compressing documentation and compliance work from hours to minutes delivers immediate, visible returns for front-line staff.
Regulatory Defensibility Is Built Into Good Design: Platforms that incorporate human oversight and audit trails by design will meet emerging regulatory expectations with minimal friction.

 

Adviser Time Does Not Scale

Kearns returned throughout the discussion to a principle that underpinned his entire argument: adviser time is finite, and it does not scale. Every hour a relationship manager spends on documentation, compliance paperwork, or meeting preparation is an hour not spent on client engagement, business development, or the kind of complex advisory work that drives revenue and retention.

“A lot of the best growth opportunities are actually within your existing book,” he said. The data supports the point. Kearns cited research indicating that 40 per cent of ultra-high-net-worth clients in Asia are already considering consolidating their assets into a primary advisory relationship. For firms whose relationship managers are spread too thin to engage their full book consistently, this represents both a risk and an opportunity.

“You’re not going to have people come to you and say, ‘Oh, I’m being underserved,'” Kearns warned. “They’re going to quietly consolidate assets elsewhere, and then you’re going to be on the receiving end of it. By the time you realise, it’s going to be a little bit too late.”

The Bottom of the Book Is Where the Upside Lives

Kearns was particularly forceful on the potential sitting in the lower tiers of a firm’s client base. Relationship managers naturally gravitate towards their largest and most active clients, leaving the bottom half of the book to receive, at best, quarterly attention. The assumption that these clients are less valuable, however, can be profoundly mistaken.

“Sometimes that bottom 50 per cent of the book is where a lot of those best opportunities are,” he said. “We’ve had a case where someone said the bottom 20 per cent of my book ended up becoming one of my biggest clients. Why? Because he consolidated assets to me and I wasn’t reaching out to them a lot.”

AI-powered engagement tools, Kearns argued, allow firms to maintain structured, consistent outreach across the full book without requiring additional headcount. The technology surfaces clients who may hold significant assets elsewhere and flags opportunities for consolidation that would otherwise go undetected.

“Don’t underestimate how many growth opportunities exist within those relationships that you have, because they’re already in-house,” he said.

Three Hours to Fifteen Minutes

When the panel’s chair challenged the speakers to explain how AI can be made appealing to front-line relationship managers, Kearns was direct. The pitch, he said, writes itself.

“Within the first two weeks of using our tool, you’re going to save a lot of time on the stuff that you hate doing the most,” he explained. “That administrative component, all the documentation, they abhor it. It’s monotonous. It’s wasting time from actually working with and talking to clients, building business.”

The numbers are striking. Kearns described how the pre- and post-meeting workflow, encompassing documentation, compliance records, and client communication summaries, can be compressed from approximately three hours to between ten and fifteen minutes using AI tools.

“Three hours that goes into pre- and post-meeting work turns into ten to fifteen minutes, and that’s music to their ears,” he said. “The moment they start using the platform, they just see how much it makes it exponentially faster.”

For firms struggling with adoption resistance, the implication is clear: start with the workflow that causes the most frustration, and the technology sells itself.

Define the Problem Before You Pick the Tool

Kearns was equally direct about a pattern he has observed across firms that struggle to move AI from pilot to production: they have not defined what success looks like before they begin.

“Don’t try to boil the whole ocean,” he advised. “When I’ve seen implementation or execution stall, or people just go around experimenting with a lot of things, they haven’t defined what success looks like.”

His recommendation was to break the advisory business into its component workflows, identify the specific problems that AI can address, and then evaluate tools against narrowly defined criteria. Different tools will deliver different types of value, and the metrics for success should reflect that.

“Make sure you quantify what success looks like,” he said. “You have to pick these different workflows, what specifically is it solving in the business? Because AI is very helpful in all different dimensions, but there’s different types of tools you’re going to pick for different types of problems.”

This discipline, Kearns argued, is what separates firms that achieve measurable impact from those that remain stuck in experimentation.

The Responsible Party Is Still You

While advocating strongly for AI adoption, Kearns was careful to frame the technology as an enhancer of human judgement rather than a replacement for it.

“You are still in the driver’s seat,” he said. “When we use AI for research, we should be looking for it to go into trusted data sources, looking for it to help enhance analysis. How are we extracting more information than would have been humanly possible?”

The point extended to the regulatory dimension. Kearns noted that the Monetary Authority of Singapore had released guidelines at the end of 2025 for operational AI tools, with the emphasis on human-in-the-loop processes and defensible decision-making frameworks. He suggested the SFC in Hong Kong is likely to take a similar approach.

“If you have a defensible process with AI and you’re picking purposeful platforms that have also thought about compliance in mind, it’ll be much more defensible,” he said. “Singapore seems like they do want people to use AI. You just want to make sure you have a defensible process.”

Someone Using AI Will Take Your Job

Kearns closed with a formulation that captured the consensus of the panel and drew a clear line under the discussion.

“It’s not AI that’s going to take your job,” he said. “It’s someone using AI who’s going to take your job.”

The statement crystallises the competitive reality facing Hong Kong’s independent wealth management community in 2026. The technology itself is increasingly commoditised. What distinguishes the firms that will thrive from those that will fall behind is not access to AI, but the discipline with which they deploy it: choosing the right workflows, defining measurable outcomes, maintaining human oversight, and above all, ensuring that every hour reclaimed from administrative friction is redirected towards the client relationships and advisory judgement that remain the industry’s irreplaceable core.