At WealthTech 2026: US edition, attendees critiqued the sometimes over-optimistic view of artificial intelligence (AI) and other technological developments transforming the wealth management industry. At the April 29, 2026 event hosted at EY's US headquarters in New York, speakers wrestled with the gap between aspiration and implementation, with the qualities that build trust between vendors and wealth management firms, and what it means to build a durable operational model when last year’s roadmap is already obsolete.

Key takeaways from the day include:

• ‘Build vs. buy’ is over. The real question is who you partner with.
• Without foundational integration and governance, AI risks becoming just another silo.
• The advisor supply crisis is combining with the emergence of AI to redesign the wealth management operating model.
• Data is not the bottleneck. The real challenge is turning trapped information into client understanding and action.
• Innovation succeeds or fails less on technology than on organizational incentives, executive alignment, and tolerance for short-term pain.

Moving past ‘build vs. buy’

The traditional binary dilemma of building a solution in-house or buying an off-the-shelf product is outdated. Several panellists argued that it obscures the real strategic question: “Who has spent the 10,000 hours to solve a problem you cannot solve at all?”

Mark Ovaska, Co-Founder and Chief Executive Officer of Precept – which announced its acquisition by iAltA on the day of the event – said the “build vs buy” framing was problematic. “It frames the conversation in terms of the vendor proposition. It’s not a vendor proposition, it’s a partnership.”

In an environment where AI is accelerating both what can be built, and how quickly, the calculus behind the decision has changed, he added. But what has not changed is the value of accumulated domain knowledge: “When you have folks like us who have spent the 10,000 hours to understand a specific problem – and get to the place where they’re solving something that is impossible for you to solve in-house – there’s no AI prompt for that."

Michael Wood, CEO at Domify, refined this further. The old logic was: build when you have a proprietary advantage; buy when the solution is commoditized. “What do you do if you get no proprietary advantage and a solution doesn’t exist?” In that gap, deep domain expertise from a partner becomes the only viable option.

For vendors, the implication is that you cannot sell as a commodity provider. You must sell your specific, hard-won knowledge of a broken workflow. Conor Walsh, CEO and Co-Founder at Romina Day, argued that the problem with many deployments is ultimately not technological, but human. “Really these implementations get stuck with an uninspired champion managing the rollout – or somebody who feels it’s a threat, or that you’ve overpromised and underdelivered.”

Avoiding AI as a silo

Despite the explosion of agentic AI, a risk is that firms simply add it as another disconnected tool, repeating the fragmentation problems of the past decade.

“AI is almost becoming another silo,” warned Joseph Sullivan, Senior Director of Strategic Accounts at Backbase. “It should be an overlay of the stack, not another tool on the right side of the stack.” He told delegates AI is “not a magic wand” that can by itself transform their operations for the better; instead, firms need to “AI-ready” their technology stacks before plugging in intelligence layers.

Brian Filanowski, CEO at Docupace, echoed this in a fireside chat with TWM senior advisor Michael Partnow. He said technology solutions were proliferating rapidly – saying he’d reviewed hundreds of pitch decks from AI startups – but not all translated into functional products. “I’m concerned it’s creating a lot of noise. Some of our customers have gone to these startup AI firms, realized that there wasn’t much there, and come back to us. Now they’re stickier than ever.”

In another panel chaired by Alliant’s Head of Retirement & Wealth Amit Dogra, governr Founder Rajen Madan said there were three questions he asked each of his clients:

• What AI exists in your estate?
• Who is responsible for its decisions and outputs?
• Can you provide an audit trail in response to customer complaints or regulatory queries?

Most firms lack the answers to those questions, he said – not because they lack knowledge or intention, but because they lack the infrastructure to do so.

On the same panel, RISR founder Jason Early argued that the commoditization of AI will play out over a longer timeframe than many expect. “There is so much inertia in financial services – and the large firms move incredibly slow. There’s a lot at risk from a compliance and governance perspective. My sense is that it happens over a really long arc.”

Ian Karnell, CEO and Co-Founder of VastAdvisor, took a different view – arguing that AI changes not only products, but the economic lifecycle of startups themselves. “We have a quickly collapsing window of being able to drive human-led innovation in the marketplace,” he said. He argued that AI-driven execution speed compresses the time available for founders to establish durable defensibility before foundational capabilities themselves become commoditized. That, he said, should make startups think differently about timelines, scale, and exit strategies.

The “agentic diamond” replaces the pyramid

EY partner Justin Singer and Executive Director Patrick Clements provided a window into the future of the wealth management operating model – previewing a changing shape of organizations, and a shift in skillsets from portfolio construction to judgment, family governance, and behavioral coaching.

“Advice is becoming more important than ever. Human advisors are becoming less available than ever,” Singer said. The traditional advisor model cannot scale downward, he argued; the do-it-yourself model fails during complex life decisions.

Singer and Clements described a transition from “episodic advice” towards continuous, system-driven engagement. Rather than treating advice as something delivered during periodic reviews, or triggered by client outreach, they described emerging models where intelligent systems continuously monitor financial context and initiate engagement proactively. “Advice is no longer something you seek. It’s something that is continually delivered to you,” Singer said.

The shift has implications not only for technology architecture, but also for client expectations. Firms built around periodic interaction models may struggle to compete with platforms capable of persistent monitoring, personalized nudges, an real-time responsiveness.

Clements called the new organizational structure an “agentic diamond”, with supervising advisors at the top, a reduced back office below, and a growing middle layer of specialists, such as estate and tax planners.

“Historically, the industry has monetized scarcity of both information as well as products. Those things are kind of starting to go away,” he said. “The future of this industry is monetizing judgment and the actions that you take based on that judgment. Trust, speed, and connectedness are the moats that are actually going to persist going forward.”

Competitive advantage is shifting away from ownership and towards execution. In practical terms, that means firms increasingly compete on how quickly they can interpret client context, coordinate expertise, and act.

Unlocking trapped value

Based on his interactions with over 300 firms, Storyline Co-Founder & CEO David Navama said they by no means lacked data – in many cases, they were overwhelmed by it. The problem was that the value embedded in that data remained inaccessible because of how they communicated with their clients. “The value is trapped – the data is not trapped,” he said.

He identified the barriers as “complexity, communication style, information overload, time constraints, emotional barriers, and regulatory restrictions.” He called these, “the defining frictions that defend why and how we engage clients today – but more importantly, why and how we don’t.”

Navama challenged firms to stop thinking about “occasions” for better communication. He noted that one large bank was struggling to pursue US$1 trillion in untapped wallet share – not because of data gaps, but because they had exhausted email, research, and webinars without breaking through.

“All the oxygen in the room is taken up with the promise of AI,” he said. “But what about the follow-through on those promises?”

Storyline’s own solution is AI-driven personalization with interactive, real-time video communication. In doing that, he said they have been guided by a few key principles:

• Build infrastructure, not products: spend more time on strategic partnerships than on direct client sales.
• Create specialized solutions: focus on the specific data, compliance requirements, and use-cases of a client, rather than creating generic solutions.
• Offer configurable design: Storyline offers standard, compliant templates – such as for portfolio reviews – that firms can modify without drowning in technical debt.
• Be compliance-ready: Storyline treated compliance as a point of advocacy rather than an obstacle, solving problems compliance officers through were insoluble.
• Be intentional: the landscape is “deeply opportunistic and deeply unforgiving”. If you don’t know the problem you’re solving, you’re in trouble.

Take on short-term pain to avoid the slow death

Fidelity Labs’ VP Commercialization Patrick Hannon offered a set of examples of innovation failure as an object lesson. Naviplan, where he worked in 2012, knew it needed to move from on-premises to cloud delivery. It did not move fast enough: revenues halved in a matter of years, and the company reportedly sold for the price of its debt. The lesson: “If you realize that you need innovation in your organization, you have to be willing to take the short-term pain.”

He said that in many cases, the crucial factor is the quality of relationships between senior executives, as the only individuals with the authority to break existing processes.

He gave the example of the launch of Valley Stock Transfer. The business case for the launch was real, but the internal risk was significant – introducing a new product to relationship managers who already carried complex portfolios.

The unlock came from two senior executives agreeing to redesign compensation, support systems, and risk management frameworks to make the introduction viable for the people who would have to carry it. Without that executive-level alignment, the innovation the company needed would have stayed on paper.

Hannon compared corporate innovation to planting seeds. “You have to take a leap of faith,” he said. “I kill some seedlings every year. It happens. But you do it every year and you learn from that. You make adjustments every year.” Innovation requires accepting short-term failure as the price of long-term growth.

Building for the transition

Speakers at WealthTech 2026 argued time and again that the challenge facing wealth management is not simply identifying the possibilities of technology, but of building organizations that are capable of operationalizing them.

AI may accelerate execution, lower barriers to entry, and reshape client expectations – but it also exposes weaknesses in governance, integration, incentives, and leadership alignment. Firms that treat it as an isolated tool risk recreating their fragmentation problems. Those that succeed will be those that are willing to redesign workflows, rethink organizational structures, accept short-term disruption, and build partnerships grounded in domain expertise rather than procurement alone.

The transition is already underway; already, firms are being judged on how effectively they adapt to it.