An interview with Danny Lohrfink, co-founder and Chief Product Officer, Wealth.com
Artificial intelligence has a lot of buzz across wealth management. Where are you seeing real tangible adoption today versus hype?
Real adoption is here. Advisors have process-heavy, document-heavy workflows. Take estate planning, tax planning, account opening, client meetings. These are things that are very process intensive. You’re taking what used to be manual, tedious and repetitive processes, and you’re breaking them down—not to replace the financial advisor—but to eliminate the manual work using AI that keeps the financial advisor from doing what they’re actually good at.
How should advisors think about integrating AI into their existing workflows without disrupting client relationships or trust?
Start with the back office, not necessarily the client meetings or even the client deliverables. The best AI implementations are often invisible to the end client. They are there to make the advisor faster, more accurate, and better prepared. If you think about the Wealth.com use case, an advisor is walking into a meeting after already having reviewed the client’s entire tax package and estate plan, because AI did the heavy lifting. The client doesn’t know or care how the analysis happened, yet they are experiencing a more dynamic, better prepared advisor. The AI is making the advisor look smarter but is not replacing the dialogue the advisor has with the client.
Dynasty recently announced a partnership with Wealth.com to embed your Esther AI into their platform. Is that the future as you see it? Are you seeing similar interest from other firms?
Absolutely. The future of AI and technological advancement within wealth management is embedded, not bolted on. Advisors don’t want another login. They want AI to be infused inside the tools that they already use. Advisors want to be able to click on a data point on their desktop and see the source and be able to trace the backend calculations to see how the answer was derived. We are seeing significant interest from other firms that want to do the same thing, and we already have many signed contracts with folks that have not gone public with PR announcements. Nonetheless firms are taking huge steps right now to create a central ecosystem for their advisors to engage with and then are choosing their vendors based off of how the vendor is adopting and adapting to this new AI environment.
We’re seeing a few different flavors, categories, types of AI emerge in advisor workflows from notetakers to chat-based tools and now a shift toward more embedded AI that sits between the advisor and their traditional tech stack. What are you seeing across firms and where do you think this is headed?
The progression that you’re describing is spot on. We went from the novelty, as I’d call it, of the chatbots and notetakers, but they were just the first step. The next phase is actually AI that understands the full context of the client relationship. While the client conversation from the notetaker is one piece of the puzzle, you must then infuse that with the legal structure of their estate plan, with their tax circumstances, with their actual balance sheet, all their meaningful data so that you can understand how it all connects. So, taking the conversation from the notetaker, understanding that the client has charitable giving intentions, then marrying that with the client’s balance sheet, with their existing estate structure and evaluating on top of it the tax implications. That is how you achieve a full 360-degree view.
Can you provide a few more details or examples that reflect how you think AI will enhance the role of the financial advisor rather than replace them?
Both tax planning and estate planning present perfect examples—no financial advisor wants to read through a dense, 100-page trust document, but they all want to understand its ramifications for the financial plan they spend so much time on with the client. So, this is not replacing the advisor, it’s making them more impactful because they are able to easily integrate the totality of the client’s wealth circumstances into their offering.
If you think about tax-planning advisors, they are always thinking about how the investment management, and the financial planning side of the house will impact the client’s tax circumstances. Or if we sell this stock, are we introducing capital gains? Is it pushing the client into AMT? Should we do a Roth conversion? What if we do a DAF versus a QCD? These are all considerations that the advisor wants to be able to run an analysis on, but historically, this was either done manually in Excel, or you were using a separate, dedicated software tool to do it, and those tools were only as good as the code it was written in.
What AI allows the advisor to do is to run cross-strategy analysis that evaluates the impact of each individual tax strategy, charitable giving, Roth conversion, or equity compensation model, and do so not in isolation, but in unison to understand the impact of a cross-strategy approach. And the AI is able to tie that back to the estate planning implications, to the asset allocation implications, etc.
In short, AI enhances the role of the advisor, making them much more efficient for every single client meeting, not just the meeting for their A-level clients, but all their clients.
We’re seeing pretty much every level of advisory firm interested in AI these days, but it can be especially complex for enterprise firms to adopt. What should enterprise firms consider when evaluating AI vendors or building out internal AI capabilities?
Three things. First, domain specificity—generic AI is not good enough for wealth management. You need models that understand trusts, estate structures, and financial planning concepts.
Second, data architecture—can the AI output structured, actionable data that integrates with your existing systems, or does it just generate text? At Wealth.com, Ester doesn’t just summarize documents, it creates structured contact cards, maps roles and relationships, and feeds that data directly into the advisor’s workflow.
Third, governance and accuracy—can you verify what the AI produced? Firms should demand transparency into how AI reaches its outputs, not just trust a black box.
Looking ahead three to five years, how do you see AI reshaping the advisor-client experience?
The advisor that serves 80 households today will in the future serve 200 households with the same or better quality. AI will handle the data gathering, the document analysis, and the ongoing monitoring that today takes up a lot of the advisor’s time.
The client experience is going to feel much more proactive; client touches will be more frequent and automated rather than only on a quarterly or biannual or annual review basis. And for the end client, that feels much more settling because the number one thing that clients look for from an advisor is not great returns, but regular communication. Advisors will get to focus on strategy, being a true relationship manager, what most advisors have always wanted to be, mixing the quantitative with the emotional and behavioral elements of financial planning.
