Episode summary
Responsible AI and Automation in Wealth Management Planning Technology
Summary
Ken Lotocki argues that responsible AI in wealth management has to be verifiable, explainable, and accountable before it can be trusted for client-facing decisions. He warns against “shadow AI,” where advisors quietly use unsanctioned tools because they are convenient, and says firms need governance and guardrails before AI spreads beyond experimentation.
He also says the biggest workflow opportunity is not replacing planning engines with large language models, but connecting them properly. In his view, LLMs should handle context and communication, while Conquest’s deterministic calculation engine remains the source of truth. That is why he sees MCP as a way to let other tools access live plan data without sacrificing auditability or repeatability.
Lotocki says advisor adoption depends on preserving the advisor’s differentiator rather than commoditizing it. He describes Conquest’s approach as headless and adaptable, with transparent outputs and embedded governance designed to reduce friction, support automation, and help advisors look more competent and build stronger client relationships.
Key takeaways
- Ken Lotocki says AI in wealth management must be verifiable, explainable, and accountable before it can guide clients or compliance-sensitive decisions.
- He warns that “shadow AI” grows when employees use unsanctioned tools because they are easier, not because they are malicious.
- Lotocki says LLMs should provide context and communication, while a deterministic calculation engine should remain the source of truth.
- He says advisor adoption improves when technology protects the advisor’s differentiator instead of commoditizing judgment and relationships.
- Conquest’s headless strategy is aimed at making its calculation layer usable across agentic workflows without losing auditability.
Notable quotes
“responsible AI implementation, um, you know, cutting to the meat of it is really comes down to three things”
“Is the result that's generated from the LLM or or from the agent verifiable, explainable, and accountable”
“unsanctioned tools will thrive and without governance unsanctioned tools will be used”
“LLMs on their own are not a financial planning engine, and anyone who tries to LinkedIn sell you a prompt has no idea what they're talking about”
“we haven't deviated from our initial mission of trying to build headless, but headless has evolved from quick and and easy uh, integrations and connections to CRMs and all those too”
How the episode opens
Hi everyone and welcome to this wealth management fast chat. I'm Shannon Rosic, director of content solutions, and I'm so excited to be joined today by chief product officer of Conquest, Ken Lattaki, because we are coming hot off the heels of our CTO think tank that we just had at Wealth Management Edge. And I think one thing was very clear is that wealth management firms are no longer just experimenting with AI and digital transformation.
They are truly trying to operationalize it in a way that's responsible and scalable and actually useful for advisors. And Ken brings a front-row perspective on where planning tech is heading, how Conquest is thinking about integration and AI, and what it will take to make innovation practical inside of advisory firms. So, Ken, super excited to talk to you.
I want to dive right in.
Let's go. — Well, I one of the biggest themes that came out of the CTO think tank was that firms are really wanting to operationalize AI responsibly. So, from your perspective, what does responsible AI implementation actually look like inside of a firm?
Sure. So, I'm going to start with a quick imaginary story that shows irresponsible AI use. So, I see your New York Rangers jersey behind you.
So, so let's say the Rangers has announced a new team GM, a new direction they're going to build using cutting-edge AI. So, fans get their hope up, ESPN actually starts caring about hockey, then they finish in the bottom of the division. So, when people start asking questions, they start looking at it, turns out that the AI was a public LLM pointed at a third-party analytics platform, the same thing I use for my fantasy hockey pool.
Um so, what what's the issue there?
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- responsible ai
- automation governance
- shadow ai
- tech stack fragmentation
- agentic ai
Companies and tickers mentioned
- Conquest
Watch the episode
Watch “Responsible AI and Automation in Wealth Management Planning Technology” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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