In this episode of Zephyr’s Adjusted for Risk podcast, host Ryan Nauman welcomes Mohan Gurupackiam, CIO at Steward Partners, to discuss how wealth management’s view of AI has shifted from curiosity and pilots to operationalization with governance and safe scaling. Mohan explains how firms are using AI as part of an advisor’s daily operating system—supporting meeting prep and automation, opportunity identification, communications, and eliminating non-value work—while noting investment research adoption remains limited due to trust. They cover key obstacles including data foundations, regulatory uncertainty, behavioral resistance and change management, legacy architecture, and talent gaps. Mohan emphasizes keeping humans in the loop, starting small with clear ROI, and combating advisor tech fatigue. He closes with three strategic advantages: unified data and context, productivity economics, and end-to-end automation.

Learn more about Zephyr here.

Learn more about Steward Partners here.

00:00 Welcome to the Podcast

01:11 Meet Mohan Gurupackiam

02:05 Steward Partners Overview

04:30 AI Mindset Shift

07:03 AI in Advisor Workflows

09:57 Human First AI Strategy

13:44 Implementation Roadblocks

19:17 Where AI Delivers Impact

24:53 Getting Started with AI

27:47 Tech Stack Fatigue

30:54 Winning in a Commoditized World

32:57 Wrap Up and Resources

Connect with Ryan Nauman:

LinkedIn

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video1742168322: Hello everyone, and

welcome to Zephyr's Adjusted for Risk

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podcast from the shores of Lake Tahoe.

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I'm Ryan Nauman, the market

strategist here at Zephyr.

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Over the past couple of years,

the wealth management space

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has been grappling with AI.

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First, it was understanding what AI is.

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Now, it is all about how to implement it

to help enhance the advisor experience.

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Well, I have on an industry expert

who's going to share his thoughts

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on the impact AI is having on wealth

management and the opportunities that

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AI presents to financial advisors.

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But first, today's episode is sponsored

by the award-winning Zephyr, which

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helps investment professionals

make more informed investment

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decisions on behalf of their clients.

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All right, enough from me.

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I have already talked enough.

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Let's go ahead and move on to the

star of the show I'd like to give a

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very warm welcome to Mohan Gurpakiam.

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Mohan is the Chief Information

Officer at Steward Partners.

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Mohan, thank you so much for

coming on the show again.

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You were on the show, we were

live at the Edge Conference the

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last time you were on the show.

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We had a fantastic conversation, so

I'm really looking forward to this one.

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A lot has changed in a year, so

there's a lot to, uh, discuss.

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So thank you.

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It's an honor to have you back on.

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Can you please tell us a little bit more

about yourself and Steward Partners?

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Absolutely.

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So Ryan, first of all, thank you

for having me back on this channel.

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I greatly enjoyed our conversation

last year when we met in Boca.

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Uh, what a terrible place.

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But here we are again to talk

about a very timely topic.

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Let me start off with Steward Partners.

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Steward Partners is an employee-owned

full service independent partnership.

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We cater to family, institutional,

multi-generational investors.

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Our partners specialize in comprehensive

wealth planning, investment strategy,

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and professional asset management.

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Uh, we serve in a, a large clientele.

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We pride ourselves on delivering,

you know, personalized service

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with commitment to excellence.

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We operate in more than 30 states and

roughly around 90 different offices.

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So that's who Steward Partners is.

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Um, a- about me, I've been…

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My name is Mohan Gurpakiam.

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I've been in the industry

for close to 30 years.

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My experience spans all the way

from direct to consumer, you know,

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uh, wealth management at scale.

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I worked at E-Trade for a long time.

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I also understand the independent

broker-dealer business where I

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was the, uh, chief technology

officer at Cetera Financial.

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And then I ran both management at

AssetMark, and I've been with, uh,

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Steward Partners for the last three and

a half years as our chief information

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officer, and it's a fantastic place.

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I cannot say enough

about Steward Partners.

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But that's me.

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Uh, you know, I'm aging myself,

but, uh, three, um, close to

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three decades in the industry.

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I've seen several reincarnations of

this industry and, um, and we're seeing

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one in, in, uh, real life right now

as we, as we are watching through it.

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Yeah.

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Mohan, that's fantastic, and I have

had the privilege of speaking with

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a few other folks at, from Stewart

Partners, from, uh, Jim Gold and Jeff.

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Great team.

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A lot of great people at Stewart Partners.

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It's always a pleasure speaking with them.

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I've always enjoyed it.

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And you are exactly right on

the AI side, technology side.

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It's amazing how the space has evolved so

quickly and just over the past few years

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and just, uh, I think it, it's moving so

quickly, and we talked about it last week.

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Like, just there, there's still so much

uncertainty, and I think a lot of it has

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to do with just how quickly technology

is evolving and changing the space.

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It adds uncertainty and, and just adds

more plate to the financial advisor, and

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we're gonna get on into that shortly.

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But, you know, the people in the wealth

management space have now had a couple

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of years to digest what AI really

means for the wealth management space.

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Do you feel there's been a transition

here on how wealth management firms

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and more specifically financial

advisors view and think about

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AI from last year to this year?

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Have we shifted in our mindset?

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I, I would, I would say yes.

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There has been a clear and, uh, I would

say a measurable shift from, I would

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say, over the last 18, 24 months, right?

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I think 24, two- 2024 and 2025, there

was more of, I would say, curiosity

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c- you know, along with skepticism.

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I would say we were more, more in the

experimentation phase, or people were,

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you know, uh, using isolated use cases.

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Oh, should I use it for meeting summaries?

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Uh, there was also a lot of hesitation

from, uh, compliance, right?

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Because the regulations usually

catch up with advances in technology,

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especially when technology is

advancing at a much faster pace.

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And there was minimal

integration into core workflows.

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Uh, fast forward 18 months, 24

months, when I speak to a lot of

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our industry peers, um, I think they

have gone from this curiosity phase.

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You know, they have moved away from

the question of, is AI useful, to

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more like, how can I scale it safely?

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Right.

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It is about an acceptance, it's

about operationalization, and

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more importantly, it's a strategic

priority for a lot of organizations.

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There is a mindset gap.

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People have moved away from pilots

to production, uh, to a strategic,

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um, I would say, v-view of AI, and

the governance is also catching up.

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So at all fronts, the answer is

yes, clear and measurable shift from

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last year to this year, I would say.

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Yeah, I completely agree, and just a

mindset and people, I think, are realizing

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they understand what is, and just now

it's like, okay, it can really help us,

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whether it's just a AI agent chatbot

to now making more efficient workflow.

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And, and the firms out there, technology

for AI firms are just helping, you know,

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give financial advisors more options

on implementation and how to do it.

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So how-- speaking of that and the

people that you talk to, your, um,

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colleagues, whether it's at Steward

or maybe just, um, other people in the

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industry, how are firms implementing

AI to enhance that advisor experience?

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Is it just mostly on the, you know,

chatbot support, or are they getting

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more on the operational side?

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I would say that would have been the

case, like, uh, like 18 months ago.

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But I, if, if I walk into a room today,

and, uh, I would say that advisors

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are actually looking at AI as part

of their daily operating system.

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And, uh, the, the best example

I would give is, you know,

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using something like, say, um,

Microsoft Word and Microsoft Excel.

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I think AI is going to be

something similar to that.

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It's core part of your, core

part of your operating system.

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And what I have heard from a lot of our

peers and our partners within Steward,

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uh, we use our-- uh, I would say not we.

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The advisors are using AI as part of

their operating system, and it varies

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all the way from meeting prep, meeting

automation, things like tasking.

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This is a, something-- This is a function

I would say the advisors spend a lot

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of time on, almost on a daily basis.

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There are also, I would say, you know,

two or three other big use cases.

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Uh, opportunity identification, whether

it's, you know, uh, new life events,

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additional products, tax strategies.

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So that is a, another place where

AI is being used extensively.

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Uh, communication and content.

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Uh, this is actually become a lot more

commonplace, extensive use of AI for

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drafting emails or adjusting the tone.

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And we have also seen automation

of, uh, non-value work.

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Uh, I want to move my file that comes

in via email into a file repository.

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That's a good example.

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So these are like use cases we are already

seeing being used quite extensively in a,

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across this, in a wealth management space,

irrespective of the size of the practice.

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Mm-hmm.

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No, those are great examples, and I just-

Feel, Mohan, that we're just on the tip

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of the iceberg right now on different ways

AI is gonna be used in advisory practices.

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And you brought up a very good point, too,

about if-- We all know wealth management

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is a very highly regulated industry.

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Like, wha-how is, you know, regulatory

comp-uh, compliance gonna handle AI, too?

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Especially when we start doing

more with AI and investment

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management and recommendations.

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Like, that I feel as if we're still

haven't even really reached yet.

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Is that correct?

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That is correct, yeah.

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Yeah.

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Do you think some firms are missing

the point or missing the most important

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aspect of AI when trying to implement it?

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Maybe they're just focusing too much on

communication part or, you know, reading

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maybe, uh, the output of a deliverable

and putting it into summary notes.

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Or do you think their advisories

and firms are missing the point?

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Or, and really, what is the

most important aspect of AI?

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I, I think it is a very--

it's a fantastic question.

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First of all, it's, uh, you know,

the, the industry is a very h-human

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touch, high touch industry, right?

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And I think this is one of the

most underrated and under-discussed

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dynamics right now, right?

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I think the m-most important question

you gotta ask is, what is the

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advisor's role in a AI world, right?

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AI is not going to replace advisor, right?

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I think that is the

biggest misunderstanding.

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You have to still put the, uh, the

human in the loop, human in the middle

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kind of a, you know, architecture,

business architecture when you

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start off with implementing or

thinking of implementing AI, right?

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That I would say is something that

most of the firms actually do not think

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of putting the human first when you

develop a AI-based operating system.

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So that's number one in my mind.

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The second thing that people do

is ignore the data foundation.

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Problem.

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I, I always try to use a simple analogy.

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Using a AI, uh, to build an

operating system is like building

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the twentieth floor in a building.

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You can't build the

twentieth floor straight up.

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You gotta build nineteen floors

underneath to basically get the

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twentieth floor up and running, right?

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So ignore the data foundation problem.

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I think that's a big issue, you

know, whether it's fragmentation,

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especially the disconnected tools.

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And there is a lot of unstructured data.

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You know, take CRM, for example.

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It's highly unstructured data, right?

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And the third thing that-- This

is actually a very common mistake.

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When I talk to people and they say

like, "Hey, do you have a AI strategy?"

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A lot of times they talk

about bolt-on AI, right?

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That is not really a AI strategy, right?

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Um, I would say the industry has to

move away from using bolt-on AI to,

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how can I transform my core workflows?

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Introducing a tool is

be-- it becomes a novelty.

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Is it a real productivity multiplier?

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That is a question that,

you know, firms have to ask.

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What is going to become a productivity

multiplier when I introduce AI, right?

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That's a good question to ask, but

also the more important one is,

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put a human in the middle, right?

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Ask, ask the question, how is AI

going to supplement the human in

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the middle?

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Yeah, Mohan, that is such a good point.

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And going back to, you know,

your, uh, comments regarding

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that, you're exactly right.

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AI is not gonna replace the advisor.

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It's gonna, like you said, supplement

the advisor and help the advisor, I feel.

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But-- And I also love that you brought

up, you know, we often talk in this

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industry, we always wanna get to the

20th floor or wherever really quickly.

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We often forget about the planning

and how important planning is in that

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foundation of building something.

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You need to build the foundation of

a house first before you can, you

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know, start building the kitchen.

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So w- are there other obstacles?

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You mentioned data, how important data is.

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Are there other obstacles to implementing

AI you're coming across when firms wanna

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implement AI, but they're, you know…

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Or they have, but they missed a

step, such as building a foundation?

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I think first of all, you

know, data is the place.

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You know, people always

miss that step, right?

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Especially when you walk into complex

practices, you have to aggregate

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data across so many sources.

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Not just custodian, but also across

your direct business, insurance,

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annuities, you name it, right?

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And being able to get all this data,

have, uh, proper classification,

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taxonomy, that's important, and usually

takes a long, long time and quite a

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bit of engineering effort in that.

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But that's not the only

impediment that I could think of.

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The other one that I would say is

the risk and regulatory uncertainty.

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Like, regulations usually, you know, are

catching up to reality, especially when

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the technology is advancing so fast.

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The, um, the average time for

a, a LLM model to be, I would

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say, uh, replaced with a newer

version is four months, right?

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So there is, uh, you know, think about

like, you know, when, um, you know, Int-

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Intel CEO said, "Oh, the processing power

is going to increase every 18 months."

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We are talking about four months.

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It's, it's a very highly compressed,

you know, changing environment.

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So risk and regulatory uncertainty,

if you don't have clarity, most of

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the firms are going to resort to the

most conservative approach, which

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allows for, uh, not a whole lot of

experimentation, so to say, right?

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So that's, I think, also

a big, uh, obstacle.

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The other one that is- We, we don't

really think about it that deeply.

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It's about advisor trust and, more

importantly, behavioral resistance, the

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change management aspect of a practice.

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Most of the advisors, their offices,

they have built-- they have perfected an

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operating system that meets their needs

over the last fifteen, twenty years.

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That change management

is going to be difficult.

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It has to be measured.

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It, it requires coaching.

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Uh, so that is actually another

impediment that I have seen.

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Uh, the other one is something that

we have seen especially with larger

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established firms which actually

have legacy architecture, right?

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And this is an interesting one because

we see medium-sized firms that are in the

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sweet spot between, like, they have newer

architecture, they can move faster, move

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things, push things a lot faster, right?

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So the legacy architecture and the

integration debt is an impediment, right?

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Especially when we are talking

about, um, implementing an, you

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know, a, an organization-wide core

operating system that's AI native.

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That becomes a bigger challenge.

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And last but not the least,

talent and change management gap.

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Uh, technology guys, we struggle.

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I cannot go to the, you know, market right

now to find, you know, prompt engineers.

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There are very few.

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Forget about prompt engineers.

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Try getting a, a, uh, training program,

right, for your, for your organization.

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There is very little, you

know, uh, talent actually.

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The talent usually takes a lot

of time to catch up, right?

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And I think that is another area

where we are all struggling.

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As technology leaders, we struggle

to find the right, um, talent to

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basically meet our immediate needs.

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I think two years from now, it'll be

a different situation, but right now,

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we are in a place where the demand

far outstrips supply at this point.

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Yeah, Mohan, those are great points.

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And going back, I love

that you brought up trust.

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As we know, this industry

really is built on trust.

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If you have the trust of your

clients as a financial advisor,

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you can be very successful.

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I-- when I use AI for research,

I'll be honest with you, I

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still don't trust some of it.

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I will end up, I end up spending more

time double-checking the numbers, the

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returns, the analytics that AI produces,

you know, gives me from a prompt.

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I'll go research and then it's like,

"I should have just done this on my

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own," because it took me more time.

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Uh, and ninety-nine point

nine percent of the time, the

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AI-generated response was correct.

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But there it is.

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It's all about trust.

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I, I'm still trying to trust it

when I create, um, you know, prompt

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it for some research and so on.

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And with that being said too, and going

back to your education, I do use AI

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quite a bit, but it's am I asking it the

right prompt or am I being clear enough?

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'Cause I don't know.

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I, I'll do…

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And I always ask please and

thank you and all that stuff

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like I'm talking to somebody.

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I probably don't need to, but we

do it, and it, it's those things

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that, yes, we need more training

because I'm sure my prompts could

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get better, and then the trust.

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I'm so glad you brought those up

But, um, you know, where can AI

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have the biggest impact within

a wealth management practice?

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You know, as our viewers know, you know,

I focus more on the investment management.

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I would love it if we had an AI tool

that, uh, said, "Create an optimized

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portfolio that gives me the largest

sharp ratio across these asset classes.

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Include all these asset classes,

produces a efficient frontier."

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Boom.

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That's how I think.

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But are there other, you know, areas

within the wealth management practice

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that can have the biggest impact?

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You know, we talked about chat,

um, you know, the chatbot.

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Is there anything else there

that you're thinking of?

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Absolutely.

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So first of all, I want to start

off with the, the one that you

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brought up, investment, um, you

know, research, investment prep.

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Unfortunately, that's not an

area where, you know, there

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is not widespread adoption.

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Even among advisors who use AI

extensively, only 7% of them use

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it for the, um, investment research

and portfolio construction.

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Part of it is actually ha- I think it

has to do with the, the trust factor, and

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it, it, it's going to take time, right?

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But coming back to biggest impact

in terms of, uh, within and with

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management practice, I would say the

first one we should start off with

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is advisor productivity and capacity.

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There are a couple of reasons.

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Number one, um, that's time,

you know, I would say, that's

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spent almost on a daily basis.

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The most amount of time spent

by an advisor is around, you

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know, things like meeting prep,

meeting the clients, automated

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com-compliance, call to actions, right?

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Um, and it-- this is also

about, you know, the capacity.

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You know, there's a well-established

study by McKinsey that says, "Oh, in

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the next ten years, we are gonna have

100,000 advisors shortage," which is true.

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We don't see a lot of, uh,

fresh, I would say, supply of

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labor coming into the industry.

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So I think AI is probably going to

address a good chunk of, I would

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say, the shortfall that you expect.

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I don't think it'll be uncommon

to see, you know, a billion or $2

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billion advisor practices in the

future because AI could automate a

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lot of the low-value work, right?

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Um, there are a couple of

other areas, I would say.

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Uh, client engagement,

uh, proactive advice.

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Um, one of the things that when I talk

to advisors, they always talk about

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what they call their morning routine.

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They're like, "Oh, I come in, walk into

the office, get my cup of joe, and I do

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the same thing, which is I go try and

pull 10 reports to figure out what are

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the five things I need to focus on, and

that's going to take me two hours," right?

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So it's interesting, the advisors

basically spend the first two hours

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trying to figure out what they're gonna

work on for the next two hours, right?

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So one of the things the advisors

have said is like, "We want

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event-triggered," I would say,

"notification or advice from the system."

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Right.

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Um, they expect when they walk in,

there is a screen that says, "Hey,

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ten accounts received cash yesterday.

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Do something about it.

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Uh, five accounts submitted

their account paperwork.

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Three of them are not in good order."

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Right?

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Or like, oh, there is like, you

know, cash that came into IRA account

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which requires a rollover, right?

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And I think that is an example of

like, you know, where advisors want

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event-triggered advice or, you know,

they want a notification saying,

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"By the way, that client is hitting

the age limit for RMD," right?

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So this is a good example.

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If I wa- you know, en- envision how

the, you know, advisor screen is going

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to look like in the next few years.

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You're gonna walk in, there's gonna be

like ten agents, and these ten agents

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are basically gonna say, "Hey, these

are the things you need to do", which

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is probably going to automate a good

eighty percent, ninety percent of all of

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your notifications and actions, right?

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The other area that is not, you

know, uh, discussed very widely

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is around workflow automation.

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One of the bigger, I would say, complaints

if you ask the advisors is a friction

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between the advisor's practice and

the operational back offices, right?

370

Reducing the operational burden,

re-reducing the cost to serve is mutually

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beneficial for both the advisors and

firms like us because it reduces the

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friction or eliminates the friction

and improves productivity vastly.

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So these are, I would say, three

areas where you can have a really

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big impact for the advisor's

practice on a day-to-day, uh, basis.

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Yeah, I agree.

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I can't wait for when I come in

because you-- It, it hits home when

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you said it takes basically two

hours of me to plan what I'm gonna

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be doing for the next two hours.

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That's exactly what I do.

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I wake up, sit here, and it's

like, "Okay, what am I gonna do?"

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You know?

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It's like two hours later, it's

like, "Oh, I finally figured it out."

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Um, just there's only so

much time in the day, Mohan.

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So if we can leverage AI to make it

more efficient, it helps everyone.

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So, you know, can you-- all our

listeners out there, the financial

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advisors who are still uncertain about

AI and the implementation, like we

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said at the be- it's moving so quickly.

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Y-your head is spinning, analysis.

389

Y-you, you don't know where to start.

390

You know you need to do

it, you just don't know…

391

Can you provide some tips to financial

advisors who are still uncertain?

392

They want to, just don't

know where to get started.

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Um, a good example I would

use is think of an AI-based

394

operating system as a large pizza.

395

You're gonna eat one

slice at a time, right?

396

You have to always start small.

397

If you try to think of like, oh, how

would AI change my practice en-entirely?

398

Uh, well, it's going to take you like

eight, 12 months to figure that out.

399

The industry would have moved on, right?

400

Um, the best advice I would tell

is, you know, start small Identify

401

a good return on investment.

402

Ask the very simple question,

where am I losing time every day?

403

Right?

404

Rather than trying to bolt on something.

405

You know, and that changes or that

differs from practice to practice, right?

406

If you are, um, probably in a practice

that has fewer number of large

407

clients, your needs might be very

different from a practice that have

408

larger number of small clients, right?

409

It's, it's where you spend time

depends on what your practice is.

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When they-- when we say you talk to one

advisor, you talk to one advisor, right?

411

Every advisor is unique.

412

So I think that's the

best advice I would say.

413

You know, start small, identify

a good return on investment.

414

You know, solve the problem, take the win.

415

You know, start thinking about how

would AI change my next few hours of

416

my time, versus start thinking about,

oh, how is it going to change the

417

entire wealth management practice.

418

You cannot control what you cannot

control, but you can control the ones that

419

are in your immediate sphere of, I would

say, control, which is, hey, what can I…

420

You know, where can I save time today?

421

Like, what are the activities I can

now, you know, uh, automate, right?

422

That's the, that's the way I would

think about, um, implementing AI.

423

That is such a great point, because I

think it can be overwhelming to some.

424

And like you said, don't try and chew

off more than that piece of pizza.

425

Just take one slice at a time.

426

No reason to, you know, try and

revamp your whole practice right away.

427

And I love that advice there, Mohan.

428

That's really good.

429

Just focus on one piece at a time.

430

Where are you spending more

time than what you should?

431

Can you make that process more efficient?

432

Great, great thoughts there.

433

Do you think there is some advisor

fatigue when it comes to technology?

434

We've been talking about technology

for years, how it's evolved,

435

all the different tech stacks,

how important a tech stack is.

436

Do you think there's

some fatigue going on?

437

Hundred percent, right.

438

I think it's a…

439

Advisor technology fatigue

is very real right now.

440

I would go to Kitces', um, you know,

fintech roadmap Like 10 years ago, I

441

could have printed it on an A4 size paper.

442

Now, if I want to print the, the,

in a fintech, uh, ecosystem, I have

443

to go to Kinko's and print it out

on a, you know, huge plotter, right?

444

There has been an explosion in

terms of the fintech products.

445

A lot of those were, you know,

came in along with the evolution

446

of cloud-based services, which

is the dominant model right now.

447

It lowered the entry barrier

significantly, which is fantastic.

448

Lot of great ideas have come to fruition.

449

But the system, the ecosystem

is just exploding, right?

450

I think, um, we call it the tool

overload or the stacks sprawl, right?

451

It just, you know, uh, like five

years ago, or even like 10 years

452

ago, I could fit my tech stack

on, like, a single page of paper

453

and say, "This is what I support."

454

Now, it's like multiple

sheets of paper, right?

455

So I think that is a real problem, right?

456

And I think, well, the other thing

that is also something you have

457

to consider is a constant change,

sometimes with questionable payoff.

458

You know, what- We have to factor in,

uh, heavily into this conversation

459

is the learning curve for the

advisors, their practices, right?

460

The lowest level of every

organization needs to be familiar

461

with any platform that we bring in.

462

The disruption it causes

to existing practices.

463

And a lot of times it's

a limited benefits.

464

When, when the systems and the

tools have been exploring, the

465

marginal increase in benefits

becomes smaller and smaller, right?

466

And it raises a question in the

minds of the advisor, right?

467

Is it worth that change when the

marginal benefit is limited, right?

468

And sometimes we have

to bring in innovation.

469

However, it has to be a balance

between, you know, understanding,

470

like, what is beneficial to my

organization, and is it worth the

471

disruption it's going to cause, and am

I committed to making it successful?

472

I think those are the questions that-

Mm … leaders like us grab and say,

473

"Hey, how do I solve that problem?"

474

But the advisor fatigue, technology

fatigue is very real right now.

475

Yeah, I think so too.

476

It's hard now to have a conversation

that d- in this space that doesn't evolve

477

around technology or AI doesn't come up

at some point during that conversation.

478

Lastly, Mohan, great conversation.

479

Real quick, you know, in this space

because of technology, there's a lot

480

of elements within wealth management

that are becoming commoditized,

481

whether it's investment management,

all the different ETFs out there.

482

You can get, go online and get

a lot of analytics for free.

483

It's being commoditized.

484

Is there something that can give firms

a strategic advantage moving forward,

485

kind of separate themselves apart

that maybe they're not thinking of

486

in, in a space that's so competitive?

487

So three things, right?

488

I would say the first, the

biggest difference maker is the

489

unified data and context, right?

490

Without that, AI is going to

be way too generic, right?

491

So I think getting in that layer is

going to be the biggest difference maker.

492

Couple of other areas I would

say, uh, productivity economics is

493

something that I would say is the

biggest, um, uh, strategic advantage.

494

Productivity economics, it's, you

have to have a relentless focus.

495

Uh, how much time is spent on productive

work is a question you gotta ask,

496

versus what can you do to, you know,

move away from the non-productive work.

497

And the third thing I would

say is end-to-end automation.

498

Rather than introducing a specific AI

tool that doesn't integrate well into

499

the, you know, the entire ecosystem,

the end-to-end automation is going

500

to be a big, uh, strategic advantage.

501

Firms that do these three really

well are going to reap the

502

benefits very quickly, right?

503

So those are, I would say, three things

that firms can use to ga- gain a strategic

504

advantage- Mm-hmm … in the near future.

505

Mohan, that's a great way of wrapping

up this conversation, bringing it

506

all together, and kind of goes back

to the beginning, you know, starting

507

with data, how important data is,

and that's, you know, where you

508

can add most value Right there.

509

Mohan, thank you so much

for coming on the show.

510

Such a great conversation.

511

I was- been looking forward to

this conversation sometime since

512

our previous one a year ago.

513

Um, thank you so much for

sharing such great insight.

514

It was an honor to have you on.

515

Where can our audience get more

information about Steward Partners?

516

So obviously, you, you can go to

our, uh, website stewardpartners.com.

517

We also have our LinkedIn channel.

518

We have our, uh, channels on, um, on,

uh, you know, Facebook, I would say.

519

But, uh, we are also very active

in the, in the press space.

520

We are participating in a lot of

industry conferences, but if you

521

want to learn a lot about, uh, our

practice, our advisors, go to our, our,

522

uh, website www.stewardpartners.com

523

and, you know, we'd love to have

a conversation with you guys.

524

I would like to stop and, you know,

give, like, my final pitch about,

525

like, um, AI along with advisors.

526

Advisors are not going to win by, you

know, uh, competing with AI, right?

527

Co-opt, like, I would say, uh,

focus on your strengths as advisors.

528

Uh, that's the best way to win in a

AI first world in wealth management.

529

Yeah, you're exactly correct, Mohan.

530

Just-- And it goes back to

where do you get started?

531

Focus on the things that take the most

time, that maybe you struggle with.

532

Have AI help you there, but it's a

complement, and it can help your practice

533

immensely having that complement to

what your strengths are, um, out there.

534

So great advice, Mohan.

535

Way to wrap it up.

536

And thank you so much for listening

to this episode of Zephyr's

537

Adjusted for Risk podcast.

538

You can watch all of our other

episodes on the Zephyr YouTube

539

channel, Spotify, and wherever else

you watch your, uh, favorite podcasts.

540

Be-- please be sure to like and

subscribe to those channels and

541

give us a follow on LinkedIn.

542

Thank you very much, and have

a great rest of your week.

543

Thank you, Ryan.