The AI Performance Edge for Advisors with John Connell

How did you come to see that combination as a key to upleveling advisor outcomes and team performance?

[00:00:53] John L. Connell: Great question. So we actually started with a very practical problem: the pain points experienced by advisors around note taking, putting together meeting prep, writing follow-up emails, and the manual data entry work across planning tools and the CRM. I'd had some family and wealth prior, had some touch points there myself. And from there we saw an opportunity that most tools were missing.

Advisors really don't need another generic AI assistant, right? There's Copilot, there's Zoom AI. We didn't want to recreate the wheel. So instead we partnered with the industry leaders in behavioral finance, shaping wealth to layer science back performance coaching and proactive team insights on top of data aggregated across client conversations, as well as client data more broadly. And really in the world of AI, data is the oil that powers the Focal AI machine.

So what that unlocks for us is quite powerful. It's every advisor now has access to the same performance frameworks used by the industry's best. That translates to better questions. That translates to better prospecting, better AUM conversion, perfect memory across touch points with a client to help advisors spot opportunities for cross-selling, or make sure that they're asking about their client's dog, you know, that just wrapped up puppy training last year. At the end of the day what we're building at Focal AI is a revenue optimizing operating system for advisory teams that's built on compliant data, connected systems, and performance coaching that actually moves the needle.

[00:02:31] Doug Heikkinen: What does performance coaching powered by meeting data actually look like in practice. Can you share an example of how those insights translate into better client conversations or conversion rates?

[00:02:44] John L. Connell: Definitely. So this goes far beyond talk time, or basic sentiment analysis. What Focal AI does is pulls from tens of thousands of proprietary behavioral finance assets and research reports, including work from Sanford PhDs and Brian Portnoy's team over at Shaping Wealth. That's effectively what allows us to deliver personalized science backed feedback directly tied to better outcomes.

I like to describe it really this way. Imagine having the best advisors in the industry sitting on your shoulder after every meeting, giving you precise, evidence-based guidance on how to improve. How to go deeper with your clients. And practically this means that we help advisors refine the specific questions that they're acting in that conversation, or asking their clients more broadly.

And because we have that full historical context on the client relationship through the CRM, planning tools, anything that you connect in with Focal, we've got 130 plus integrations today, Focal AI can then proactively surface missed opportunities. So, maybe forgetting to bring in a client's kids into the retirement conversation. Or recognizing mortgage or insurance opportunities when a client mentions buying a home.

So really, across a team this changes everything by way of outcomes, because everybody on the team now has the right tools to become an A team player.

[00:04:13] Doug Heikkinen: Many advisors see coaching as a soft skill, but you're tying it directly to measurable outcomes. How does Focal AI's approach help teams learn faster and scale high quality service across a firm?

[00:04:25] John L. Connell: First focal AI already saves Advisors ten to roughly fifteen hours per week through compliant meeting prep, note taking, CRM sync, and follow up email automation. Now, the most important issue is what we do with that time, right?

With performance coaching layered in, we help advisors close more prospects, bring over more AUM, and in many cases identify assets that were casually mentioned in conversations years ago but perhaps never acted on. So, today we're providing behavioral cues across core insight areas such as active listening and question quality, follow up execution, structured meeting hosting, and decision ownership.

And if you've got somebody like a Jason Pereira or Michael Kitces on your shoulder telling you how to be a better advisor, that's essentially what the Focal AI experience delivers at scale. And then for those teams, if you're a leader of an organization, you are able to have insight for the first time into analytics that shows exactly how every advisor benchmarks across key performance metrics.

So each advisor receives a personalized performance improvement plan and then the managers suddenly have visibility into who their top performers actually are and how it is that they can then tactically lift the bottom quartile to the same level as their best performers in the business.

[00:05:53] Doug Heikkinen: Let's talk about security and compliance. Focal AI puts a lot of emphasis on being purpose-built for financial advisors. Why does secure compliant AI create a competitive advantage for advisory firms?

[00:06:07] John L. Connell: You know, Doug, we see a lot of AI vendors, especially in the pure AI note taking space, operate in the gray. And this might be a factor of their CTO being based overseas. Maybe they're sending customer data directly to OpenAI or Anthropic. Maybe they're storing video recordings. And all of that, right? It introduces real risk.

So the key is really secure conversational data being the foundational layer for agentic automation. From our vantage point at Focal AI, we are compliant for SEC, FINRA, even OPC and PIPEDA regulated entities up north in Canada. And because we operate inside a secure Microsoft Azure perimeter, we can then safely use that data to do things like automatically fill PDFs. We can populate hundreds of fields across CRMs or planning tools like Conquest. And then trigger downstream workflows with a single click.

So building security first infrastructure from day one for us was absolutely priority number one. The whole team on our end has a background in enterprise technologies. Focal AI's CTO, for example, had started his career at a broker dealer that was then bought by Goldman Sachs. And he was an early employee at both DocuSign as well as Chainalysis.

So this is just a single point of example on the team. He's already built compliant systems for some of the largest financial institutions in the world. I think what we're seeing in market is that security isn't just a check the box or a constraint here. It's really what enables everything else. It's ultimately table stakes. And you have to get that right from day one.

[00:07:49] Doug Heikkinen: Some advisors are tempted to lean on generic AI tools. What are the hidden risks or trade-offs compared to solutions built specifically for regulated environments like wealth management?

[00:08:01] John L. Connell: Yeah. So, many generic AI tools don't meet regulatory standards. Full stop, right? Many store video artifacts. They expose public URLs. They lack clear PII policies, or they don't offer proper data residency or retention controls. So there are firms that without even realizing it are losing control.

Now the way that we define "purpose-built" at Focal AI, that means that we're abiding by industry regulatory standards. We are understanding the advisor client context around conversations like retirement or insurance or planning. We are delivering industry specific coaching insights, and then automating workflows that are unique to the advisors, the assistants, CSPs, ops teams as well.

And what I'd want advisors to know is that choosing a vertical specific or a purpose-built tool, right, for advisors, versus an off the shelf generic AI, is really about more than just features. It's about the compliance considerations, it's integration with your most commonly used tools. It's really setting your firm up to be competitive in an environment where your peers are already using AI to get ahead.

[00:09:17] Doug Heikkinen: When firms are evaluating AI vendors, what are the top questions they should ask about things like data privacy, storage, and long-term compliance posture?

[00:09:28] John L. Connell: Exceptional question. Yeah, this is absolutely critical, right? There are in my head four or five big questions that should be asked. One being, is your CTO and personnel with potential PII access exclusively based in the US or Canada, right? We don't have our CTO based outside of North America, and for Focal AI we're operating under a strict SOC 2 type 2 per enterprise requirement.

The second question here is around model training and customer data. Does a vendor train their models on customer data? In our case we're using stateless models by design, which means that customer data is never stored and it's never otherwise trained or used by those foundation model providers.

The third big question to ask, and this is important to align with SEC, FINRA, and some of the requirements up north as well, is do you store audio or video? And then where and how is that data stored, right? Depending upon your jurisdiction, there are regulatory bodies that you have to abide by.

And I'd say the last one I'll throw in here, if you're looking at a specialist offering, something like what Focal is doing with performance coaching, is that unique in some way, shape, or form, right? Is it science backed, in our case, or partnered with an industry expert. Or is it more of a off the shelf capability set versus something that is purpose built for your use case.

So I think what I'd want firms to understand here is that the answers around some of these key questions, they should be quite clear from AI vendors. And ideally they've had a few reps with just understanding what good looks like in their space.

[00:11:13] Doug Heikkinen: Shifting to adoption, many leaders say their biggest AI challenge is an interest. It's execution. What have you seen works best for firms actually rolling out AI tools that stick?

[00:11:26] John L. Connell: You're exactly right. Yeah, interest isn't the problem here. It's execution all the way. Firms today should be thinking about ROI on time to value. What we're seeing successful firms do is start with workflows that advisors already use. So some of the most common include note taking, meeting prep, we've seen prospecting be popular as well. And as firm's advisor count grows, being able to then uplevel behavioral performance across that advisor base becomes increasingly important, so that the quality, for example, of coaching actually matters quite a lot.

From there we've seen organizations typically roll out in small cohorts, really focusing in on a select set of advisors for feedback and insight. And then once you've been able to find what works, lean into scaling that motion to then capture the value, especially within those larger enterprise functions. Because ultimately you need to be able to tie the AI and the output there to time saved, to revenue impact. These are the metrics that actually matter.

And importantly, involving compliance early so that you don't have bottlenecks later related to vendor dd, and just pushing a vendor through the process. I think that the key here is setting yourself up for long-term success with AI, not just a flashy pilot.

[00:12:53] Doug Heikkinen: Everybody says AI is going to save advisors time. But beyond that how can advisors measure whether AI is truly improving performance, for example, in consistency, client follow up, or their overall experience?

[00:13:09] John L. Connell: We recommend that firms evaluate very concrete outcomes. That includes prospect conversion rates growth in AUM tied to proactive insights that are uncovered and otherwise unknown. The number of meetings advisors can manage with an extra 10 to 15 hours per week.

We've got a couple of clients on the website now that speak to the testimonials on, hey we're saving up to 15 hours a week. We are seeing a return on 21% this year, best year yet.

But ultimately when everyone improves together, variance shrinks, and then performance compounds.

[00:13:52] Doug Heikkinen: Advisors often worry automating tasks will make service feel less personal. How do you help teams decide which tasks to automate and which should remain human driven?

[00:14:04] John L. Connell: That's a great question. So we view Focal AI as an empowerment tool for advisors. It's not a replacement. The key distinction here Is that we are automating the work that distracts from those relationships not the work that creates them. Think documentation, CRM updates, task creation, having to manually type out emails. What we're not trying to automate, this is the human's role, to establish that bond of trust, is the judgment, the empathy. The advice still stays human. So ironically, the firms that automate well end up delivering more personalized services because advisors are now fully present with their clients.

[00:14:52] Doug Heikkinen: Last one for you as agenic AI continues to evolve, how do you see it shaping advisor workflows over the next few years, and what excites you most about these possibilities?

[00:15:04] John L. Connell: Yeah, yeah. There's so much excitement to be coming next So we'll continue automating on our end at Focal AI monotonous, back office work like data entry, which frees advisors and teams to then engage more deeply with clients.

Now what's coming next is even more exciting, arguably. We've got deeper personalization in performance coaching. There is team level insights and benchmarking that's already here. You can expect more on that front. Training acceleration for new advisors. Multi-step workflow automation across multiple advisor tools, beyond just piping data and automating data in empty fields.

Right now we're especially excited about automatically filling PDFs like RMDs or beneficiary forms, and then being able to sync that data across platforms like a Conquest or your CRM. And again I just want to really iterate here that this does not replace advisors. It elevates them. And the future advisor I think spends less time managing systems and more time, ideally, doing what clients truly value. It's thinking it's listening and it's guiding clients.

[00:16:19] Doug Heikkinen: John, great stuff. Again thank you for being with us today, and best of luck to you for a great 2026

[00:16:26] John L. Connell: Thanks Doug right back at you I appreciate the time here.

[00:16:28] Doug Heikkinen: To learn more about focal ai please visit MeetWithFocal.com That's MeetWithFocal.com. We are on all social media platforms @Advisorpedia. Please give us a follow. For our producer Tory Miller and everyone at Advisorpedia, thank you so much for listening.