There's a wide spectrum of AI adoption in wealth management right now. On one end, firms are experimenting with ChatGPT for marketing copy. On the other, firms are building dedicated AI councils, running 40+ projects simultaneously, and using conversation intelligence to reshape how advisors serve clients.

Allworth Financial — one of the largest RIAs in the country — is firmly on the ambitious end of that spectrum. And the way they're approaching AI offers a practical blueprint for any firm serious about moving beyond experimentation.

In a recent conversation on the Next Mile podcast, John Bunch, CEO of Allworth Financial, shared how the firm is thinking about AI, why he considers it a "push all the chips in the middle" moment, and why firms that treat AI as a nice-to-have rather than a strategic imperative are making a mistake.

Start with governance, not tools

Fourteen months before our conversation, Allworth formed an AI council — a cross-functional team that meets weekly to oversee the firm's AI initiatives.

"We have two leaders inside the business," Bunch explained. "We have representation from legal, compliance, advisors, marketing — and we have over 40 AI projects in flight right now at Allworth."

The composition of the council is as instructive as its existence. Having the firm's chief legal officer — a former SEC lawyer — at the table from day one isn't a check-the-box compliance gesture. It's an acknowledgment that AI in financial services touches privacy, data security, regulatory compliance, and fiduciary responsibility simultaneously. Getting governance right isn't something you bolt on after you've built the tools. It's the foundation that makes everything else possible.

"This could end really poorly if you didn't have structure and discipline around this," Bunch said. "That's why we built the AI council. That's why they meet weekly. That's why I get debriefed. I debrief the board on it."

For firm leaders wondering where to start, this is the first lesson: build the governance structure before you scale the technology. A small cross-functional team that meets regularly, includes legal and compliance, and has a direct line to the CEO and board creates the environment where AI projects can move quickly without creating risk.

The data foundation makes AI possible

Allworth's AI strategy didn't start with AI. It started with data.

"We've had a data lake and been in the data business for five or six years," Bunch noted. "None of this is really new to us."

This is a critical distinction that separates firms ready for AI from firms still talking about it. Allworth built its data infrastructure before the AI wave hit. They invested in consolidating data from across their tech stack into a centralized environment — not because they knew exactly how they'd use it for AI, but because they understood that connected, accessible data was foundational to running a better business.

That investment is now paying compounding returns. Every AI project the firm launches has access to clean, structured data from across the organization. Advisors have dashboards that pull from this data layer to track everything in their practice. The firm can analyze patterns across thousands of client interactions. None of this would be possible if the data were still siloed across disconnected systems.

For firms that haven't yet invested in their data infrastructure, this is the bottleneck. You can buy AI tools all day, but if your data is fragmented across 7-12 systems that don't talk to each other, those tools will produce unreliable outputs at best and dangerous ones at worst.

Conversation intelligence: where AI gets real

One of the most compelling examples Bunch shared was Allworth's use of conversation intelligence technology across advisor meetings.

"They actually showed me data on 646 conversations my advisors had had over the last two weeks," Bunch said. "They broke down client sentiment based on the transcripts and the data — the information they heard. And then I could drill down into what products and services were talked about. If we talked about investments, what part of the investment were we talking about — asset allocation or specific investments?"

In a single hour reviewing this data, Bunch said he realized: "This is not going to be like the worldwide web. This is going to be totally transformational."

Think about what this enables. Instead of anecdotal reports about how client meetings are going, firm leaders can see quantitative data on client sentiment across hundreds of conversations. They can identify which topics are coming up most frequently, where advisors are strong, where they need support, and where client concerns are emerging before they become problems.

For practice management, the implications are profound. Managers can coach advisors based on actual conversation data rather than gut feel. Training can be targeted to specific gaps. Product and service development can be informed by what clients are actually asking about, not what the firm assumes they want.

AI as a practice management accelerator

Beyond conversation intelligence, Allworth has built advisor dashboards that leverage their data infrastructure to give every advisor a real-time view of their practice.

"All of our advisors have a dashboard where they can measure just about everything in their practice," Bunch explained. "I can get it on my phone. If you were my advisor, I could open up my phone and tell you, 'In the last year, you've had 47 financial plans. You've talked to 30 of your clients about insurance needs.' And we could have a robust conversation about how to manage your practice to be a better adviser and deliver better client results."

This is AI and data working together not as a replacement for the advisor but as an amplifier. The advisor still has the relationship, still makes the recommendations, still provides the human judgment. But now they have a data-driven view of their own practice that helps them identify opportunities, track their effectiveness, and continuously improve.

"To me, that's the start of AI inside of Allworth," Bunch said. "It's really about leveraging data to be more insightful."

Enterprise ChatGPT: innovation from the ground up

Allworth has also made enterprise ChatGPT available to every employee. This might seem like a basic move, but it's yielding results that a top-down AI strategy alone wouldn't produce.

"A lot of the innovation is coming from that kind of homegrown way of automating and making their lives easier," Bunch observed.

When you put AI tools in the hands of the people closest to the work, they find use cases that leadership never anticipated. An operations team member finds a way to automate a repetitive data entry task. A marketing team member discovers a more efficient way to produce client communications. An advisor figures out how to prep for meetings faster.

These individual productivity gains compound across a firm of hundreds of employees. And they create a culture where AI isn't something that happens to the firm — it's something the firm actively participates in building.

The CEO's role: transformational, not incremental

Throughout the conversation, Bunch was clear about where he stands on AI's importance: this isn't an incremental improvement. It's transformational.

"From my chair as a CEO, this is a push all the chips in the middle moment," he said. "I think the firms that don't adopt this and believe that the vendors that you're doing business with are going to be your AI engine — I think they're going to be left behind."

This is a direct challenge to the wait-and-see approach many firms are taking. The argument for waiting — let the technology mature, let someone else make the mistakes, let the regulatory environment clarify — has a surface-level logic to it. But Bunch's counterargument is that the firms investing now are building institutional knowledge, data assets, and operational capabilities that will be difficult to replicate later.

"I think it's a massive mistake if CEOs are not thinking about this as transformational change, not just a nice to have," he concluded.

What the future demands of advisors

Bunch's view of where AI leads the industry is both optimistic and challenging for the advisory profession.

"I think it's fair to say that clients will be able to do a lot of the things today that we do for them — whether it's cash flow analysis, analysis of investments," he said. "I think in the future, advisors will be more like counselors and coaches on a wide variety of things than they will be experts on cash flow or investments."

This is a significant reframing. If AI commoditizes the analytical work that advisors currently do — and there's strong evidence it will — then the differentiator becomes the human skills: communication, empathy, coaching, understanding context, navigating complex life situations.

"The firms that actually help their advisors move in that direction are going to be the winners," Bunch said. "Because a lot of life, it's not about how much money you have. It's about how well you live your life."

The firms building AI strategies today aren't just preparing for a technology shift. They're preparing for a fundamental evolution in what it means to be an advisor — and positioning their teams to thrive in that future rather than be disrupted by it.

This article is based on insights from Episode 113 of the Next Mile podcast, featuring John Bunch, CEO of Allworth Financial, in conversation with host Kyle Van Pelt, CEO and Co-Founder of Milemarker.

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