AI in wealth management: Schwab’s Alison Dooher on advisor adoption and governance

Artificial intelligence in wealth management didn’t just evolve over the past year – it accelerated.

What was once experimental is now embedded in daily workflows. At the recent industry gathering, I sat down with Alison Dooher of Schwab Advisor Services to discuss what’s changing, what advisors should be cautious about, and how large institutions are thinking strategically about AI’s next phase.

Here’s an edited transcript of our discussion:

Suleman Din: Over the past year, AI tools have flooded the wealth management space. From your vantage point, what stands out most?

Alison Dooher: I’ve never seen something go from new to norm so fast. In about 12 months, we went from advisors asking what AI is and whether they should use it to the vast majority using it regularly in their practices. That speed has been remarkable – and I don’t think it’s slowing down.

What’s also interesting is how AI changes the data conversation. Advisors have long been told to structure and clean their data. AI now enables the extraction of value from data without extensive structuring. That unlock could be incredibly powerful.

At Schwab, we’ve initially focused on applying AI to our own knowledge content — essentially, organizing and delivering answers more intelligently. Instead of advisors searching through multiple links and platforms, we want them to ask a question and get a specific, relevant response quickly. We’re actively testing that model with strong confidence thresholds before broader rollout.

Din: Every technology cycle has a push-pull between innovation and caution. Where should advisors slow down?

Dooher: Governance and data protection come first. We take a “measure twice, cut once” approach. Firms need clear internal AI policies – what’s permitted, what’s not and how client data is handled.

Advisors also need to scrutinize vendors. If you’re using third-party tools, you must understand how they handle your data. Is it still solely your data? Is it being used to train other models? What are the breach risks?

There’s also a legislative layer. Right now, states are introducing their own AI rules. Ideally, we’d see clearer federal guidance focused on outcomes rather than tool restrictions. Let innovation happen – but define responsible boundaries.

Din: There’s also the issue of hallucinations and liability. How should advisors think about that risk?

Dooher: The “human in the loop” concept is real – and essential.

AI should augment, not replace, especially in client engagements. Take meeting note-takers. A simple but powerful policy is to require someone to attest that the summary is accurate and that the next steps are correct.

That human confirmation protects clients and firms. It also preserves the advisor’s role as the expert. Automation can’t replace judgment.

Din: We’re already seeing advisors send AI note-takers into meetings – sometimes without even attending themselves.

Dooher: I don’t love that.

Beyond compliance risk, it changes culture and etiquette. If you’re recording or summarizing with AI, you should seek permission. Clients deserve transparency.

And advisors should expect the reverse – clients may bring their own AI devices into meetings. We’ve seen this trend in healthcare. That introduces another voice into the room. It may offer “second opinions” in real time.

But just like self-diagnosing on search engines, AI-generated feedback can be incomplete or wrong. Advisors must be prepared to contextualize and educate.

Din: What are you learning internally as you deploy these tools?

Dooher: Two major themes.

First, AI-driven knowledge delivery. Advisors typically don’t call us for simple questions – they call for nuanced ones. AI helps surface the right content in a digestible, quick-to-access form.

Second, integrations matter more than ever. Note-takers evolved from summaries to next-best-action prompts. But that only works if the ecosystem has access – with permission – to the right data.

What’s old is new again: integrations, data hygiene and connected systems are foundational. The magic doesn’t work without them.

Din: What vendor innovations have impressed you most?

Dooher: Workflow intelligence is compelling – especially tools that structure unstructured data to trigger action.

Equally interesting is insight generation. Some platforms analyze meetings to identify patterns that predict attrition risk or life events. Others evaluate whether key topics were addressed in prospect meetings and help firms refine the quality of their engagement.

It’s almost like a dynamic performance script running in the background – highlighting gaps in real time. That’s powerful for continuous improvement.

Din: Schwab serves both large and small RIAs. How does that shape your AI strategy?

Dooher: We operate on two ends of a barbell.

On the one hand, we build proprietary tools that drive scale and efficiency within our custodial platform. On the other hand, we lean heavily into integrations and partnerships across the broader tech ecosystem.

We’re intentional about APIs, data delivery, and strategic partnerships. Advisors operate within rich tech stacks. Our role is to help solve the integration challenge – not replace the ecosystem.

Din: AI demands infrastructure investment. How does that affect long-term technology strategy?

Dooher: Modernization is constant. The key decision is whether you bolt AI features onto existing systems or build them into next-generation architecture.

Sometimes choosing the long-term build means a slower time to market – but it prevents building twice. That’s a strategic call every large institution must weigh.

Din: Big tech firms are pushing aggressively into AI. Could they disrupt established financial institutions?

Dooher: Our principle is clear: AI augments human relationships – it doesn’t replace them.

Schwab has thrived for decades because of people. The commitment to advisors and clients is the differentiator. Technology enhances that – it doesn’t substitute for it.

We’ve always balanced build-and-partner strategies. That won’t change. Innovation requires ecosystem collaboration. But the core value remains human expertise and trust.

The bottom line for advisors

AI in wealth management has moved beyond curiosity. It’s operational. It’s client-facing. And it’s shaping workflows in real time.

But as Alison Dooher emphasizes, the winning firms won’t be those that automate the fastest – they’ll be the ones that:

• Protect data rigorously
• Keep humans in the loop
• Build strong integrations
• And use AI to enhance – not erode – client relationships

The tools may evolve rapidly. The trust equation does not.