4 Ways AI Is Transforming the Financial Advisor Role and How HR and L&D Leaders Should Respond

At most financial firms, the question is no longer whether advisors will use artificial intelligence. Most already are.

A recent analysis reports that 95% of wealth and asset management firms have scaled generative AI across multiple use cases. And advisor adoption is moving just as quickly. In a 2025 Advisor 360° survey of 300 U.S. financial advisors, 85% described generative AI as helpful to their practice, up from 64% the previous year. More than three-quarters (76%) said they had experienced immediate benefits.

AI is reshaping the financial advisor role in four critical ways: automating administrative work, accelerating investment research, increasing the importance of human judgment and compliance and increasing the value of relationship skills. 

This makes AI as much a workforce development challenge as a technology initiative.

So, the question, then, is not whether advisors are using AI. It is how AI is changing what advisors do and whether their skills are changing along with it. 

1. AI Can Take Routine Work Off Advisors’ Plates

Advisors are already using generative AI for predictive analytics, marketing support, and meeting-note summaries, according to Advisor 360. Other uses include drafting routine communications, preparing for client meetings and organizing information collected during those conversations.

These applications can give advisors back meaningful time. But even relatively simple tasks need oversight. 

Consider a meeting recap that confuses two accounts, leaves out a concern the client raised or turns a tentative comment into a firm decision. The summary may read well enough that the mistake is easy to miss. Now, a time-saving tool becomes a data-privacy, compliance, or reputational problem.  

For HR and L&D teams, the first job is to turn firm policy into everyday practice. Advisors should know:

• How to use AI without exposing personally identifiable information, confidential financial data, or internal firm information

• A consistent process for checking AI-generated drafts or analysis when accuracy, context and compliance require additional review

• Who to contact when a use case falls outside of established guidelines

This training will be more useful when it reflects situations advisors actually encounter. For example, instead of simply warning about inaccurate output, ask them to review a flawed meeting summary and identify what needs to be corrected. 

That kind of practice helps advisors build habits they automatically follow no matter how busy the workday gets.

2. AI Is Accelerating Research and Making Critical Thinking Even More Important

AI can scan financial reports, economic indicators, company filings and market commentary far faster than an individual advisor. It can summarize developments, compare scenarios and identify patterns that might warrant a closer look. 

A 2025 Natixis Investment Managers survey of 520 investment professionals found that 69% expected AI to improve the investing process by uncovering hidden opportunities. Another 62% said it was becoming an essential tool for evaluating market risk. 

The operative word here is “tool.”

An AI system may flag an investment opportunity without fully accounting for liquidity, tax implications or a client’s time horizon. It may rely on incomplete information or mistake correlations for something more meaningful. Generative AI can also produce an answer that sounds authoritative even when the underlying facts are weak. 

But faster analysis is not necessarily better analysis. Advisors need to recognize when an answer does not make sense. 

That requires more than a course on prompting. Advisors need the financial knowledge to examine the assumptions, compare the output with trusted sources and decide whether the finding is relevant to the client. 

For this reason, firms should connect AI training to the rest of the advisor learning journey. Data literacy, investment knowledge, critical thinking, and professional education all contribute to an advisor’s ability to challenge machine-generated conclusions. 

AI does not replace the need for advisor expertise. It raises the value of expertise that can challenge the output.

3. AI Can Support a Financial Plan but the Advisor Still Owns the Recommendation

Advisors appear more cautious about using AI for work that sits at the heart of the client relationship. Only 29% of financial advisors surveyed by Advisor 360, said that they used AI to develop personalized financial plans. Compliance concerns were one reason for that restraint. 

The hesitation makes sense. 

A planning tool might produce a mathematically sound scenario without fully accounting for a client’s concentrated stock position, family obligations, or reluctance to accept additional risk. It can model possible outcomes, but it cannot assume the advisor’s professional accountability or fully understand what matters to a client. 

Workforce training should focus on that handoff: what the tool can do, what the advisor should do, and how the final decision will be documented. 

One useful exercise is to give advisors an AI-generated recommendation that is technically plausible but poorly suited for the client. Ask them:

• What additional questions would they raise?

• What would they change?

• How would they explain the decision? 

This gets closer to where automated support ends and professional judgment begins compared to a general lesson on the benefits and risks of AI. 

4. The Efficiency Dividend Only Matters If Advisors Reinvest It in Clients

One of AI’s clearest promises is that advisors will have more time for clients. But saved time does not automatically become better advice or stronger relationships.

Firms must decide what they want advisors to do with that capacity and help them develop the necessary skills to achieve it.

An AI-generated summary may capture every word from a client meeting. It will not, however, necessarily recognize the long pause before a client answers a retirement question or notice that two family members have conflicting priorities. Those moments require listening, context, and follow up.  

As technology takes on more information gathering and administrative preparation, advisors have an opportunity to go deeper by asking better questions, explaining complex choices more clearly, and helping clients make decisions during uncertain or emotional moments. 

That puts communication, discovery, and behavioral finance squarely within the firm’s AI strategy. This means corporate training should not treat human capabilities as secondary to technical AI training. 

Turning AI Policy into Advisor Capability

Financial firms have made considerable progress on governance. In the Advisor360 survey, 82% of advisors said their firms had formal generative AI policies, almost double the 47% in the previous year.

That is significant progress. But a policy is a starting point, not a workforce strategy. 

Three actions can help HR and L&D leaders close that gap:

1. Train within real workflows. Build learning around the decisions advisors make during meeting preparation, research, planning, and client follow-up.  

2. Connect AI fluency to advisor expertise. Technical training should sit alongside financial knowledge, professional education, continuing education, compliance, critical thinking, and communication, not apart from them. 

3. Measure more than course completion. Partner with managers to observe if advisors are using approved tools correctly. Are they catching weak outputs? Are they converting time savings into growing client lists and offering stronger service? 

Building the Skills Behind AI-Enabled Advice

Different parts of this learning strategy may call for different forms of development. Corporate training programs can support firmwide capability building, while professional designations and certifications help advisors deepen the expertise needed to evaluate AI-generated findings. 

For financial planning employees, CFP certification can strengthen the technical skills behind advisor judgment, while continuing education can help firms keep those capabilities as current as the technology, markets, and client expectations change.

AI can process information, prepare drafts and model possibilities. Advisors still have to decide what the information means, whether the recommendation fits and how to guide the client forward. 

Saving time is useful. What advisors do with that time will determine whether AI actually improves the client experience and grows assets under management.  

Kaplan Financial has built a foundation on merging technology with financial education to create an end-to-end learning ecosystem to boost pass rates, accelerate ramp-up times and drive long-term career growth for your employees. If you are interested in learning more about Kaplan’s continuous learning ecosystem, please reach out.