Don’t Make These Mistakes With Generative AI in Your Practice

Generative artificial intelligence seems to have limitless possibilities. However, just because generative AI can perform a task doesn’t mean it should do so—especially when it comes to financial advising.

If used properly, generative AI can help advisors take care of administrative tasks and allow them to spend more time on the softer side of financial advising, which is what investors value from a financial advisor.

But how do investors feel about all this? What do they think generative AI can reasonably do for their advisors, and what do they think it looks like to use generative AI “properly”?

In our research, we delve into this topic and provide guidance for how advisors can incorporate generative AI into their practice. In particular, we find some missteps advisors should avoid.

Mistake Number One: Using Generative AI for the Wrong Things

In our research, we presented one group of investors with examples of scenarios where advisors used generative AI. With a different group, we presented the same scenarios but did not mention that the advisor was using generative AI. For example, we posited to the first group, “Imagine a scenario where you are working with a financial advisor [and] … Your advisor uses generative AI when writing marketing content intended for your demographic.” And to the other group, we said, “Imagine a scenario where you are working with a financial advisor [and] … Your advisor writes marketing content intended for your demographic.”

We then compared people’s reactions, as measured by how each use case affected their relationship with the advisor. The graph below showcases the distribution of ratings for each of the use cases, with lower ratings reflecting a negative impact on the relationship.

Investors' Reactions to Gen AI Use Cases

Simply put, reactions seemed to skew slightly less positive when investors knew that generative AI was used in the execution of a task. Still, most reactions tended to stay in the positive or neutral regions.

However, when it came to uses that required a personal connection or access to person data, investors noted that generative AI use had a negative impact on the relationship. This included tasks such as “Providing personalized recommendations” and “Generating a personalized email.”

In other words, not all use cases are created equal when it comes to using generative AI. There are some activities that investors believe should be reserved to humans—which is actually great news for human advisors.

Lesson: Gen AI cannot build relationships for you, so don’t try to fake sincerity. Instead, use Gen AI for activities it is good at, like summarization.

Mistake Number Two: Not Using Safeguards With Generative AI

Although these results so far highlight a negative outlook of generative AI in financial advising, our study also points to ways advisors can mitigate investors’ concerns that may be driving these reactions.

We asked investors what kind of safeguards would make them comfortable with financial advisors using generative AI. We found five themes, each of which advisors should address to help assuage client concerns:

1. Investors want their privacy and data protected.
2. Investors want disclosure on the use of generative AI.
3. Investors want human review, where all generative AI output is checked for accuracy.
4. Investors want agency and the opportunity to opt out of using generative AI for their account.
5. Investors want unbiased advice.

Lesson: Don’t assume you and your clients are on the same page about generative AI. Take the time to implement safeguards and clarify them to clients. This can help address common concerns such as the accuracy of output and privacy protection.

Mistake Number Three: Not Communicating the Client Benefits From Your Use of Generative AI

It’s all too easy for investors to perceive an advisor’s use of generative AI as a way to cut corners. Without a proper explanation, investors may believe that their advisor is using generative AI to get away with doing less work and still get paid. Unfortunately, we do see this in our data. When it comes to their advisor using generative AI, many investors wonder, “What’s in it for me?”

Luckily, our data also points to an answer: efficiency.

When we asked investors what was driving their reactions, a reoccurring theme was “Efficiency.” Some investors mentioned this theme in a negative light, noting things like the advisor being overly focused on efficiency and not devoting enough attention to helping their clients. However, most investors saw efficiency as a positive, stating that its use can help advisors outsource the “dumb stuff” and focus on activities AI cannot replace, like human engagement, relationship building, and behavioral coaching.

Lesson: Emphasize how your clients are benefiting from your use of generative AI. For example, emphasize that generative AI gives you the ability to spend more time working with them face-to-face versus spending time on back-office work.

Wrapping Up

It’s undeniable that generative AI is a powerful tool. And, given the ever-increasing demands on advisors to differentiate themselves from technology, it’s one that advisors must learn to harness.

But just like any other tool, we must be careful how we wield it. In an industry where the client experience is of utmost importance, it’s essential to be aware of investors’ perceptions of generative AI and implement it in a way that works for them.