Should You Require Your Team to Use AI?

AI for Advisors newsletter

Some people on your team are probably using AI every day, while others haven’t touched it. For now, that’s a difference in personal preference. The question worth asking is how long it stays that way?

Imagine two employees. Both are intelligent. Both work hard. Both care about clients. One uses AI every day. The other refuses to touch it.

Six months later, one employee completes tasks faster, drafts better communications, prepares for client meetings more thoroughly, and picks up new topics more quickly.

The other works exactly as they always have. At what point does AI become less of a personal preference and more of a professional expectation?

Workplace technology follows the same pattern

At first, adoption is optional. Then it becomes encouraged. Eventually it becomes assumed: Email, CRM systems, financial planning software, video conferencing. Nobody asks whether employees should use those tools anymore.

The debate ended quietly, without any formal announcement. The tools just became part of the job. The question is whether AI is heading down the same path—and how fast it’s moving.

For many firms, AI is no longer experimental. Teams are already using it for:

• Meeting preparation and follow-up
• Client communications and outreach
• Marketing content and newsletters
• Research and competitive analysis
• Internal documentation and knowledge management
• Workflow automation and task delegation

The issue is whether some employees are learning to work with AI while others are standing still.

What happens when AI fluency becomes uneven?

Now, imagine two advisory firms. The same scenario as the employees above. Both have talented advisors, good teams supporting them, and both care deeply about clients. One firm has spent a year helping colleagues learn how to use AI safely and effective, while the other has treated AI as optional.

Twelve months later, one team is vastly more efficient and effective than the other. The difference isn’t innate human intelligence, it’s that one team is leveraging on-demand intelligence that amplifies their capacities and enjoying compound benefits.

So, the risk isn’t AI replacing employees. It’s AI-assisted team and individual employees outperforming non-AI powered teams and employees. A productivity gap that starts small doesn’t stay small. Over time, it creates real challenges around compensation, performance management, hiring, and career advancement.

If two people have access to the same tools but one consistently produces more, leaders eventually must respond.

The case against mandating AI

Of course, there are legitimate reasons to be cautious: compliance requirements, data privacy questions, accuracy concerns, uneven skill levels across the team, and the very real fear of overreliance on AI outputs that no one has stopped to verify.

And the skeptics aren’t wrong to feel uneasy. Public concern about AI is rising, driven by worries about job displacement, data privacy, environmental costs, misinformation, and the concentration of power in the hands of a few largely unaccountable technology companies. That’s not fringe thinking. That’s a significant portion of the workforce.

So, blanket mandates will likely create resistance rather than progress. These are real concerns and they deserve real policies. What they don’t deserve is to become permanent excuses for standing still.

Is this the wrong question?

Instead of asking “Should everyone use AI?” try asking “Should every employee know how to use AI when it would improve their work?” That reframe matters. It shifts the conversation from compliance to competency and from resistance to readiness.

One way to find out where your firm actually stands is to assess it directly. The prompt below will walk you through a structured conversation with any AI model and help you evaluate your firm’s current level of AI readiness.

AI leadership assessment prompt

Copy and paste the prompt below into any AI model:

After you run through those questions, you’ll have a clearer picture of whether AI in your firm is truly optional—or whether it’s quietly becoming something more.

What AI fluency might look like—and how to build it

In practice, firms may begin expecting employees to understand basic prompting, evaluate AI-generated outputs critically, verify facts and recommendations independently, protect sensitive client information, use AI within firm policies, and know when not to use it at all.

That’s professional literacy, not technical expertise. You don’t need everyone to become an AI power user. You need everyone to become AI-capable.

Most firms don’t need sweeping mandates to get there. A more practical approach includes selecting approved tools, establishing simple policies around privacy and compliance, offering basic AI literacy training, encouraging employees to identify one recurring task AI could help with, and sharing successful use cases across the team.

The objective isn’t forcing adoption. It’s helping people develop competence and judgment—the same way you’ve always brought new professional skills into your firm.

The advisor-specific question

Some advisors wonder: “Will AI replace financial advisors?” A more immediate question may be: “Will AI-literate advisors outperform advisors who ignore it?”

The answer increasingly appears to be yes because AI amplifies expertise, rather than replace it. Advisors who combine deep client knowledge with AI-assisted research, communication, and planning may gain real advantages in the quality of their work and in the time they have left over to deepen client relationships.

There may be an even deeper question emerging. If AI can help advisors identify planning opportunities, prepare more thoroughly, surface risks, and communicate more effectively, does understanding those tools eventually become part of professional responsibility? Even part of a future fiduciary standard?

That question remains unsettled. But history suggests that when a technology consistently improves the quality of professional work, clients eventually expect competent professionals to understand it.

The good news is that AI fluency does not require technical expertise. Most professionals don’t need to become AI programmers. They need enough familiarity to understand what AI does well, where it falls short, and how it can fit into their workflow.

The spreadsheet test

Consider this scenario: A candidate walks into an interview and says, “I should let you know—I don’t use spreadsheets. Never have, never will.”

Most hiring managers would politely wrap up the interview. Spreadsheets aren’t exotic technology. They’re a baseline professional expectation and you don’t get credit for avoiding them. You just get passed over.

We may be approaching the moment when AI carries the same weight. Not a tool for early adopters but also not an optional enhancement. More like an emerging baseline professional expectation.

The debate is about whether learning to work with AI is becoming a fundamental job skill in the same way working with email, software, and spreadsheets became fundamental. The firms that answer that question early may have a lasting advantage over the firms that wait.