Compliant AI use for advisors

AI is powerful. But for advisors, it’s a compliance minefield.

Financial advisors are stewards of some of the most sensitive personal data imaginable—social security numbers, bank accounts, birthdates, home addresses, and family details. The responsibility is immense. A single misstep with this data can lead to a catastrophic breach of trust and legal exposure.

That’s why the rise of AI presents such a paradox for advisors.

On one hand, AI tools are game-changing. They can summarize meetings, draft emails, identify follow-ups, and automate hours of manual work. Not using AI today is electively hamstringing your firm. But on the other hand, using AI recklessly—especially with client data—is like handing your filing cabinet to a stranger.

Let’s break it down.

The compliance risk of AI workflows

Here’s a common and seemingly helpful workflow:

1. A Zoom meeting ends

2. The transcript is passed to ChatGPT to summarize the conversation

3. Notes and tasks are created in Wealthbox CRM

4. An email draft is generated in Outlook

   
   

   

   
   

But behind the scenes, something dangerous is happening: raw, unfiltered client data is being passed between multiple third parties (Zapier and OpenAI, in this example), each of which may be using your data to train their models or store it insecurely.

In another example, we’ve heard from many advisors who use Google’s NotebookLM to gain insights from client documents. Advisors upload files, such as tax returns, account statements, and mortgage documents, seeking help with summarizing, analyzing, or answering questions based on the data. But here’s the issue: every single one of those documents contains highly sensitive PII, and once they’re uploaded to Google’s systems, that data may be used to train models or be stored indefinitely.

Google’s Notebook LM, OpenAI’s tools, and others may ingest user data unless you’ve explicitly opted out through enterprise agreements. For most advisors, this means that a client’s PII may be used to train systems that are completely outside your control. That should raise massive compliance red flags.

So what’s the solution?

Abandoning AI isn’t realistic. The productivity gains are too substantial to ignore.

The solution isn’t to opt out—it’s to use AI the right way.

Here’s what that looks like:

• Use one trusted platform Don’t pipe sensitive data across five tools. Keep your data in one secure system that does everything in place. Every additional handoff increases the risk.

• Obfuscate and redact sensitive data before AI sees it When client data is sent to an AI model, personal identifiers should be either obfuscated (temporarily hidden) or redacted (permanently blacked out), depending on how sensitive the data is.

  
  

Obfuscation vs. Redaction

• Obfuscation: Temporarily masks personal data with tokens so it can be safely processed, then restored afterward.

  • Example: “John Doe” becomes <NAME:Mc8>, and is reinserted after processing.

• Redaction: Permanently removes highly sensitive data that should never be shared with a model.

  • Example: A social security number becomes ██████████ and remains hidden.

    
    

An example in action

Before AI Processing:

My name is John Doe and my email is john.doe@example.com.

I live in Cedar Hills, Utah and my phone number is (123) 456-7890.

My social security number is 123-45-6789…

After Obfuscation and Redaction:

My name is NAME:Mc8 and my email is 6re@redacted.example.

I live in ████████████████ and my phone number is ██████████████.

My social security number is ██████████…

When the AI returns its output, the system can reintegrate obfuscated fields (such as names), but redacted fields remain hidden. That’s the balance: security and usefulness.

Safe AI starts with the right infrastructure

If you’re an advisor using AI—or thinking about it—don’t assume the tools you’re using are secure by default. Most aren’t.

You need systems built specifically for the industry’s complex compliance needs. You need smart data handling built in. And you need to understand exactly where your data is going.

At Slant, we’re building that kind of infrastructure—where advisors can get the benefit of AI without putting client trust at risk.

AI doesn’t have to be dangerous. But it does have to be done right.

How Slant keeps your data safe

At Slant, we believe advisors deserve the power of AI without compromising client trust. That’s why we’ve built security into the foundation—combining intelligent automation with industry-grade safeguards.

Here’s how we do it:

• All-in-one AI assistant

Slant doesn’t rely on a fragile patchwork of disconnected apps. While we utilize best-in-class infrastructure partners, we’ve designed Slant to be security-first, operating as a unified, tightly controlled platform to help protect your data.

That means fewer unnecessary handoffs, clearer accountability, and stronger safeguards for your clients’ most sensitive information.

Every step—from transcription to redaction to task creation—flows through a secure, coordinated environment designed specifically for advisors.

• Automatic obfuscation and redaction

  
  

  Before any data is analyzed by AI, Slant masks or removes sensitive information. Names, account numbers, and personally identifiable information (PII) are obfuscated or redacted entirely, ensuring private details remain confidential.

  
  

• Reversible tokenization

  
  

  Obfuscated data is safely reinserted into the final output, allowing advisors to gain clarity without exposing client information.

  
  

• End-to-end encryption

  
  

  All client data—whether stored or in transit—is encrypted using enterprise-grade protocols, protecting against unauthorized access at every step.

  
  

With Slant, you don’t have to choose between security and speed. You get both—intelligent automation that respects your compliance obligations and protects your clients.