What Your Team Needs to Know About AI Security

As AI adoption grows, it’s critical to carefully review and manage data access, permissions, and overall data security. While AI has revolutionized the way we do business, there are some serious limitations of AI security controls, and the risks of ignoring proper safeguards could leave your organization vulnerable. Luckily, we’ve developed a practical action plan for deploying AI securely across your organization.

If you’d like to watch a video explaining this, view the recording here:

What Your Team Needs to Know (and Do)

Here’s what your team needs to understand about AI security: no matter what system you’re working in, whether it’s your ERP, CRM, or other platform, you need to make sure each role has the most limited permissions possible.

What some companies do is default to the “system admin” role so that each person can do anything. But if you do that with your AI, you end up sharing vulnerable information, and your AI could accidentally leak that data to those who shouldn’t have access. Each role within your organization needs to be aware of AI security risks and best practices.

IT Administrators

IT administrators get the first pass at enforcing strong AI security guidelines. The first thing they should do is clean up debt accounts, excessive permissions, and shared service accounts. Then, instead of giving AI access to every piece of data, they should give it the least amount of access possible, slowly adding on the permissions that are needed.

If you’re an IT administrator, make sure you do the following:

• Use separate environments
• Enable multifactor authentication
• Establish a review cadence

Go in regularly and look to see if there’s still a need for a specific team to have admin rights within the system. Check for inactive users and excessive permissions.

Business Users

For business users (or anyone using AI), it’s important to only utilize the AI tools explicitly allowed. You should treat MCP server URLs or login credentials like passwords, and never share them with anybody.

Remember, if you ask your AI a question and it says, “I don’t have access to that data,” you aren’t supposed to have access to that data. That means the AI security guardrails are working correctly.

Leadership

For leadership, AI security comes down to a governance decision. You need a data classification policy that defines what’s AI eligible, what’s not, and where the line is between them.

For example, salary data shouldn’t be handled by AI, because you wouldn’t want too many people in the company to have access to that information. However, customer contact information and sales orders may be eligible for more users. Make those decisions deliberately and communicate them clearly to your security team.

Honest Limitations of AI Security

All security has limitations. One of the biggest ones is that no system can prevent a legitimate user from misusing data they’re authorized to see. That’s why it’s so important to look internally at your roles. When an authorized user has all the right access, but misuses that data, it stems from a hiring and training issue.

We also can’t guarantee that AI won’t hallucinate. We can provide it with all the data it needs, but AI still might confidently give you the wrong answer.

Security is risk management, not risk elimination. Even the best security model fails if nobody reviews it, updates it, or enforces it. With PopdockAI’s 7 layers of security, we can reduce the attack surface, make unauthorized access incredibly difficult, and create clear audit trails, but even we can’t eliminate the risk completely.

What Happens If You Ignore AI Security

The scary truth is that employees might already be using AI before you’ve permitted them to. Maybe somebody discovered that they could upload an Excel spreadsheet of customer data into ChatGPT, and it was able to build a report faster for them. No one told them not to, so they kept doing it. Shadow AI is a real risk.

With the free version of ChatGPT, the data uploaded could be used to train future models, which includes your customer data. There’s no audit trail or contract to protect you. If you wouldn’t email it to a stranger, don’t put it in a free version of an AI platform.

To understand just how risky this is, imagine someone within your organization is good with technology. They make their own MCP server, but there’s no security review, no credential management, and no logging. The MCP server works for a demo and proof of concept, but then six months later, you discover that it was exposed without authentication. This leads to a data security incident.

Now you have the security team asking for an audit trail that doesn’t exist. Your legal team asks what data was exposed, and you don’t have an answer. The board says, “Why weren’t there controls in place?”

If you ignore AI security, you open your organization up to compliance violations and reputational damage. Doing nothing isn’t really a “free” option; it just has some deferred consequences.

Build Your Own vs. PopdockAI

When trying to decide how to address AI security, it’s important to know what goes into an out-of-the-box or do-it-yourself approach. PopdockAI makes it easy to take control of your AI security.

Your AI Security Action Plan

Implementing AI securely is not negotiable. We’ve created a practical, phased approach that provides a solid framework without requiring you to stop your current workflows.

PHASE 1: ASSESS (Weeks 1-2)

The first step is assessment, and most companies, unfortunately, will skip this step. Before you start implementing something, you need to ask yourself how you can do it securely.

• Inventory all AI tools in use (official and shadow)
• Audit ERP security
• Classify data
• Identify which systems need AI connectivity
• Review admin access for each account within each system

A lot of people are starting with one tool, then finding out that the tool has limitations, and then they switch to another AI tool that’s more robust and better equipped to handle their MCP requirements. This is why it’s important to assess everything before heading into implementation.

PHASE 2: IMPLEMENT (Weeks 3-6)

When starting to implement AI, you should deploy AI with the most restrictive access. Start small. Don’t just jump in with a project using 50 different tools.

• Deploy PopdockAI with least-privilege connector roles
• Configure list and field-level restrictions
• Set up separate environments
• Enable audit logging
• Implement MFA (multi-factor authentication)

It’s much safer to start small and then add fields after testing. Get a secure, successful model first, start with the most restrictive access you can tolerate, and then loosen as needed.

PHASE 3: GOVERN (Ongoing)

Governance is a long-term endeavor that never ends. Especially if you want your AI security to stand the test of time.

• Quarterly access review
• Regular AI query audit log reviews
• Update data classifications as business needs change
• Train new employees on AI security policies

AI security is the most important aspect of using AI within your company. Your team needs to understand how it works and what could go wrong. With PopdockAI’s 7 layers of security, you can control what information each user, along with your AI, can access.

Questions are answered, data is retrieved, records are updated, and insights are generated, all while seven layers of security operate transparently in the background. Contact us to learn more about PopdockAI and see how we can help keep your data secure.