Why Your Organization Needs to Take Permissions and Security Seriously as You Bring in AI Tools?

As companies begin to bring in powerful AI tools like ChatGPT and Copilot, they’re discovering new ways to improve productivity and streamline tasks. These tools can analyze data, automate repetitive tasks, and even make suggestions that help employees work smarter. But there’s a risk here that many organizations overlook: security and access control.

Some companies rely on “hiding” sensitive parts of applications - keeping certain menus, data, or pages out of sight - to prevent unauthorized access. But with AI, this approach isn’t safe. AI tools aren’t bound by what’s visible or invisible on the screen; they can often find and access hidden data or functions. Without proper permissions and access controls, this can lead to serious security breaches. Here’s why your organization needs a detailed review of permissions and security settings before diving into AI.

1. Hiding Data Isn’t the Same as Securing It

In traditional applications, companies sometimes “hide” sensitive areas from certain users, hoping that will prevent unauthorized access. But AI tools don’t rely on a visual interface like people do - they can sometimes bypass the surface and access information that wasn’t intended for them. So, if a sensitive area or data set is only “hidden” but not truly restricted, an AI tool could still see or use it.

This means security through obscurity (just hiding elements) is no longer enough in an AI-driven world. Organizations need to make sure every piece of sensitive data and every critical function is properly restricted through access controls.

2. Permission Checks Keep AI from Seeing What It Shouldn’t

A thorough security assessment helps ensure that each role within the company has access only to what they need to do their job - no more, no less. This includes:

• Defining user roles and access levels: Each user should only see what’s relevant to them.
• Limiting sensitive actions: Making sure actions like deleting data or accessing confidential information are carefully controlled.
• Securing data behind strong permissions: Data shouldn’t just be hidden from view but actively protected by access controls.

By running a full review, companies can close security gaps before AI tools are put in place, reducing the risk of exposing sensitive information.

3. Avoid Data Leaks and Privacy Issues

With privacy laws like GDPR and HIPAA, there are strict regulations around who can see what data, especially when it’s about customers or patients. If AI tools aren’t managed with secure access controls, they could accidentally reveal or mishandle sensitive information.

To avoid the risk of fines, legal issues, and damage to reputation, companies need to know exactly what data each user, role, or tool can access. A full permissions review will help identify any weak spots before AI systems are allowed to operate, ensuring the data is properly secured.

4. Prevent Potential AI Security Loopholes

Adding AI to your systems opens up new avenues for potential attacks. Hackers could try to exploit AI tools to access data they’re not supposed to. A thorough permission review helps you catch potential vulnerabilities by:

• Identifying any weak points that would let AI see too much.
• Ensuring that users only see what’s necessary, even if an AI tool were compromised.
• Conducting regular checks to make sure new AI functions haven’t introduced security gaps.

5. Build Trust and Maintain Data Integrity

When employees and customers know that security measures are tight, they’re more likely to trust the systems in place. A detailed review of permissions and security settings shows a commitment to protecting data. This also helps to prevent accidental changes to critical information, ensuring data accuracy.

By regularly assessing permissions and tightening security, organizations not only protect sensitive information but also foster trust across teams, clients, and partners.

Key Steps for Conducting a Comprehensive Permission and Security Assessment

• Inventory Permissions: Catalog all user roles, permissions, and system access points across applications.
• Implement Role-Based Access Control (RBAC): Assign permissions based on job roles, ensuring that users have the least privilege necessary.
• Enforce Attribute-Based Policies: Use attributes (like location, time, and device) for a more dynamic and secure access model.
• Regular Audits and Reviews: Continuously assess permissions and security settings to catch potential vulnerabilities as systems evolve.
• Simulate AI Interactions in Testing: During testing phases, simulate AI-powered interactions to identify any potential security gaps in how AI tools interact with hidden or sensitive data.

As organizations start using powerful AI tools like ChatGPT and Copilot, securing permissions and access controls isn’t optional—it’s essential. Relying on hiding elements is a risky shortcut in today’s AI-enabled world. Instead, organizations should proactively review permissions and set up strong security policies.

By doing so, they’ll protect sensitive information, maintain compliance with privacy laws, reduce security risks, and create a trusted environment where AI can work safely and effectively. With a solid foundation of access control, companies can embrace AI’s potential without compromising security.