AI security risks IT leaders need to understand and act on

What type of AI security risks can affect a business?

Not all AI is created equal—different types of systems come with different risks. It’s important to understand how each one can expose your business to potential vulnerabilities if left unchecked.

Here are three common categories of AI that can introduce risk:

• Generative AI—tools that create content, summaries, or responses, often pulling from a wide range of data sources
• Traditional AI—machine learning models trained for specific tasks like fraud detection or workflow automation
• Predictive AI—systems that analyze data to forecast outcomes, like demand, behavior, or performance trends

Each of these tools can add value—but when they’re not backed by the right security framework, they can create real exposure. Here are the biggest risks businesses should be watching for.

1. Data exposure and unauthorized access

AI tools touch a lot of information. Without strict access controls, sensitive data can land in the wrong place—fast. That could mean customer records, financial reports, or internal HR files showing up where they shouldn’t.

Picture this: an AI tool generates a customer-facing message… using content from an internal financial forecast. It’s not just awkward—it’s a critical failure in access governance.

The result? Exposure of confidential data, loss of trust, and potentially, serious legal consequences. These aren’t rare edge cases—they’re entirely preventable with the right controls in place.

2. Compliance violations and regulatory penalties

AI doesn’t get a free pass on compliance. Tools that handle personal data must follow the rules—whether it’s GDPR, HIPAA, SOC 2, or CCPA. But many AI systems weren’t designed with compliance in mind.

That means even one mishandled dataset can lead to fines, customer backlash, or worse: a long-term hit to your brand’s credibility.

Staying compliant means using tools that are secure by design—not just patched together for enterprise use.

3. Model misuse and hallucinations

AI isn’t always right—sometimes, it makes things up entirely. Often called an AI hallucination, this can lead to embarrassing, inaccurate, or even legally risky outputs.

The MIT Technology Review reported on a story in 2024 about Google’s AI Overviews feature, where users were suggested to “add glue to pizza” and “eat at least one small rock a day”. It’s easy to see how this can cause issues!

For example, using AI to summarize a report might make up a stat or quote material that shouldn’t be public. This kind of mistake can damage reputation, cause miscommunication, or even result in legal trouble.

4. Lack of IT oversight

When people start using AI tools on their own—without telling IT leaders—it creates shadow AI. It’s great to use AI—but if the tools aren’t vetted, there’s no guarantee they meet your security standards.

Moreover, shadow AI means the tools and any data a user inputs can fly completely under the radar. It’s a headache you can avoid by simply having established AI tools and best practices in place already—so everyone is aware.

Poor IT oversight can result in people making unauthorized data transfers or using unvetted platforms, and it provides no clear accountability—a perfect storm for all kinds of other risks and compliance headaches.

AI can help—but only when it’s used within clearly defined, IT-managed systems that protect visibility and control.

These risks are real—but with the right practices and policies in place, they’re completely manageable. In the next section, we’ll break down how IT leaders can reduce exposure and keep AI use secure—plus how Dropbox Dash helps make it happen.

Best practices to avoid AI security risks

You’re probably eager to leverage AI to enhance your team’s productivity—but it’s only worth doing if it’s securely integrated. Fortunately, there are practical ways to keep AI tools in check—without slowing your teams down.

Here are four best practices IT leaders can use to minimize risk and stay in control:

Strong access controls and role-based permissions

The risk: Without clear boundaries, AI tools might give employees access to data they shouldn’t see—like sensitive reports or internal communications.

Our fix: Dropbox Dash offers granular access controls, bulk permission management, and role-based policies that apply across your AI-powered workflows. You stay in control of who can access what—no exceptions.

Use secure AI models that align with compliance standards

The risk: AI still has to meet your industry’s compliance standards. If your tools don’t comply with GDPR, HIPAA, SOC 2, and any other relevant regulations, you’re looking at serious fines—and huge stress for your security team.

Our fix: Dash is built with compliance in mind. AI-powered universal search, summaries, and answers all follow the same strict standards—so your content stays protected and audit-ready.

Regularly monitor AI activity and audit trails

The risk: If you’re not tracking AI activity, it’s hard to tell if someone’s misusing the tool or accessing data they shouldn’t. This leads to a lack of IT oversight, one of the biggest risks AI can pose to an organization.

Our fix: Dash’s admin console gives you complete visibility over usage, permissions, and connected tools. You can export logs, monitor behavior, and integrate with SIEM systems to keep oversight centralized.

Prevent AI hallucinations with human oversight

The risk: AI-generated responses aren’t always perfect—they can be inaccurate, biased, or just plain wrong. It can seem like a joke at times, but think of Google’s AI Overview issue—something like that could be a threat to life!

Our fix: Dash grounds its summaries and answers in permissioned content only—so nothing comes out of thin air. And with human review and usage policies in place, you’re not relying on AI alone to get it right.

With access control, real-time visibility, and compliance built into the foundation, Dropbox Dash helps IT teams unlock AI’s benefits—without inviting unnecessary risk.

Frequently asked questions

What are the biggest AI security risks for businesses?

The biggest AI cybersecurity risks for businesses include data exposure, unauthorized access, compliance violations, model misuse, and lack of IT oversight. Left unmanaged, these risks can lead to data leaks, fines, and other major headaches. That’s why visibility and strong governance are essential.

How can IT teams ensure AI-powered tools remain secure?

It starts with tight access controls, strong compliance alignment, and real-time monitoring. You’ll need tools that let you control who can access AI-generated content, monitor file interactions, and help keep everything audit-ready.

Tools like Dropbox Dash centralize oversight through admin consoles—so you’re not chasing permissions or usage logs across disconnected systems.

What are best practices for preventing AI data leaks?

A few tried-and-true tips are setting role-based permissions so AI can’t access sensitive data it doesn’t need, using tools with built-in compliance standards (like SOC 2 or GDPR), and reviewing AI outputs before sharing externally. It’s advisable to monitor and log AI activity too—so there’s always a trail.

Regular risk assessments are also a fantastic best practice to manage AI risks and those posed by other cyber threats like malware, phishing, and other new or emerging adversarial attacks.

Stop real AI risks from getting in your team’s way—try Dash

AI can supercharge productivity—but only if security is built in from the start. Dropbox Dash gives you enterprise-grade safeguards, full visibility, and the control IT teams need to scale AI safely.

The result? A smarter, faster workflow your teams can trust—no trade-offs, no headaches.