AI-ready or not? Google Drive best practices recap

Google Drive AI security risks are no longer hypothetical. With tools like Gemini now embedded directly into Google Workspace, the way AI interacts with your files has fundamentally changed — and most organizations aren’t ready for it.

BetterCloud recently hosted “AI Ready or Not? Google Drive Best Practices”, a webinar digging into the real, unglamorous work that makes AI rollouts succeed or fail: file governance. 

Want to watch the recording? Catch it here.

Here’s a recap of the key takeaways for IT and security teams.

What Are the Google Drive AI security risks?

The core problem is this: AI tools like Gemini don’t just access your data. They inherit your existing permissions. Any file that was already accessible, shared with a link, shared broadly across a domain, sitting in a forgotten shared drive, is now queryable by AI.

That means Google Drive AI security risks aren’t new risks, exactly. They’re your old risks, amplified at a scale and speed that changes everything.

Three forces are making this urgent right now:

1. AI amplifies existing permission risks. Permission creep and oversharing were always problems. Now they’re active vulnerabilities. Anything shared with “anyone with the link” or broadly across a domain is fair game for AI to surface.

2. The speed of data creation has exploded. Generative AI produces content faster than any human team can review or govern. Outdated information doesn’t just sit quietly anymore. It can be retrieved, summarized, and distributed at scale before anyone catches it.

3. A new attack surface has emerged. Prompt injection attacks, shadow AI, and employees using unapproved tools with read/write access to your Drive are no longer theoretical. They’re active threats that traditional security tools weren’t designed to handle.

The biggest blind spot: Internal access

When asked what IT and security teams most often overlook, the answer was consistent: internal access.

For a long time, if data stayed within the domain, it felt safe enough. The effort required to manually find and misuse a specific file was a natural deterrent. But when a user can query Gemini and surface that same information in five seconds, “it’s internal” is no longer sufficient protection.

The threat model has shifted from can someone get through the castle walls to can someone move freely between the chambers once they’re inside.

Shadow AI compounds this. Employees logging into unapproved AI tools, often with the best intentions, and granting those tools read/write access to Drive creates blind spots that IT may have no visibility into at all. Data leakage, confidentiality breaches, compliance violations: these can happen without a single malicious actor involved.

Should you pause your AI rollout?

It’s a reasonable question, and the honest answer is: not entirely, but proceed carefully.

A full organizational pause isn’t realistic. Someone needs to be testing and learning. But a thoughtful, staged rollout makes a lot of sense. Start with higher-trust teams who can pilot AI agent integrations, understand what gets exposed, and help define governance guardrails before access is broadened.

The key principle: build a safety net that scales with your AI rollout, not one you scramble to build after something goes wrong.

That means:

• Automated scanning for sensitive content (PII, financials, IP) at the point of creation or sharing
• Policy enforcement that acts in real time, not after-the-fact audits
• User education that happens in context (“this file was blocked because it contained sensitive data”) rather than one-off training sessions people forget

What belongs in Google Drive anymore?

This one requires some honest rethinking. The old philosophy of “dump everything in the cloud” is effectively dead.

A useful guiding principle: if it’s active, collaborative, and intended for human interaction, it belongs in Drive. If it’s static, archival, or a raw system of record, it probably belongs elsewhere: in your CRM, ERP, or dedicated source-of-truth systems.

Practically, this also means getting serious about the age of your data. Files shared externally two or more years ago, with no active use case, should be unshared by default. If something is needed, it will surface again. But leaving years of stale, broadly-shared data sitting accessible to an AI is an unnecessary risk.

How to reduce Google Drive AI security risks right now

You don’t need a perfect governance framework before you act. Start here:

• Audit external sharing. Who is sharing what outside the organization, and why? MyDrive external sharing may need to be restricted entirely for certain teams.
• Apply Google Drive labels. Labeling is customizable and powerful. Combined with automated content scanning using predefined regular expressions for PII, financial data, and IP, you can start classifying your most sensitive files without manually reviewing everything.
• Set time-bound access policies. External shares older than a defined threshold should be automatically revoked. If access is still needed, it can be re-granted intentionally.
• Define your crown jewels first. You don’t need to classify every file in the organization. Start with the data that would cause the most damage if exposed, and build policy around that.
• Whitelist and blacklist AI tool integrations. If your organization has standardized on Gemini or another enterprise AI platform, consider blocking unapproved AI tools at the network level to reduce shadow AI risk.

The human side of the problem

Roughly 70% of insider threats stem from human error, not malicious intent. That reframes the problem significantly.

The goal isn’t to turn every employee into a perfect data steward. It’s to build an environment where good behavior is the default, where sensitive files can’t easily be shared publicly, where policy violations are caught automatically, and where users are educated in the moment rather than blamed after the fact.

Automation handles the scale. Education changes behavior over time. The combination is what actually moves organizations toward a self-governing environment.

Looking for more stats on file sharing? Go here.

What separates organizations that get AI right from those that don’t

The SaaS explosion offers a useful parallel. Organizations that moved fastest on SaaS adoption a decade ago got real productivity gains, but many did so without a governance plan. They’ve spent years in reactive cleanup mode ever since: security vulnerabilities, redundant spending, sprawling app inventories no one can fully account for.

We’re at the same inflection point with AI, but the stakes are higher and the timeline is compressed.

A year from now, the organizations that got AI right will be the ones who treated their data environment as a dynamic engine powering their AI strategy, not a digital attic they’re still trying to sort through. They’ll have built trust in their data and trust in their users before the chaos set in.

The ones who fall behind will be repeating the same cleanup cycle, just with AI making the mess faster than ever.

BetterCloud helps IT and security teams get visibility and control over their SaaS environments, including file governance and AI readiness in Google Workspace. If you want to dig into what this looks like for your organization, reach out to our team.