Your Team Is Already Using AI, So How Can You Manage the Human and Vendor Risk?

While businesses debate AI adoption policies, their employees have already decided. They’re linking ChatGPT to company drives, uploading files to AI tools, and creating workarounds they hope satisfy compliance. The real question isn’t whether your team uses AI, but whether they’re doing it safely and with your knowledge.

Picture this: you’re adding a work document to your personal ChatGPT account for a quick analysis when a prompt appears: “Connect to Google Drive for enhanced functionality?” Your cursor hovers over the button. You think about what’s stored there: client proposals, financial projections, maybe that salary spreadsheet from last year’s review cycle.

That hesitation? That’s your instinct warning you about a decision millions of employees make daily, often choosing convenience over caution. And if you’re thinking “my team would never do that,” I have news that might change your mind.

Here’s your quick read brief:

  • Workers are already using AI tools without their employer’s knowledge
  • Shadow AI appears in nearly every business we examine, regardless of size or industry
  • Even “secure” platforms can fail: vendor promises aren’t guarantees

The AI Already Inside Your Walls

Seven out of ten workers using ChatGPT at work hide it from their employers, making it the fastest-growing shadow IT application in history (Josys, 2024; IT Brew, 2024). Think about that for a moment. In your 50-person company, that could mean 35 employees secretly using AI right now.

Your marketing team uploads campaign materials to AI design tools without checking data policies. Sales feeds customer lists into AI prospecting platforms. Finance experiments with AI-powered expense tools that don’t just process your data but train on it.

The WeTransfer revelation perfectly captures this risk. Users discovered the file-sharing service now claims rights to use uploaded content for AI training. How many client files moved through WeTransfer this week because someone needed to share something too large for email?

Think about your teams. Legal departments using AI for research might include confidential client details in their prompts “for context.” Finance teams upload invoices to AI expense tools without realizing they’re training someone else’s model on vendor relationships and spending patterns. I see this weekly in conversations with business owners who discover these practices during routine security reviews.

People aren’t just doing this because they can. The pressure driving this underground adoption is real. When managers demand doubled productivity without additional resources, employees turn to AI. When official channels provide no guidance or flatly ban these tools, people find their own solutions. By forcing AI underground, organizations lose visibility, control, and the opportunity to implement it safely.

Good Intentions, Dangerous Results

Healthcare workers swap patient names, thinking that ensures HIPAA compliance. A colleague recently asked me this, genuinely believing they’d found a compliant solution. They hadn’t considered that dates, locations, unique conditions, and even writing patterns can identify patients. AI systems excel at connecting these dots, potentially re-identifying “anonymous” data later.

This knowledge gap between AI’s capabilities and user understanding creates massive vulnerabilities. Employees think AI tools process only what you explicitly provide. But if you connect an AI to Google Drive, it can spider through years of documents, shared folders from old projects, and files you forgot existed.

Team ChatGPT subscriptions have different security provisions than individual accounts. Business plans may promise not to train on your data, but terms change. Companies merge. Today’s promise becomes tomorrow’s fine print. Most employees don’t understand that “linking” means giving AI access to everything they can see, creating risks they never imagined.

Why “Secure” Doesn’t Mean Safe

Remember when giants like Target, Marriott, and Equifax were hacked? Each had sophisticated security teams, compliance certifications, and reassuring security pages. Each suffered breaches that made headlines and cost millions.

So when business owners show me their AI vendor’s security page and say things like “Look, they’re SOC 2 compliant!”, I can’t help but think about the list I keep of 20+ major companies with stellar security promises that got hacked anyway.

There are two categories of AI risk which require different approaches:

Cloud-based AI sends your data to systems you don’t control. Platforms may claim not to train on your data, but several businesses have already discovered their innovations appearing in competitors’ AI-generated content. Once uploaded, you’ve lost control.

Internal AI tools seem safer but hide different dangers. These systems can access everything users can reach. Without proper segmentation, an AI scheduling assistant might discover access to financial records or strategic plans. AI doesn’t respect the informal boundaries humans understand.

The question isn’t what vendors promise but what happens when those promises break. Target, Marriott, and Equifax had sophisticated security teams and compliance certifications. If they couldn’t prevent breaches, why trust a startup AI company’s marketing page?

Turn Shadow AI Into Strategic Advantage

So your employees haven’t waited for an official AI use policy, and every day without guidance increases potential risks. Panicking helps nobody, so here’s the practical steps you can take to get AI under control in your organization:

Start with discovery, not judgment. Don’t ask “Are you using unauthorized AI?” Instead, try “What tools have you found helpful for productivity lately?” The results often surprise even experienced IT leaders, revealing everything from ChatGPT to specialized industry AI platforms. With an open approach, you may just stumble on your next productivity game-changer.

Create practical policies. Banning AI entirely is unrealistic and staff will likely ignore it. It’s better practice to establish approved tools with clear use cases. Explain not just what’s restricted but why. When employees understand that uploading documents might mean competitors can access them later, they’ll make better decisions.

Become enablers, not blockers. When employees request AI tools, explore what problems the tools are solving for them. What approved alternatives exist? How can you implement AI safely while maintaining productivity? Smart organizations create AI Centers of Excellence: cross-functional teams that evaluate tools, establish guidelines, and champion safe adoption.

Train with real examples. Generic security training fails because it feels irrelevant. Use actual scenarios if you have them, for example like assuming fake names will ensure compliance, or uploading invoices for AI analysis may lead to training a competitor’s model years later.

Implement technical safeguards. Network segmentation prevents AI from accessing everything. Access controls limit exposure. Monitoring systems detect unusual data movements. For example, if an employee asks about executive salaries, properly configured systems prevent AI from finding that information.

Build AI Frameworks for Security and Productivity

Shadow AI isn’t theoretical. It’s operating in your business right now. While you’re reading this, employees are making security decisions with limited understanding and unlimited AI access.

The businesses succeeding with AI aren’t necessarily the early adopters. They’re the ones who moved thoughtfully, balancing opportunity with security. They turned shadow AI into a strategic advantage by acknowledging it and responding intelligently. You can pretend your employees aren’t using AI and hope luck holds, or you can build frameworks for safe and productive use.

Remember, when it comes to AI and IT security, what you don’t know can hurt you. But what you acknowledge and address can transform your business.

Address AI Risk

Have concerns about Shadow AI in your organization? Sagacent helps businesses discover their AI footprint and implement secure alternatives. Contact Sagacent Technologies to schedule an AI consultation. [https://sagacent.com/schedule-a-consultation/]

Glossary of terms:

Shadow AI: Employees using personal or unauthorized AI tools for work tasks without IT knowledge or approval

AI Hallucination: When AI generates false but convincing information, presenting fiction as fact

Data Residency: The physical location where your data is stored and processed, determining which country’s laws apply

Extra reading cited in newsletter:

#AISecurity #ShadowIT #BusinessProtection #DataSecurity