Privacy and Security Considerations for Gen AI in Manufacturing

The Power of AI Comes with Hidden Risks

Generative AI is revolutionizing how manufacturers design products, manage production, and optimize workflows. But behind the promise of efficiency and automation lies a growing concern — data privacy and security.

As AI tools become deeply embedded in business systems, manufacturers must understand not only what AI can do, but also what data it can see. When sensitive intellectual property, proprietary formulas, or client data flow through AI tools, the stakes are high.

The Danger of Free AI Tools in a Business Environment

Free generative AI platforms like ChatGPT, Gemini (free tier), or Claude are powerful — but not private.
When employees use these public tools for work, they may unintentionally expose business-sensitive information that becomes part of the AI’s training data.

Why Free AI Tools Are Risky for Manufacturing

  • No control over data retention: Inputs may be stored and used to train public models.

  • No compliance guarantees: These tools don’t meet manufacturing standards such as ISO 27001, ITAR, or CMMC.

  • No audit trail: There’s no visibility into what employees are sharing or where the data goes.

  • No enterprise security controls: Administrators can’t monitor or restrict use.

Imagine an engineer pasting a portion of a confidential CAD design into a free AI tool to “get suggestions.” That data is now out of your hands — and possibly in the public model’s dataset forever. This could mean you no longer own any rights to your intellectual property.

Insider Risks in Business-Level AI Tools

Even when organizations upgrade to enterprise-grade solutions such as ChatGPT Business, Microsoft Copilot or Google Gemini for Workspace, security risks can persist.

These business AI tools can integrate directly with company data — SharePoint, OneDrive, Teams, Gmail, and Drive. They don’t create new data risks by themselves, but they magnify existing permission settings. If those permissions are misconfigured, the results can be disastrous.

AI Reflects Your Access Model

  • Copilot: Pulls content from SharePoint and Teams. If those folders are set to “Everyone,” Copilot can surface HR documents or financial data to anyone.

  • Gemini: Reads data from Drive, Docs, Sheets, and Gmail. Misconfigured sharing settings can expose project blueprints, client contracts, or proprietary research.

AI doesn’t break your permission system — it exposes it.
The more connected your organization becomes, the higher your risk if access controls aren’t carefully designed.

How Misconfigured Permissions Lead to Data Exposure

Picture this:
A manufacturing operations manager asks Gemini to “summarize all vendor contracts.” The AI complies — but unknowingly pulls data from folders that include confidential pricing, HR information, and partner agreements, simply because they were left visible to “All Internal Users.”

The result?
A single prompt can inadvertently reveal private information that would normally take deliberate effort to access.

🎧 Listen to our team discuss how AI can unintentionally widen access to sensitive manufacturing data.

In this episode, we dive deeper into how AI tools can unintentionally expand access to sensitive company data — and what manufacturing leaders can do to prevent it.
Who Has Access to Your IP When Using AI?
  • 15 min
Who Has Access to Your IP When Using AI?
Shift Change: The Idaho Manufacturing Podcast
Play

AI safety doesn’t come from blocking innovation — it comes from building the right guardrails around it. The key is to secure the networks, devices, and users that power AI interactions — without slowing productivity.

Securing Generative AI in Manufacturing

To safely leverage generative AI, manufacturers need more than good intentions — they need a layered security framework that protects data wherever it travels.

AI tools thrive on access. That’s why securing AI isn’t just about locking things down — it’s about creating controlled visibility. You should be able to see who is accessing what, from where, and ensure every interaction is logged, encrypted, and verified.

A Modern Security Framework for AI Adoption

Here’s how manufacturers can build that foundation:

  1. Establish Unified Network Security Controls
    Centralize protection across all locations, devices, and users — whether on-site or remote — using a single cloud-based platform that enforces consistent security and access policies.

  2. Adopt a Zero Trust Approach
    Don’t assume trust inside your network. Validate every user and device before granting access to sensitive systems, AI tools, or company data.

  3. Enhance Endpoint Protection & Visibility
    Use advanced endpoint monitoring to detect unauthorized data movement, risky AI usage, or potential exfiltration from local devices.

  4. Implement Continuous Threat Detection & Response
    Pair AI innovation with intelligent monitoring that identifies anomalies — like unexpected data queries from Copilot or Gemini — in real time.

  5. Segment and Control Access to Sensitive Data
    Apply least-privilege access principles so employees can only interact with the information necessary for their roles. This prevents AI tools from reaching across silos unintentionally.

  6. Secure Data in Motion and at Rest
    Encrypt traffic between users, applications, and cloud systems. Protect sensitive files within storage, collaboration, and AI analysis environments to prevent leaks or misuse.

This kind of layered security approach gives manufacturers confidence to innovate with AI — while maintaining compliance, visibility, and control over every byte of business data.

Partner with Experts Who Secure the Foundation for AI

Adopting generative AI in manufacturing isn’t just about choosing the right tools — it’s about ensuring your infrastructure is ready to support them securely. That’s where TotalCare IT comes in.

Our team helps manufacturers build the secure groundwork needed to deploy AI confidently, without risking data exposure or compliance violations. From the cloud to the factory floor, we ensure your systems, users, and policies work together safely.

How We Help You Secure Your AI Environment

  • Infrastructure Hardening
    We assess and secure every layer of your environment — from network access to cloud configurations — to ensure your AI tools operate on a protected foundation.

  • Permission & Access Governance
    We audit and correct user permissions within Microsoft 365, SharePoint, and Google Workspace to prevent unauthorized AI data exposure.

  • Zero Trust Implementation
    We apply identity-based access controls that verify every connection before granting access, ensuring data stays within the right boundaries.

  • Continuous Monitoring & Response
    We provide real-time visibility into your systems and AI activity to detect and stop abnormal behavior before it becomes a breach.

  • Compliance Alignment
    Our frameworks align your AI use with industry regulations and standards such as CMMC, NIST, and ISO 27001 — keeping your operations both secure and compliant.

Before AI can transform your business, your environment must be ready to handle it securely. TotalCare IT makes sure your systems, permissions, and policies are aligned to keep data protected and accessible only to those who need it.

Secure Your Manufacturing Environment for AI Success

Whether you’re experimenting with Gemini, implementing Copilot, or exploring AI-driven analytics, TotalCare IT ensures your infrastructure is fortified — so AI empowers your team instead of exposing your data.

👉 Schedule a Discovery Call
to connect with our experts to discuss how we can help secure your digital environment for the future of manufacturing.

FAQ: Privacy & Security in Generative AI for Manufacturing

1. Is it safe for employees to use free AI tools like ChatGPT for work?

Not for sensitive or proprietary work. Free tools don’t guarantee data privacy — they may retain your input for model training, which can expose intellectual property or confidential information.

2. How do enterprise AI tools like Copilot or Gemini protect data?

They offer enterprise-grade security features — encryption, access control, and audit logging — but rely on your existing permission settings. If your SharePoint or Google Drive permissions are too open, the AI can surface unintended data.

3. What’s the biggest AI security risk for manufacturers?

Misconfigured access controls. Many organizations don’t realize that their internal file structures allow “read” access to more users than intended. When AI tools read across these repositories, sensitive data can be exposed in summaries, responses, or chat interfaces.

4. How can manufacturers reduce AI-related privacy risks?

Start with a data governance review and AI risk assessment. Ensure your identity and access controls follow a “least privilege” model, and educate employees about responsible AI use.

5. Does TotalCare IT offer AI security audits?

Yes — we provide Security & Privacy Assessments for manufacturers adopting tools like Copilot, Gemini, or ChatGPT Enterprise. Our experts analyze your configuration, identify risk exposures, and recommend mitigation steps.