Generative AI is already in your business, often through tools employees picked themselves. That “shadow AI” can boost productivity, but it also creates real risks around data leakage, compliance, and accuracy. This post walks Milwaukee SMBs through what shadow AI is, why it matters, five starter rules for a one-page AI acceptable-use policy, and how to turn that policy into real-world practice with training and technical controls.
Shadow AI at Work- How to Write…
TL;DR:
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Most employees are already using AI at work, often through unapproved tools and browser extensions, aka “shadow AI.”
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Shadow AI isn’t automatically bad, but it can leak client data, create compliance headaches, and produce unchecked outputs when there’s no policy or oversight.
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You don’t need a 40-page legal document; you need a one-page, plain-English AI acceptable-use policy everyone can understand.
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A simple starter policy covers: treating AI like sending data outside the company, keeping sensitive data out of prompts, using AI for drafts (not final answers), sticking to approved tools, and asking when in doubt.
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To make it real, inventory current usage, pick a short “green list” of tools, add light technical controls, train with examples, and review the policy at least once a year.
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Stamm Tech can help Milwaukee teams discover shadow AI usage, draft an AI policy, configure controls in Microsoft 365/Google Workspace, and deliver practical training.
Generative AI is already in your business, whether you’ve “rolled it out” or not.
Surveys show that roughly three-quarters of workers are using AI at work, and many are doing it through public tools they picked themselves.
Gartner estimates that by 2030, 40% of enterprises could experience security or compliance incidents caused by “shadow AI”, AI tools used without approval or oversight.
For Milwaukee SMBs, that’s both good and bad news:
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✅ Good: Your people are trying to be more efficient.
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❌ Bad: Company and client data may be flowing into tools with no guardrails.
You don’t need a 40-page policy to fix this. You need one clear page everyone can understand.
What is “shadow AI”?
“Shadow AI” is when employees use AI tools for work without:
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Clear approval
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A written policy
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Any technical controls around what data is allowed
Examples:
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Dropping a customer proposal into a public chatbot to “clean up the wording”
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Asking AI to summarize an internal report that includes financials or PHI/PII
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Using browser extensions or plugins that quietly send data to third parties
None of these are automatically evil, but they’re risky when no one knows what’s being used or what’s going in.
Why it matters for small and mid-sized businesses
Big enterprises have AI task forces, legal teams, and data governance committees. Most SMBs have:
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A small IT team (or outsourced MSP)
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A handful of line-of-business apps
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People just trying to get work done
That mix makes a few risks stand out:
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Data leakage: Client names, financials, or internal strategy docs pasted into tools that store prompts.
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Compliance trouble: Healthcare, legal, finance, and manufacturing IP can all fall under specific regulations or contract language.
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Bad outputs with no review: Employees treating AI drafts as “finished” without checking accuracy.
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No audit trail: Leadership doesn’t know which tools are in use or what data they’ve seen.
he goal isn’t to ban AI. It’s to use it on purpose, not by accident.
Start with five simple questions
Before you write a single sentence of policy, answer these internally:
- Where are people already using AI?
Email, documentation, proposals, coding, customer communications, etc.
- What types of data are “off limits”?
Client names, account numbers, patient data, HR info, pricing models, etc.
-What tools are approved?
Internal AI features in Microsoft 365/Google, or licensed tools hosted in known locations.
-Who owns the policy?
Someone in leadership, IT, and (ideally) legal/compliance.
-How will you explain this in plain English to staff?
No one reads dense policy PDFs. This needs to fit on a one-pager and in a quick training.
A one-page AI acceptable-use starter
Here’s a simple, human-readable starting point you can adapt:
1) Treat AI like sending data outside the company.
If you wouldn’t email it to someone outside your organization, don’t paste it into AI.
2) Keep sensitive data out of prompts.
No client names, account numbers, medical details, HR issues, or confidential financials in public tools.
3) Use AI for drafts, not final answers.
AI can draft emails, summaries, and ideas. A human owns the final version.
4) Stick to approved tools.
Use only the AI tools listed by IT/leadership. If you want to try something new, ask first.
5) When in doubt, ask.
If you’re not sure whether something is safe to paste into AI, stop and check with IT or your manager.
That’s it. One page. Realistic. Enforceable.
Turning policy into practice
A written policy is step one. Making it real looks like this:
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Inventory what’s already happening.
Have a quick, non-punitive survey: “Where do you already use AI?”
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Pick your “green list” tools.
Start with AI built into platforms you already use (Microsoft 365, Google Workspace, CRM, etc.).
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Adjust technical controls where it makes sense.
Use browser controls, data loss prevention (DLP), and account restrictions on especially sensitive systems.
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Train with examples, not fear.
Show real-world “good vs. bad” prompts. Make it clear you’re pro-AI, just with guardrails.
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Review it annually.
AI is changing fast. Commit to revisiting your policy at least once a year.
Where Stamm Tech fits in
For Milwaukee-area teams, we can help you:
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Map out where AI is already showing up in your environment
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Draft a simple, one-page acceptable-use policy tuned for your industry
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Configure technical controls in Microsoft 365, Google Workspace, and key business apps
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Provide ongoing training so your team knows how to use AI safely
AI isn’t going away. The question is whether you’ll let it grow in the shadows or bring it into the light with clear, practical guardrails.
If you’d like help turning this into a one-pager for your staff, we’re here.
FAQ
Q1: What is “shadow AI” in simple terms?
Shadow AI is when employees use AI tools (like public chatbots, browser extensions, or unapproved apps) for work without any official approval, policy, or oversight.
Q2: Why is shadow AI risky for small businesses?
Because sensitive data like client details, financial information, and strategy docs can end up in tools where you don’t control how it’s stored, shared, or used. That can create security, privacy, and compliance problems.
Q3: Is the answer to just block all AI tools?
Usually no. Employees are using AI because it helps them. A blanket ban just pushes usage further underground. It’s better to approve a small set of tools and define what they can and can’t be used for.
Q4: What should absolutely never go into a public AI tool?
Anything you’d be uncomfortable seeing in the wild: client or patient identifiers, account numbers, credentials, confidential financials, HR info, non-public legal details, or proprietary designs and code.
Q5: How can we tell which AI tools are “safe”?
Look at where they store data, how long they keep prompts, who owns the platform, and whether they offer enterprise or compliance features. Work with IT and legal. Don’t rely only on marketing pages.
Q6: Do we really need a written AI policy?
Yes. With most workers either using or planning to use AI at work, a written policy sets expectations, protects the business, and gives employees clarity instead of mixed messages.
Q7: How can Stamm Tech help with AI governance?
We help you discover current usage, set up practical rules, configure technical controls, and deliver plain-English training so your team uses AI safely and confidently.