TL;DR: Your 75-person company doesn't need a 200-page compliance manual. But you do need a one-page acceptable use policy, a simple data classification guide, and someone who can answer questions. Start there. Governance at your size is about enabling safe adoption, not preventing it.
The Governance Disconnect
When most people hear "AI governance," they picture mahogany conference rooms, 200-page policy documents, and a whole department whose job is saying no to things. That's what governance looks like at Fortune 500 companies. That's not what it looks like for you.
I spent years designing AI governance frameworks at a regulated professional services firm where we had compliance teams, audit trails, and enough red tape to choke a horse. But here's what I've learned since: the principles that made that work are actually simpler when you're smaller, not harder.
The problem is that most small business owners either assume they don't need governance at all, or they try to copy the enterprise playbook and end up creating processes so bureaucratic that nobody follows them. Both approaches are mistakes.
You need governance. It just needs to be right-sized.
Why Governance Matters When You're "Just Using ChatGPT"
Let me be direct: your employees are already using AI tools. Studies consistently show that 50-70% of workers use AI tools at work without their employer's explicit knowledge. That's not a judgment — it's reality.
Here's where it gets risky. Without guidelines, someone will eventually paste client data into ChatGPT. Or your Q&A. Or financial information from your last budget review. Or that proposal that includes intellectual property you can't afford to lose. They won't do it maliciously. They'll do it because it's convenient and because nobody ever told them not to.
If you're in any regulated industry — financial services, anything healthcare-adjacent, professional services — the stakes are higher. Regulators expect you to have some documented approach to data handling, even if you're small.
But here's the thing that usually gets overlooked: governance is not about control. It's not about making it harder for your team to do their jobs. Good governance is about making it safe for them to use AI confidently, without constantly wondering whether they're about to get the company sued.
That's worth doing right.
The Minimum Viable Governance Framework
You don't need to boil the ocean. Here's what you actually need on day one:
An Acceptable Use Policy (1-2 pages, maximum)
This answers three questions: What tools are approved? What data can and can't go into AI tools? Who do people ask when they're unsure?
That's it. Keep it short enough that people will actually read it. A 30-page document sits in a drawer. A one-pager goes on a slack channel and gets referenced.
A Data Classification Guide
Create three simple buckets:
- Public: Information that's already public. Use any tool you want.
- Internal: Information that's yours but not confidential. Use only approved enterprise tools (like Copilot or Claude for Work, where your data isn't fed into training models).
- Confidential: Client data, employee information, financial details, anything covered by NDA or regulation. Never put this in an AI tool, period.
Give two or three examples in each category so people actually understand it. "Client financials" is more useful than "sensitive business data."
An Approved Tools List
Name the specific tools your team is allowed to use. Update it quarterly. The tools change fast enough that this list will be outdated before you know it, but having a list removes ambiguity. People know what they're supposed to use.
A Point Person
Someone your team can ask questions to. Doesn't need to be a full-time role. Could be your operations manager, your tech-savvy admin, or whoever you trust to learn this stuff. Someone people can ping and say, "Hey, can I use this tool for this?" and get an answer in under an hour.
That's your governance framework. You're welcome to add more, but that foundation will handle 90% of your needs.
Writing a Policy People Will Actually Follow
Here's where most governance frameworks fail: they're written by lawyers for lawyers, and nobody else reads them.
Your policy should be two pages. Use plain English. Say "Don't paste client information into ChatGPT" instead of "Confidential data shall not be processed by unauthorized AI systems." Real people will read the first one.
Give specific examples. Talk about what people can do, not just what they can't. Most people respond better to permissions than prohibitions. Tell them: "You can brainstorm project ideas in ChatGPT, draft emails, ask research questions, create meeting notes." That's more useful than just saying "don't do bad things."
Review it every six months. The AI landscape changes too fast to set it and forget it. New tools emerge. Your risk profile changes. Your team learns what works. Update the policy to reflect reality.
Data Handling Basics: What to Feed AI and What to Keep Out
This is the practical stuff. Let's talk about what actually goes into those categories.
Safe to use with any AI tool: Publicly available information, general templates, your own draft writing, brainstorming sessions, research questions, publicly available competitor analysis.
Caution — use enterprise tools only: Internal processes and procedures, proprietary methods that aren't obvious, non-confidential client names, general project timelines, anything that's yours but could give a competitor an advantage if they knew it.
Never put into AI: Client data of any kind, employee personal information (names, addresses, Social Security numbers), financial account numbers, details from contracts, anything covered by an NDA, anything regulated (HIPAA, GDPR, state privacy laws), legal documents, passwords or credentials.
Here's my rule of thumb: If you wouldn't paste it into an email to your entire company in the break room, don't paste it into a public AI tool. Your employees can see an all-company email. So can strangers if Anthropic or OpenAI decides to use it for training.
Governance That Grows With You
Start with the minimum framework I outlined. Really. Don't overthink this.
Then add complexity only as your AI usage actually matures. After a few months, you might realize you need a tool for image generation, or you're using AI heavily enough that you want a tool usage log. Add those things then.
Revisit your policy every quarter in the first year. The tools are changing fast. Your team is learning. You'll discover use cases you didn't anticipate. Build governance for the AI adoption you actually have today, not the adoption you think you should have.
The biggest mistake I see is governance that's so restrictive nobody follows it. A policy that says "AI is only for executives with written approval" is worse than no policy at all, because now your team is just going around you anyway — only now they're doing it in secret.
Governance should enable adoption. It should make people feel confident that they can use these tools. That's the goal.
The Real Conversation
Governance sounds heavy. Compliance sounds like a buzzkill. Policy sounds boring.
But what we're really talking about is this: "How do we use these tools responsibly so everyone on our team feels confident they're not about to create a problem?"
That's a conversation worth having. And it doesn't take a Fortune 500 budget. It doesn't take a dedicated department. It takes an afternoon with your leadership team and maybe a few hours to write it down.
The Midwest doesn't need more complexity. We need clarity, practicality, and permission to move forward. That's what good governance gives you. Learn more about how we help companies implement this, or take our assessment to identify where governance fits into your broader AI strategy.
