Summary
This post addresses the gap between employee AI tool use, which is already happening in nearly every Gulf Coast business, and the near-total absence of written AI policies. It covers three things a policy needs to include: rules on what data cannot be pasted into public AI tools or recorded by meeting assistants, a review step for AI-generated work before it goes out, and a documented standard for consistent enforcement. Closes with a call to book a Risk-Free Strategy Session.
By: Jordan Gerheim, CEO – Outside Chief Legal LLC
By the time most Alabama business owners get around to writing an AI policy, employees have already been using AI tools for months. ChatGPT, Copilot, Gemini, and other tools are sitting in browser tabs on nearly every laptop in the building, whether or not anyone approved it.
That gap between what employees are actually doing and what the business has decided about it is where the risk sits. Not because AI tools are dangerous on their own, but because nobody has written down what is allowed, what is not, and what happens to the information an employee types into one.
This is not just a large-company problem. A five-person landscaping crew, a ten-person medical practice, and a two-hundred-person manufacturer are all dealing with the same issue. The tools are fast, easy, and built into the way people work, so employees use them the way they use search engines, often without stopping to ask whether anyone approved it.
Here are three things an AI policy needs to cover, and what happens when they are missing.
1. What Employees Can and Cannot Paste Into a Public Tool
The immediate risk is not the AI tool itself. It is what an employee pastes into it to get a faster answer.
A public AI tool is not a secure or private workspace. Depending on the tool and its settings, information typed into it can be stored, used to train future versions of the model, or reviewed by the company that runs it. Client names, contract terms, financial figures, and employee records typed into a free AI tool to save time can end up outside the business entirely, with no way to pull them back.
A Baldwin County property management company had an office assistant paste a tenant dispute email chain into a free AI tool to draft a response faster. The chain included another tenant’s payment history and a settlement figure from an unrelated matter. None of that was meant to leave the office, but the business had no policy telling the assistant what was off-limits.
A written policy that identifies what cannot be entered into a public AI tool, including client data, financial records, employee information, and any confidential information covered by a confidentiality agreement, gives employees a clear line instead of a judgment call they are not equipped to make on their own.
The same issue shows up with AI meeting assistants that automatically record and transcribe calls. A tool set to join every meeting by default will happily record a conversation with your attorney, a sensitive personnel discussion, or a call where pricing strategy is discussed openly. Once that transcript exists, it lives outside the room where it was spoken, and a policy that only talks about typed prompts misses the problem entirely.
2. Who Reviews AI in the workplace Before It Goes out
AI tools are fast at producing a first draft. They are not reliable at getting every detail right, and they will state incorrect information with the same confidence as correct information.
The risk shows up when AI-generated content goes out the door without a human checking it first. A marketing email with the wrong price. A client-facing summary with a fact the tool invented. A contract clause pulled from a generic template that does not match how the business actually operates. Each one looks polished, which is exactly why it gets missed.
A Mobile-based home services company used an AI tool to draft responses to online reviews. One response included a specific guarantee about response time that the company did not actually offer. A customer held the business to it, and the back-and-forth cost more in customer service time than writing the response by hand would have taken.
A policy should say plainly that AI-generated content is a draft, not a finished product, and name who is responsible for reviewing it before it reaches a client, vendor, or the public.
That review step matters just as much for internal documents as it does for client-facing work. An AI-drafted employee memo, a summary of a vendor contract, or a set of meeting notes can all contain small errors that carry real weight later, especially if someone relies on that document as an accurate record of what was agreed to or decided.
3. What Happens Without a Written Rule
When there is no AI policy, every decision about how to use these tools gets made individually by whoever happens to be using them that day. That inconsistency creates its own risk.
If an employee is disciplined for something related to AI use, a data exposure, a mistake in client-facing work, or time spent on personal projects during work hours, the business needs a documented standard to point to. Without one, the conversation becomes about whether the rule was fair rather than whether it was followed, because there was no rule to follow.
A restaurant group with locations across Baldwin County ran into this directly. A manager used an AI tool to draft a termination letter for an employee, and the letter included language about performance issues that had never actually been discussed with that employee in writing. The termination was contested, and the business had no policy on AI-drafted employment documents to show it had a consistent process. What should have been a routine termination turned into a drawn-out dispute.
The businesses handling this well are not banning AI tools outright. They are writing down what responsible use looks like, walking employees through it once, and updating it as the tools change. That is a shorter project than it sounds like, and it closes a gap sitting in nearly every Gulf Coast workplace right now.
Putting a Policy in Place
An AI use policy does not need to be long to work. It needs to name what information cannot go into these tools, who reviews AI-generated work before it goes out, what meetings and conversations are off-limits for recording tools, and what happens when the policy is not followed.
It also needs an owner. Someone in the business should be responsible for updating the policy as new tools show up and as the ones already in use change their settings or terms. AI tools are updated constantly, and a policy written once and never revisited will fall out of date faster than most other workplace policies.
If the business does not have one yet, that is not unusual. Almost none do right now. But the businesses that put a policy in place before something goes wrong end up in a far better position than the ones writing their first policy after an incident forces the issue.
A written policy also gives employees something they usually want and rarely get: a straight answer. Most employees are not trying to create risk when they use an AI tool at work. They are trying to move faster on a task with tools that are already part of how they work outside the office. A clear policy tells them where the line is instead of leaving them to guess, which protects the business and removes the guesswork for employees at the same time.
A Risk-Free Strategy Session with OCL is a practical way to start. We look at how the team is actually using these tools today and help put a policy in place that matches how the business really operates.
Book your session at outsidechieflegal.com.
General information, not legal advice.
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