Your employees are already using AI.

They’re pasting emails into ChatGPT to “rewrite this more professionally,” feeding it snippets of proposals, or asking it to summarize long PDFs. That’s the reality in 2025.

The question isn’t “Will we use AI?”
It’s “Will we use AI in a way that protects our data, our clients, and our reputation?”

That’s what an AI policy is for.

In this playbook, we’ll walk through five practical rules you can use to govern tools like ChatGPT and other generative AI in your business—so you can capture the upside of AI without turning it into a security or compliance nightmare.

Why Your Business Needs an AI Policy Now (Not “Someday”)

Most organizations are behind the curve on AI governance:

• Employees start using AI informally long before leadership sets any rules.

• Sensitive information ends up in AI prompts without anyone realizing it.

• No one knows which tools are “approved” or how those tools handle data.

• Leaders can’t answer simple questions like, “Where are we using AI today?”

That combination—high enthusiasm, low oversight—is where companies get burned.

A clear AI policy changes that. It:

• Protects confidential and regulated data

• Reduces legal and compliance risk

• Builds client trust

• Gives your team confidence to use AI, instead of guessing what’s allowed

• Turns AI from a risky experiment into a reliable business asset

Let’s turn this into something tactical.

Rule 1: Decide Exactly Where AI Is Allowed (and Where It Isn’t)

If your only AI policy is “be smart,” you don’t have a policy.

Start by answering two questions:

1. Where do we want AI to help?

2. Where is AI absolutely off-limits?

Step 1: Map “Green Light” Use Cases

List specific, approved use cases by department. For example:

• Sales & Marketing

  • Drafting social posts, emails, and blog outlines

  • Repurposing existing approved content into different formats

• Operations

  • Summarizing internal procedures or meeting notes

  • Drafting job descriptions from provided requirements

• Customer Service

  • Drafting suggested replies (with human review)

  • Building internal FAQ drafts based on existing documentation

Step 2: Define “Red Light” Areas

Just as critical: define where AI cannot be used.

Common red zones:

• Any client confidential or regulated data (financial, medical, legal, etc.)

• Information covered by NDAs or contractual secrecy clauses

• Credentials, internal URLs, system details, or security configurations

• Anything you’d be uncomfortable seeing in the wild on the internet

Step 3: Put It in Plain Language

Your team shouldn’t need a lawyer to understand the policy. Example:

“You may use AI tools to draft content, summarize non‑confidential information, and brainstorm ideas. You may not enter client names, financial data, passwords, proprietary code, or any information covered by an NDA into public AI tools.”

Make it short, clear, and easy to remember.

Rule 2: Protect Data Every Time Someone Prompts an AI Tool

Every AI prompt is a data transfer.

If that prompt includes client details, internal strategy, or anything sensitive, you’ve just shared it with a third‑party service—whether you meant to or not.

Build a Simple Data-Protection Rule Set

At minimum, teach your team three data categories:

1. Public: Already on your website, social media, or marketing material

2. Internal: Day‑to‑day operational info that should stay inside the company

3. Confidential: Client data, financials, security details, regulated information

Then set the rule:

• Only “Public” information goes into public AI tools.

• “Internal” and “Confidential” data may only be used with approved, secured AI platforms (if you have them)—and even then, only under defined conditions.

Practical Prompts vs. Risky Prompts

• ✅ Safe Example:
  “Rewrite this paragraph from our public website to sound more conversational.”

• ❌ Risky Example:
  “Draft an email to our client, ABC Manufacturing, about their overdue invoice for $54,320 and reference their order from March 3rd.”

The second example includes client identity + financial details—that should never go into a public AI tool.

Technical Controls (Where Inman Technologies Can Help)

Policies are important, but people make mistakes. That’s where technical controls add real protection:

• Data Loss Prevention (DLP) to detect and block sensitive info leaving your environment

• Conditional access and security controls around AI tools

• Approved, enterprise-grade AI platforms integrated with Microsoft 365 or other systems

Policy + technology = real protection.

Rule 3: Keep Humans in Charge of Decisions and Output

AI is fast. Confidence is high. Accuracy is… variable.

Generative AI will:

• Invent facts

• Misinterpret nuance

• Get tone completely wrong

• Produce content that looks polished but is legally risky

That’s why your policy must state clearly:

“AI can assist, but humans remain accountable for all decisions and external communication.”

Require Human Review for Key Outputs

At minimum, require human review when AI is used for:

• Anything sent to clients or vendors

• Marketing or sales collateral

• Contracts, legal language, or compliance-related content

• Policies, procedures, and internal standards

• Reports that inform financial, operational, or staffing decisions

The reviewer is responsible for checking:

• Accuracy and completeness

• Tone and professionalism

• Legal and contractual implications

• Alignment with your brand and values

A Note on Ownership and Copyright

Laws are still evolving, but one point is clear: the more purely AI‑generated the content, the weaker your claim to unique ownership.

To reduce risk:

• Treat AI as a drafting assistant, not the final author

• Require meaningful human editing, contribution, and judgment

• Document when and how AI was used in important work

That combination makes your output more defensible and more valuable.

Rule 4: Track, Log, and Audit AI Usage

You can’t govern what you can’t see.

Most organizations have zero visibility into:

• Which AI tools are in use

• What kind of data is being entered

• Which teams are heavily reliant on AI

• Where AI-produced errors are causing rework or risk

What To Log

Aim to track, at least for your approved tools:

• Who is using AI (user or department)

• When it’s being used

• Which tools or models are used

• General purpose (e.g., “drafting emails,” “summarizing docs”)

• Any major outputs tied to important business decisions

You don’t have to log every word of every prompt to get value. Even high‑level logging gives you:

• An audit trail for compliance and disputes

• Insight into where AI is saving time—or causing problems

• Data to justify investments in better AI platforms

Centralize the Tools

Shadow AI (everyone installing their own extensions and tools) is a governance killer.

Your AI policy should:

• Define which AI tools are approved

• Block or discourage unapproved tools where possible

• Provide easy access to the official tools so people don’t hunt for risky workarounds

Rule 5: Make AI Governance a Continuous Practice

AI moves too fast for a “set it and forget it” policy.

New tools launch every week. Regulations shift. Vendors change how they store and train on user data. Your business, clients, and risk profile evolve.

Treat AI governance as an ongoing program, not a one‑time document.

Set a Review Rhythm

We recommend:

• Quarterly: Light review of AI usage, incidents, and toolset

• Annually: Full policy review with leadership, HR, legal/compliance, and IT

During each review, ask:

• Where is AI helping us the most?

• Where has AI created problems, rework, or risk?

• Do we need to update our “green light / red light” use cases?

• Are employees clear on what’s allowed?

• Have regulations or vendor terms changed?

Train, Retrain, Repeat

You can’t rollout an AI policy once, send one email, and declare victory.

Build AI into your security awareness and compliance training:

• Onboarding: Introduce AI policy and approved tools

• Annual training: Update on new risks and best practices

• Targeted refreshers: After any notable AI incident or policy change

The message should be simple:

“We want you to use AI. We just want you to use it safely.”

AI Policy Starter Checklist (You Can Use This Today)

Here’s a simple checklist you can adapt:

1. Define Purpose

   • Why are we using AI? (productivity, quality, innovation, etc.)

2. Identify Approved Tools

   • List the AI tools employees can use

   • Document where and how each tool is allowed

3. Set Data Rules

   • What can never be entered into AI tools?

   • How do we classify Public / Internal / Confidential data?

4. Clarify Human Oversight

   • Where is human review required before anything is shared externally?

   • Who is accountable for final outputs?

5. Implement Technical Controls

   • DLP, access controls, logging, and monitoring

   • Approved integrations with Microsoft 365 and other core systems

6. Establish Logging and Reporting

   • What do we track?

   • Who reviews usage and when?

7. Create a Review Cadence

   • Quarterly and annual review schedule

   • Owners for updating the policy

8. Train Your Team

   • Onboarding training

   • Regular refreshers and incident-driven updates

Even a “version 1.0” policy built around this checklist puts you miles ahead of businesses running on AI chaos.

Turning Responsible AI Use into a Competitive Advantage

AI isn’t just a shiny tool. It’s infrastructure.

Companies that win with AI will be the ones who:

• Use it aggressively—but safely

• Protect their clients’ data and trust

• Move faster because their policies are clear and their tools are aligned

If you’re a growing business in Fort Worth or anywhere in Texas, that’s where Inman Technologies comes in.

We help organizations:

• Design practical, plain‑English AI policies

• Align AI governance with cybersecurity, compliance, and existing IT standards

• Implement technical controls that back up the policy with real protection

• Train teams so AI becomes a force multiplier, not a liability

If you’re serious about putting AI to work—without losing control of your data or your reputation—let’s talk.

Ready to build your AI Policy Playbook?
Schedule an AI governance and security assessment with Inman Technologies and turn responsible AI into a lasting competitive advantage.