Artificial intelligence is already being used inside most businesses, whether leadership realizes it or not.
Employees are using AI to draft emails, summarize documents, analyze information, create content, and automate routine tasks. At the same time, software vendors are rapidly adding AI features to the tools organizations already use every day.
The opportunity is significant. AI can help businesses improve productivity, streamline operations, and uncover new efficiencies. But it also introduces new risks around data security, compliance, vendor management, and accountability.
That’s why more organizations are beginning to develop formal AI policies. The challenge is that many business leaders assume there is only one type of AI policy. But in reality, there are two distinct but connected documents that organizations should implement: an AI Governance Policy and an AI Usage Policy.
Understanding the difference is the first step toward using AI responsibly.
Why AI Policies Matter
Most organizations already have policies for cybersecurity, acceptable use, data classification, vendor management, and compliance. AI doesn’t replace those policies. It introduces new considerations that must fit within them.
Without clear guidance, employees may:
- Use unapproved AI tools
- Upload confidential information into public AI platforms
- Rely on inaccurate AI-generated content
- Enable AI features without understanding how data is being handled
- Expose the organization to contractual, regulatory, or reputational risk
The goal of AI policy isn’t to prevent innovation. It’s to create guardrails that allow employees to take advantage of AI while protecting company, customer, and employee data.
What Is an AI Usage Policy?
An AI Usage Policy is the employee-facing rulebook.
It explains how employees may use AI tools in their daily work and establishes clear expectations for acceptable behavior.
A typical AI Usage Policy addresses:
- Approved AI tools
- Prohibited tools and accounts
- What data may be entered into AI systems
- What data must never be entered into AI systems
- Rules for personal AI accounts and browser extensions
- Output verification requirements
- Incident reporting procedures
In short, an AI Usage Policy answers the question:
“What am I allowed to do with AI?”
For example, an employee may be allowed to use an approved AI tool to brainstorm marketing ideas or summarize meeting notes. However, they may be prohibited from entering customer contracts, employee records, payment information, or other sensitive data into a public AI platform.
The audience for this policy is the workforce. Its purpose is to establish clear, practical rules that employees can follow every day.
DOWNLOAD OUR AI USAGE POLICY TEMPLATE HERE
What Is an AI Governance Policy?
An AI Governance Policy operates at a higher level.
Instead of focusing on individual employee behavior, it defines how the organization evaluates, approves, monitors, and manages AI risk.
An AI Governance Policy typically addresses:
- AI ownership and accountability
- Approval processes for new AI tools
- Risk classification and review requirements
- Vendor due diligence
- Data protection requirements
- Human oversight expectations
- Incident response
- Compliance obligations
- Audit and evidence requirements
In short, an AI Governance Policy answers the question:
“How does the organization control AI?”
The audience is typically executive leadership, IT, security, compliance, legal, and business-unit leaders responsible for approving and overseeing AI use.
DOWNLOAD OUR AI GOVERNANCE POLICY TEMPLATE HERE.
AI Governance vs. AI Usage Policy
The easiest way to think about these documents is that governance establishes the rules, and usage translates those rules into everyday behavior.
- Employee-facing
- Defines acceptable use
- Focuses on daily behavior
- Covers approved tools and data handling
- Supports workforce training
- Leadership-facing
- Defines oversight and accountability
- Focuses on risk management
- Covers approvals, reviews and monitoring
- Supports governance and compliance
The two policies should work together.
Governance determines which AI tools are approved, what types of data can be used, and what level of review is required. The Usage Policy then communicates those decisions to employees in language they can easily understand and follow.
For a more detailed description, DOWNLOAD OUR AI USAGE VS. GOVERNANCE EXECUTIVE BRIEF.
The Biggest AI Risks Businesses Face Today
Many organizations assume AI risk is primarily a future problem. In reality, most AI-related risk comes from everyday business activity.
Shadow AI
Employees frequently use AI tools without formal approval. This can include personal AI accounts, browser extensions, and free AI services that operate outside the organization’s visibility.
Sensitive Data Exposure
Employees may unintentionally upload confidential information, customer records, employee data, source code, or regulated information into AI systems that are not approved to handle it.
Vendor Risk
Many AI vendors retain prompts, store outputs, or use customer information to improve their models. Organizations need to understand exactly how their data is handled before adopting new tools.
Embedded AI Features
AI is increasingly appearing inside software that businesses already use. A vendor may enable AI-powered summarization, search, or automation features that process sensitive information without anyone realizing it.
Overreliance on AI Output
AI-generated content can be inaccurate, incomplete, or misleading. Human review remains critical, particularly for customer-facing, financial, legal, healthcare, or compliance-related content.
Where Should SMBs Start?
Many business leaders assume AI governance requires a large compliance program, but that’s not the case. Most organizations can make significant progress by focusing on a few foundational steps.
1. Identify Existing AI Use
Start by understanding where AI is already being used.
Talk to department leaders and employees. Review business applications. Look for AI tools, browser extensions, and embedded AI features already operating inside the organization.
2. Create an AI Inventory
Document approved and unapproved AI tools.
You don’t need a complex system. A simple inventory that tracks the tool, owner, purpose, and data involved is a strong first step.
3. Define Approved and Prohibited Uses
Establish clear guidance around:
- Approved AI tools
- Approved use cases
- Restricted data types
- Required reviews and approvals
4. Review AI Vendors
Before adopting new AI solutions, evaluate:
- How data is stored
- Whether customer data is used for model training
- Security controls
- Compliance certifications
- Data retention practices
5. Train Employees
Even the best policy will fail if employees don’t understand it.
Provide practical guidance on approved tools, prohibited activities, output verification, and incident reporting.
6. Review Regularly
AI technology is changing rapidly. Policies should be reviewed and updated as tools, regulations, and business needs evolve.
Does Your Business Need Both Policies?
The answer is yes.
An AI Usage Policy without governance creates rules that may not reflect actual business risk.
An AI Governance Policy without a Usage Policy creates decisions that never reach the people using AI every day.
Together, they provide the structure needed to balance innovation with security, compliance, and accountability.
As AI becomes more deeply integrated into business operations, organizations that establish clear governance and usage standards will be better positioned to take advantage of the technology while reducing unnecessary risk.
Frequently Asked Questions
What is the difference between AI governance and AI usage?
AI governance focuses on organizational oversight, approvals, and risk management. AI usage focuses on employee behavior and acceptable use of AI tools.
Does a small business need an AI Governance Policy?
Yes. Even small organizations are using AI tools and AI-enabled software. A governance policy helps ensure those tools are reviewed, approved, and monitored appropriately.
What should employees never enter into public AI tools?
Organizations should generally prohibit employees from entering confidential business information, customer data, employee records, credentials, source code, and regulated information into unapproved AI systems.
How often should AI policies be reviewed?
At a minimum, annually. Policies should also be reviewed when significant new AI tools, regulations, or business requirements emerge.
Can AI policies help with compliance?
Yes. Well-designed AI policies support broader cybersecurity, privacy, and compliance programs, including requirements related to HIPAA, CMMC, PCI DSS, privacy regulations, and customer security expectations.
