Artificial intelligence is quickly becoming part of everyday work. Employees are using AI to summarize documents, draft communications, analyze information, write code, brainstorm ideas, and speed up routine tasks.
But that convenience introduces a significant business risk: employees can expose valuable intellectual property without realizing they’re doing it.
A prompt that includes an unreleased product feature, proprietary source code, customer information, internal strategy, or confidential document can move company information outside the controls organizations normally rely on to protect it.
And the risk isn’t limited to a malicious employee intentionally taking company secrets. In many cases, the employee may simply be trying to get their work done faster.
Protecting intellectual property in the age of AI therefore requires more than telling employees, “Don’t share confidential information.”
Organizations need to help employees recognize intellectual property, provide approved enterprise AI tools, and establish clear policies reinforced through consistent training.
Here are three key steps.
1. Teach Employees How to Identify Intellectual Property
The first step in protecting company IP from AI is surprisingly basic: employees need to know what intellectual property is.
Intellectual property isn’t limited to patents and trademarks.
Depending on the organization, valuable company IP examples can include:
- Proprietary software and source code
- Product designs and specifications
- Research and development
- Internal processes and methodologies
- Strategic plans
- Pricing information
- Customer or prospect information
- Marketing strategies
- Unpublished financial information
- Trade secrets
- Copyrighted materials
- Confidential information received from customers, vendors, or business partners
This distinction becomes particularly important with generative AI because employees routinely provide AI systems with information in order to receive useful outputs.
Consider an employee asking an AI tool:
“Here’s the product roadmap we’re presenting to leadership next week. Summarize the major competitive advantages and suggest how we should position them.”
From the employee’s perspective, they’re simply using AI to make their work easier.
From the organization’s perspective, they may have just entered confidential product strategy into an AI system that wasn’t approved for that information.
There’s another side of the IP issue, too: employees need to recognize intellectual property belonging to other people and organizations.
AI-generated content can raise copyright, trademark, licensing, and ownership questions. Employees shouldn’t assume that because an AI system produced something, the organization automatically has unrestricted rights to use it.
That’s why AI literacy and IP literacy increasingly need to go together.
Organizations should first make sure employees understand what information belongs to the company, what information belongs to others, and what information should never be entered into an AI system.
For a deeper explanation of workplace intellectual property, see Emtrain’s article on why protecting intellectual property in the workplace matters.
2. Provide Enterprise AI Tools Employees Are Approved to Use
Teaching employees what not to share is important, but organizations also need to address a practical reality:
Employees are going to use AI.
Simply prohibiting AI without giving employees a secure alternative can encourage “shadow AI” — employees using consumer AI applications or unapproved tools outside the organization’s technology environment.
Instead, employers should establish which AI systems employees may use for company business.
Emtrain’s sample Responsible AI Usage and Governance Policy takes this approach directly. It recommends that employees only use AI tools that have been reviewed, approved, and provided to the workforce for company-related work, specifically citing data security and protection of intellectual property among the reasons for this requirement.
That review matters because not every AI tool handles organizational data the same way.
Before approving an AI platform, organizations should evaluate issues such as how the vendor handles data, what security measures are in place, what contractual protections exist, and whether the vendor’s AI governance practices align with the organization’s requirements. Emtrain’s policy template specifically calls for AI vendor due diligence around governance practices, data handling and security, contractual transparency and accountability, and ongoing compliance monitoring.
But an approved tool doesn’t mean anything can be entered into it.
Organizations still need rules governing what employees can put into AI systems.
For example, Emtrain’s sample policy prohibits entering company confidential information such as trade secrets, unreleased product designs, financial information and strategic plans. It also addresses proprietary code, algorithms, IP, information covered by NDAs, and personally identifiable information.
The goal isn’t to prevent employees from benefiting from AI.
It’s to create a controlled environment where they can use AI without making individual employees responsible for evaluating the security and data practices of every new AI tool they encounter.
3. Create an AI Governance Policy — and Train Employees Consistently
Technology controls alone won’t protect intellectual property.
AI governance increasingly resembles cybersecurity in one important respect: every employee can create risk.
An organization can invest heavily in security, legal protections, access controls, and enterprise AI platforms. But one employee copying confidential information into an unapproved AI tool can circumvent many of those safeguards.
That’s why organizations need both policy and behavior change.
An AI governance policy should establish clear expectations around questions employees encounter in their actual work:
- Which AI tools can I use?
- What information can I enter?
- What information is prohibited?
- Can I use AI-generated content externally?
- Do I need to verify AI outputs?
- What happens if I accidentally enter confidential information?
- Who do I contact when I’m unsure?
A policy can also establish organizational responsibility for AI rather than leaving individual departments to make these decisions independently.
Organizations don’t have to approach AI governance without established guidance. The National Institute of Standards and Technology (NIST) has developed a Generative AI Profile as part of its AI Risk Management Framework to help organizations identify and manage risks unique to generative AI.
From there, organizations need to translate those broader risk-management principles into clear rules employees can actually follow.
For example, Emtrain’s policy template proposes an AI Governance Committee involving IT, Legal, HR, Compliance, and Operations, with responsibilities including approving AI technologies, assessing risks, responding to incidents, conducting audits, updating policies, and overseeing employee training.
But publishing the policy isn’t the end of the process.
Employees need to understand how those rules apply to the everyday decisions they’re making with AI.
And unlike a relatively static workplace policy, AI practices are changing rapidly. New tools appear. Existing products introduce AI functionality. Employees find new use cases. Risks evolve.
That’s why AI governance training shouldn’t be viewed as a one-and-done compliance exercise. Emtrain’s policy template specifically recommends training for all employees along with regular updates and refreshers as AI technology and risks evolve.
Protecting IP From AI Is Ultimately a Workforce Issue
Companies have traditionally protected intellectual property through contracts, security controls, confidentiality agreements, access restrictions, and legal protections.
Those safeguards remain important.
But AI creates another point of vulnerability: the everyday decisions employees make about what information they put into an AI tool.
That makes protecting IP from AI partly a technology challenge — but also a workforce behavior challenge.
The organizations that manage this risk effectively will give employees three things:
- Knowledge: Help employees recognize company IP and third-party intellectual property.
- Tools: Give employees approved enterprise AI systems and clear rules for using them.
- Governance: Establish an AI policy and reinforce it with practical, ongoing employee training.
The objective shouldn’t be to discourage employees from using AI. It should be to make responsible AI use the easiest and clearest option.
Turn AI Governance Into Everyday Employee Practice
Protecting intellectual property from AI requires more than putting rules in a policy. Employees need to understand what intellectual property they are responsible for protecting, why it matters, and how their everyday use of AI can put those assets at risk.
Emtrain’s Enterprise AI Governance Policy Template gives organizations a starting point for establishing expectations around approved AI tools, confidential information, data handling, human oversight, vendor management, and incident response. The template also emphasizes workforce training and regular refreshers as AI technology and risks continue to evolve.
Policy should be reinforced with practical employee education. Emtrain’s Protecting Intellectual Property training course helps employees recognize and safeguard patents, trademarks, copyrights, trade secrets, and other valuable company assets — including understanding how AI tools can create new risks to IP.
Organizations can build on that foundation with Emtrain’s AI Governance Training course, which focuses specifically on responsible AI use. Through workplace scenarios, employees learn how AI can compromise trade secrets, copyrights, and proprietary information, as well as how to follow their organization’s AI governance policies when using AI tools.
Together, clear policies, IP awareness, and practical AI governance training give employees the guidance they need to use AI productively without unnecessarily putting the organization’s intellectual property at risk.
