Published on
When you think about employee security training, what comes to mind? For a large part of the workforce, it's the annual chore of watching some videos and taking a few quizzes. In the AI era, a minimalist approach to training misses the mark.
Rolling out new AI tools can save an organization time and money, but only if you also consider how to train employees to use generative AI securely.
To use AI to its full potential, companies need to teach employees how to use AI well and securely, closing what we call the AI Capability Gap.
What Does It Mean to Train Employees on Generative AI Security?
Generative AI employee training is the process of educating your workforce on how to use AI tools safely. A thorough training program centers around these outcomes:
- Using approved AI tools effectively and within company policy
- Recognizing AI-driven cyber threats, including social engineering
- Validating AI outputs rather than blindly trusting what it produces
- Meeting AI obligations under the EU AI Act or guidelines from the U.S. Department of Labor
- Protecting sensitive data from accidental leaks
A structured program doesn't scare employees away from using AI. It teaches them how to handle it responsibly and increase efficiency without sacrificing security.
What Are the Risks of Letting Employees Use Generative AI Without Training?
Using AI tools without training can lead to data breaches, compliance violations, and financial penalties. Nearly 80% of the labor force works at an organization using AI for at least one business function, but they aren't all receiving AI security training for employees.
Making Mistakes With Chatbots
Untrained employees often treat AI chatbots like search engines. When they feed sensitive client data or proprietary source code into a public tool, the provider may store it, review it, or use it to train future models. This increases the risk of exposure and leaks.
Employees who haven't received training also may not realize the importance of applying human judgment to generative AI output. According to a recent study, less than half of organizations using AI have trained their employees on how to evaluate output.
Understanding AI hallucinations and inaccuracies is vital because chatbots can appear confident even when they're wrong. If your team doesn't audit and verify output, they may use fabrications or outdated information when making important decisions or creating company publications.
Creating Security Vulnerabilities and Compliance Issues
Employees who haven't received clear instructions on which tools they can use sometimes turn to unvetted apps. As a result, IT departments lose visibility over data. Unauthorized tools, such as fake AI apps or browser extensions, could also introduce malware to your network or give outside parties unauthorized access to your data.
In addition, without responsible AI use training, your team could accidentally breach industry privacy laws, such as HIPAA in healthcare or financial privacy regulations. Those violations can result in fines and legal liability, along with damage to your reputation.
A lack of training also makes it more difficult for employees to identify AI-focused cyberthreats in their daily work. For example, they might not recognize highly personalized phishing emails or manipulated images or video.
Why Do Organizations Need a Formal Generative AI Training Program?
A formal training program makes AI use safer and more consistent across your team. It's part of your overall generative AI governance, which lays out what's acceptable and what isn't.
Risk Mitigation
A formal program is essential if you want to minimize risks. It standardizes data privacy protocols and teaches safe input boundaries.
Watching a quick video or experimenting individually helps employees discover basic functionalities. However, it doesn't enforce a company-wide approach to using AI tools.
When you're intentional about educating your team, everyone learns about the same advanced verification techniques and secure practices.
Scalability and ROI
A formal program is crucial for growing companies and ensuring you get the most value from your AI tools. When employees only receive informal training, or are left to train themselves, some will thrive while others will fall behind.
Tech-savvy employees become more productive and efficient with AI. Those who are less comfortable with new tools struggle to keep up and make time-consuming or expensive mistakes.
A formal training program establishes a baseline across the organization. When all employees are on the same page, the benefits accumulate and justify your investment.
What Should a Generative AI Security Training Program Cover?
AI security training should cover the basics of AI tools, information about data privacy, and guidance on how to detect threats. It should also give detailed information about how to protect confidential or sensitive data.
What Key Points Do Employees Need to Know About AI?
Any training program should include an introduction to AI and how employees will use it within your organization. Provide a list of approved and prohibited tools, and explain what benefits they offer for different workflows.
Your training should also include information about specific security threats, such as:
- Deepfakes: Teach staff how to spot potential deepfake scams, such as a fake executive on a video call asking for an urgent wire transfer.
- Phishing and social engineering: Employees can no longer rely on grammar mistakes to spot a phishing scam, so they need to know what other red flags to watch for.
- Prompt injection: Attackers can hide instructions in emails, documents, or web pages that an AI tool reads, tricking into leaking data or taking unwanted actions.
- Excessive agency: Giving AI tools automated permissions involved in critical tasks could result in data leaks and operational errors.
- Model hallucinations: Train employees to verify all output from generative AI to confirm facts are accurate and current.
In addition, your training should give employees information about incident reporting procedures. Tell them how to document and report suspicious AI tool behavior or deepfake attempts.
How Do You Teach Employees to Protect Sensitive Data When Using AI?
When training employees on sensitive data and AI, focus on what's at stake. Offer concrete examples of how things can go wrong, pulling from real-life scenarios in similar organizations. Set clear guidelines for how to avoid those kinds of situations.
For example, establish a list of approved tools and distribute it to everyone on the team. Be specific about which platforms your organization authorizes and encourages employees to use.
Teach your team what counts as confidential data, such as source code or customer records. Demonstrate how pasting those kinds of information into unapproved public chatbots can result in leaks.
Set never-enter rules for specific types of information. Your list might include personally identifiable information (PII), financial records, credentials and API keys, and client contracts, particularly when using external models.
Finally, give your employees opportunities to experiment in a safe environment. A risk-free sandbox allows them to see firsthand how different tools can put sensitive data at risk.
How Do You Build and Roll Out a Generative AI Training Program?
When creating and implementing an AI training program, choose an existing platform from a trusted provider and tailor it to your organization. Effective AI training program design goes beyond videos and quizzes, so develop a program with hands-on activities and assessments.
Should Training Be Role-Based or One-Size-Fits-All?
AI training for employees is generally more successful when it's role-based because it addresses the differences in how certain employees interact with AI tools. Generalized training is less engaging and ignores unique risks for specific roles.
All employees within your organization need basic AI literacy, but some require more complex training. Start by deciding who needs what, separating foundational skills from more advanced ones.
Role-based AI training allows you to adjust the program based on employees' responsibilities and tools. For example, employees in marketing may need different training than those in finance or operations.
Should All Employees Start Training at the Same Time?
When implementing a new training program, consider using a phased rollout. Start with a small group to see how well the training works for them.
Review the results, and collect their feedback. If things go well, you can move forward with the remaining members of your team.
On the other hand, if you encounter issues, you have the opportunity to make changes before getting everyone on board.
Training team leaders early is also important. If managers and supervisors go through the program first, they can model proper AI usage and answer employee questions.
How Do You Measure Whether Generative AI Training Is Working?
Measuring AI training effectiveness involves looking at key metrics beyond a completion checkbox. Maybe every employee finished the training, but did they learn anything?
To see whether the program is having the intended effect, evaluate whether your team is adopting the strategies and demonstrating the capabilities it covered.
Skills assessments are a good option for checking employees' understanding of safe AI usage. Have them complete an assessment both before and after the training to see what progress they've made.
For deeper insights, track the results by role, team, and department. This helps you see where you have information gaps and possible security risks, as well as which teams are ready to share what’s working.
In addition, track employees' use of approved tools versus unapproved ones, and review their AI-assisted work for quality and safe practices.
How Do You Choose the Right Platform to Train Employees on Secure AI Use?
To find the right AI security training platforms, think about the applications you use and the kinds of work your employees do.
Ask yourself what types of tools it covers, and what tracking and assessment capabilities are available. Do they go beyond a simple checkbox?
If a program only offers a single learning pathway for all employees, look for one you can modify based on employee needs. For example, Security Journey offers a foundational learning track for every employee through AI Advantage and provides additional paths for various roles, such as marketing, sales, and HR. It also offers AI Access for non-developers building with AI, secure code training for developers and skills assessments with reporting by role, team and cohort.
On top of that, think about whether the program is interactive or passive. Employees won't gain much from their training if they're half-focused on a video playing in the background. A solution with hands-on labs helps keep them engaged and improves retention.
Before you commit to any solution, ask for a demo so you can see it in action.
