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AI training for non-technical employees covers what to verify before acting on AI output, what data to keep away from public tools, and what to check before an AI tool goes live. The best AI training programs go even further by customizing what they teach to employees by role. The goal is to close the AI Capability Gap: the distance between giving people AI tools and helping them use those tools well and securely.
What Is AI Training for Non-Technical Employees?
AI training for non-technical employees teaches people without engineering backgrounds how to incorporate AI tools into their workflow. Some companies call it AI literacy training since it teaches them how to better interact with this new technology. It covers marketing, finance, HR, operations, and legal teams, all of whom could use AI tools but often don’t have a technical background.
Though the tools may be the same, the training looks different from what developers get. A developer needs to review AI-written code for security flaws, while a finance manager needs to check an AI summary of a contract against the contract itself before approving it.
Why Do Non-Technical Employees Need AI Training?
Employees without an engineering background already use AI at work, often without approval or formal training. PagerDuty surveyed 1,250 office professionals at companies with over $500 million in revenue across the U.S, U.K., Australia and Japan and and found that two-thirds of them had used AI tools they believed their company policy didn't allow.1 More than a third of them entered customer data into public AI tools.
That's what's known as shadow AI risk, which is the risk a company takes on when employees use tools it never approved. If often happens because employees know that AI can help them work faster, but they’ve been handed a policy without practical training on what it means for their day-to-day work, or withouth approved tools that meet their needs.What Happens When Employees Use AI Without Training?
The untrained employee may accept AI output without checking it. The University of Melbourne and KPMG surveyed more than 48,000 employees in 47 countries and found that 58% of US respondents relied on AI output at work without evaluating its accuracy.2
The problem is that AI models tend to present incorrect information very confidently. An HR coordinator might ask a chatbot how the company handles vacation days at termination, a question a public chatbot can’t reliably answer because it has never seen the company’s handbook, and pass that answer to a departing employee without ever checking what the handbook says. If the chatbot was wrong, the terminated employee might then come back with a grievance or even a legal claim, since rules on paying out unused vacation days vary by jurisdiction
What Skills Should AI Training Cover for Non-Technical Employees?
Verification should be the first thing. Employees who learn how to check AI output against a source they trust avoid making mistakes based on a confident answer that was wrong.
They also need to know which tools their company approved and what information they can input into each one. Free consumer tools could train on any data they get, including sensitive client information unless someone opts out.
Employees should also practice responsible AI use by knowing where AI fits in a decision or process and where human judgement has to take over. For example, a model could draft a performance review in an approved tool, but the manager is ultimately responsible for what it says.
Finally, employees need to learn how to apply AI to the real work of their role. Most people start with drafting, summarizing and searching. Good training helps them go further and rethink workflows and decisons, so AI delivers more than small time savings.
How Do You Teach Employees to Use AI Securely?
Teach security in the context of what an employee is already doing. A marketer who builds an automation learns what that automation can and cannot do as they're building it, which lands better than an isolated security module they took months ago.
That timing is especially important for employees who have never built software before. Zapier surveyed 818 US workers who built a working tool with AI and found that over a third of them had no formal programming background. They know what they want the tool to do, but they might not know how to set the right access parameters. Security Journey’s AI Access training is built for this group. It covers private repositories, tokens and secret checks, pull requests and audit logs as people build with AI assistants.
Michael Burch, VP of AI Enablement and Acceleration at Security Journey, puts it plainly: "You are not capable unless you also understand the security implications of what you are building."
How Do You Build an AI Training Program for Non-Technical Teams?
Measure what your employees can already do with AI before you decide what to teach them. Researchers at UC San Diego Health ran an eight-month randomized study with close to 20,000 employees and found that recently completing annual security awareness training had no significant effect on whether employees fell for simulated phishing emails. Check the box AI modules risk the same result. That’s why a baseline matters: it shows you where to focus and lets you measure change later.
Customize the program for each department and go from there. Gallup recommends role-specific AI training as a paralegal and a sales rep clearly need different things.4
Then measure capability, not completion. Reassess skills after training, track progress by role and team and look for teams who AI practices are ready to scale.
How Do You Choose the Right AI Training Platform for Your Organization?
Start with what a vendor can tell you about your own employees. Many will just report a completion rate, which doesn't tell you much about whether they learned or not. You want a vendor who can show you which skills your employees have by role, team and cohort, and where they struggle along with where AI risk is emerging.
Then look at what employees do within the training. An employee who watches a video about data handling will forget it in a week, while one who works through a scenario from their own job will take something away from it.
Security Journey built AI Advantage around both. AI Advantage gives every employee a practical foundation, with hands-on AI Skill Labs, and lessons on prompting, output handling, privacy, responsible use, and tools like ChatGPT, Microsoft 365 Copilot, and Claude. AI skills assessments and reporting show leaders where capability is growing, where gaps remain, and where risk is emerging. Employees work through tracks matched to their role and can receive help from a real person when they get stuck.
References
- PagerDuty. “PagerDuty Report Finds Two-Thirds (66%) of Office Professionals Have Used Unauthorized AI Tools at Work.” June 2026. https://www.pagerduty.com/newsroom/shadow-ai-workplace-survey-2026/
- University of Melbourne and KPMG. “Trust, Attitudes and Use of Artificial Intelligence: A Global Study 2025.” April 2025. https://assets.kpmg.com/content/dam/kpmgsites/xx/pdf/2025/05/trust-attitudes-and-use-of-ai-global-report.pdf
- Ho, G., Mirian, A., et al. “Understanding the Efficacy of Phishing Training in Practice.” IEEE Symposium on Security and Privacy, May 2025. https://sysnet.ucsd.edu/~voelker/pubs/phishtrain-oakland25.pdf
- Zapier. “34% of AI Builders Have No Formal Training.” July 2026. https://zapier.com/blog/building-business-software/
- Gallup. “Manager Support Drives Employee AI Adoption.” November 2025. https://www.gallup.com/workplace/694682/manager-support-drives-employee-adoption.aspx
