AI-Powered Employee Profiling

Important Note: AI-Powered Employee Profiling is available for Enterprise customers only. The feature is off by default and must be enabled before profiles will generate.

This article walks you through the AI-Powered Employee Profiling feature, including how to enable it, what each section of the profile contains, and how recommendations are generated.

1. What is AI-Powered Employee Profiling?
2. Enabling AI-Powered Employee Profiling
3. Profile sections deep-dive
4. How recommendations are generated

1. What is AI-Powered Employee Profiling?

AI-Powered Employee Profiling generates personalized security insights for each employee. The AI continually assesses employees based on their phishing simulation results, training history, platform engagement, and other risk signals to recommend the training modules and phishing templates best suited to their individual profile, along with detailed explanations as to why.

2. Enabling AI-Powered Employee Profiling

To enable the feature:

1. Go to Reporting.
2. Open Employee Settings.
3. Toggle AI-Powered Employee Profiling to Enabled.

Profiles will begin generating once the feature is on and sufficient behavioral data is available.

3. Profile sections deep-dive

Each employee profile contains four sections:

AI Summary: A plain-language overview of the employee's security strengths, weaknesses, and overall human risk posture. The summary reflects factors such as past compromises, reporting history, training completion, business impact rating, and dark web exposure.

Recommended Training: A list of training modules tailored to the employee's identified gaps. Modules are selected to either close a known weakness or reinforce a behavior that is currently weak.

Recommended Phishing: A list of phishing simulation templates suited to the employee's profile. Templates the employee has already encountered may be deprioritized, while new variants are introduced to reduce avoidance from familiarity.

Selection Rationale: A written explanation of why specific training and phishing recommendations were chosen. This gives administrators the context needed to validate or adjust the AI's suggestions before assigning content.

4. How recommendations are generated

The AI assesses each employee using a combination of behavioral and contextual signals:

• Phishing simulation history: clicks, reports, compromises, and ignored simulations.
• Training history: completed modules, in-progress assignments, and gaps.
• Platform engagement: participation and consistency in security activities.
• Risk indicators: dark web monitoring exposure, role-based business impact, and observed incident patterns.

These signals are weighed together to produce the strengths, weaknesses, and tailored recommendations shown in the profile.