Manage AI Risk and Address Shadow AI
The majority of employees use unapproved AI tools at work, and shadow AI breaches cost significantly more than average data incidents. Leaders who manage AI risk effectively channel demand through sanctioned alternatives rather than imposing bans that drive usage underground. Without visibility into actual AI usage and a disciplined approach to data classification and human oversight, organizations face regulatory exposure and security vulnerabilities they cannot even quantify.
Proficiency Level
This is a preview of how skill assessment works in Admire
Measurable Behaviors
Each behavior is directly observable and can be assessed through manager observation. In Admire, these drive evidence-based skill tracking.
Deploy AI Usage Monitoring
Deploys AI usage monitoring to gain visibility into which tools employees use, what data enters those tools, and which decisions AI influences.
Address Shadow AI with Sanctioned Alternatives
Addresses shadow AI by providing sanctioned alternatives with proper controls and a fast-track approval process for new tools rather than relying on bans.
Establish Data Classification Framework for AI Use
Establishes a data classification framework for AI use that defines which data tiers can be used with which categories of AI tools.
Maintain Human-in-the-Loop for Consequential Decisions
Maintains human-in-the-loop requirements for consequential decisions with clear documentation of AI's role in the decision chain.
Track Regulatory Landscape and Classify AI by Risk Tier
Tracks the regulatory landscape including EU AI Act timelines and industry-specific requirements, and classifies AI systems by risk tier before enforcement deadlines.
This is a preview of how behavior tracking works in Admire
Mastering AI Risk Management and Shadow AI Response
A leader who has mastered this skill has deployed AI usage monitoring that provides real visibility into which tools employees use and what data enters those tools. They address shadow AI by providing sanctioned alternatives with proper controls and fast-track approval processes. They maintain data classification frameworks for AI use and track the regulatory landscape to classify AI systems by risk tier well before enforcement deadlines.