Using AI Safely and Responsibly in the Workplace

• Identifying personal data, sensitive information, and PII in workplace records
• Assessing privacy risks when organizational data is processed by AI
• Applying data protection principles to AI-enabled work
• Data minimization, anonymization, and de-identification techniques
• Determining what information can and cannot be submitted to an AI system

Hands-on Lab: Classify and De-Identify Before You Paste — Classify realistic workplace records, determine which information can safely be processed with AI, and de-identify sensitive content before use.

• Mapping AI data-handling decisions to applicable privacy requirements
• Consent and permitted use of personal information
• GDPR, CCPA, the EU AI Act, and emerging AI requirements
• Industry-specific privacy considerations
• Converting regulatory requirements into day-to-day AI operating controls

• Security risks unique to AI-enabled systems
• Prompt injection and manipulation of AI instructions
• Unauthorized access to and exposure of connected data
• Deepfakes, voice cloning, and AI-enabled phishing
• Identifying malicious or suspicious AI interactions
• Response and escalation procedures

Hands-on Lab: Threat Spotting Drill — Analyze realistic emails, chat messages, recordings, and AI interactions to identify AI-specific threats, document the evidence, and determine the appropriate response.

• Configuring AI privacy and security options
• Managing access and data-use settings
• Safe prompting and preventing accidental data leakage
• Handling external instructions and prompt-injection attempts
• Copyright, intellectual property, and AI-generated content
• Implementing technical safeguards before AI tools are used with business data

Hands-on Lab: Secure Your AI Workspace — Configure the privacy, security, and data-use settings of an AI environment and produce evidence showing how each technical setting protects organizational information.

• Detecting bias in AI-generated results
• Comparing outputs for inconsistent or discriminatory behavior
• Transparency and explainability
• Designing human-review checkpoints
• Determining when AI output can be used directly or requires escalation
• Establishing accountability for AI-assisted work

Hands-on Lab: Bias and Oversight Check on AI Outputs — Run paired workplace prompts, compare results for inconsistent treatment or bias, improve the prompts, and design human-review checkpoints for higher-risk outputs.

Create a ready-to-use AI operating package for a workplace team that includes data-handling rules, secure-use guidance, threat-response procedures, human-review checkpoints, and evidence of configured AI security and privacy controls. The capstone is assessed against a skills-based rubric and must be successfully completed to earn the CERT4TECH Certificate in Safe and Responsible Workplace AI Use.