What stays out
Identify personal information, credentials, contracts, privileged material, trade secrets and other restricted data.
Protect information before prompting
AI Safety & Privacy Training for Employees
Employees need rules they can apply at the moment they open an AI tool. This session turns abstract risk into clear examples, decisions and review habits.
Where this helps
Turn abstract risk into everyday decisions
- Organizations with informal employee AI use
- Teams handling client or employee information
- Managers concerned about accuracy and confidentiality
Protective habits
01
Recognize prohibited information
02
Use redaction and approved alternatives
03
Verify important output
04
Escalate uncertain use cases
Risk areas
Clear boundaries employees can act on
Why output can fail
Understand hallucinations, stale knowledge, biased patterns and confident-sounding errors.
A safer workflow
Use approved tools, minimum necessary context, source checks, human approval and appropriate recordkeeping.
Why this training is different
The workplace challenge behind the session
Employees need a decision they can make at the moment of use: Is the tool approved? Is the information permitted? Can the task use less data? What must be checked, and who approves the result?
01
Classify information before prompting
- Situation
- A realistic task contains public, internal and personal details.
- In the room
- Sort the information and remove what is unnecessary.
- Quality check
- Use only what policy permits in an approved tool.
02
Handle a plausible fabrication
- Situation
- An answer includes a convincing but invented source.
- In the room
- Trace material claims to authoritative originals.
- Quality check
- Remove anything that cannot be supported.
03
Pause an uncertain use
- Situation
- The task is useful, but tool approval is unclear.
- In the room
- Document the question without entering the data.
- Quality check
- Escalate to the named privacy, security or policy owner.
How the learning progresses
A deliberate path from explanation to accountable use
Before input
Classify tools, accounts and information.
During use
Minimize data and keep uncertainty visible.
Before output
Verify facts, fairness and permissions.
When unsure
Stop and use the established escalation path.
Decisions to settle
- Approved tools and accounts
- Prohibited information categories
- Required verification evidence
- Incident and escalation contacts
Prepare for a useful session
- Bring current data classifications
- List approved accounts
- Choose fictional risk scenarios
- Include privacy or security contacts where possible
Continue planning
Choose the next detail your organization needs
Training at your workplace
Give employees clear, practical boundaries for AI use.
Tell JimmyAI about your team, workplace and learning goals.