// approved tools, policy simulations, prompt libraries, workflow libraries, and misuse reporting

$ train --policy="applied"

AIducation turns company AI policy into role-specific practice. Learners use approved tools, follow data boundaries, apply prompt and workflow libraries, report misuse, and create audit-ready evidence.

[GENERATE_FROM_POLICY][VIEW_POLICY_API][SAFETY_LABS]

Enterprise policy layer

15
Policy academies
105
Controls
56
Approved tools
60
Misuse signals
[+] AIducation for Support remains the first policy-safe practice path.

// Policy_training_loop

Policy training becomes evidence when employees practice real decisions with approved tools, source checks, escalation boundaries, and misuse reporting.

Policy

Apply company AI rules to realistic role scenarios instead of passively reading a document.

Tools

Practice approved tool use with clear data, role, workflow, and verification boundaries.

Libraries

Use approved prompt and workflow libraries for repeatable high-risk AI work.

Report

Identify unsafe AI behavior and produce a manager-readable misuse or escalation note.

// Role_policy_academies

Every role gets the same governance primitives, but applied to its own tools, workflows, data risks, and manager review needs.

View misuse reporting API filter
AIducation for Support

Support AI Policy Training

first wedge
7
controls
3
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI
AIducation for Sales

Sales AI Policy Training

7
controls
3
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI
AIducation for Marketing

Marketing AI Policy Training

7
controls
4
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI
AIducation for HR

HR AI Policy Training

7
controls
4
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI
AIducation for Finance

Finance AI Policy Training

7
controls
4
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI
AIducation for Engineering

Engineering AI Policy Training

7
controls
4
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI
AIducation for Product Managers

Product AI Policy Training

7
controls
3
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI
AIducation for Executives

Executives AI Policy Training

7
controls
4
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI
AIducation for Operations

Operations AI Policy Training

7
controls
4
tools
3
library
  • [+] Approved tool catalog
  • [+] Data handling
  • [+] Verification requirement
AcademyAPI

// Controls_and_evidence

The policy layer connects governance to learning artifacts: approved tools, data handling, verification, escalation, misuse reporting, prompt libraries, and workflow libraries.

Connect policy to portfolios
Approved tool catalog

Learners use only approved AI tools for the role, data type, and workflow.

Tool mission completion linked to approved-tool status.

Data handling

Sensitive customer, employee, financial, legal, health, or code context is minimized or removed before AI use.

Scenario answer identifies data risk and safe handling step.

Verification requirement

AI output must be checked against source material, calculations, policy, or code paths before reuse.

Verification checklist and final artifact show what was checked.

Escalation boundary

Learners escalate when authority, compliance, security, privacy, or quality risk remains unclear.

Rubric result shows correct escalation or manager approval path.

AI misuse reporting

Learners know how to report risky prompts, unsafe outputs, unauthorized automations, or policy exceptions.

Misuse reporting simulation and manager-ready risk note.

Approved prompt library

Learners start from approved prompt templates instead of ad hoc prompts for high-risk workflows.

Prompt template artifact saved to the learner portfolio.

Approved workflow library

Repeatable AI workflows include ownership, inputs, output checks, and rollback or escalation paths.

Workflow playbook artifact and capstone evidence trail.

// Misuse_reporting

Misuse reporting turns unsafe AI behavior into coaching and audit evidence before it becomes live-work risk.

Support learner pastes sensitive data into an unapproved AI tool

Support learner forwards AI output without verification or source evidence

Support workflow automates a decision that requires human approval

Support artifact includes unsupported claims, citations, calculations, or policy promises

// Audit_ready_exports

Admins can prove policy training with completion, tool, scenario, score, library, misuse, credential, and portfolio evidence.

Policy training completion
Approved tool mission result
Scenario attempt and rubric score
Prompt and workflow artifact links
Misuse reporting drill evidence
Credential or portfolio verification link