Enterprise AI Fundamentals
Safe, responsible, and compliant enterprise AI use
Outcome: Establish a defensible baseline for workforce AI use across the organization.
Baseline policy language, workforce enablement evidence, and practical safe-use guidance.
Implementation Outcome
This course provides a shared foundation for understanding AI in the enterprise. It clarifies how AI is used at work, what risks it introduces, and what responsibilities employees have when using AI tools. The course reduces misuse, data leakage, and compliance risk while providing defensible evidence of workforce enablement.
- Enterprise AI acceptable-use baseline (workforce-ready)
- Data handling & confidentiality quick-reference guide
- Accountability checklist for AI-assisted work
Controls & Evidence
- Designed for records retention, version control, and documented review cadence
- Supports internal control alignment and defensible oversight practices
- Produces an audit-reviewable evidence set suitable for internal audit request workflows
Data handling: No submission of sensitive or proprietary data is required to complete the program.
Risk Exposure
Lack of defensible policies or controls can result in significant, unmitigated enterprise risk exposure. This program addresses the risk areas most relevant to this capability.
- Unapproved tool usage and shadow AI adoption
- Confidential data leakage through prompts or uploads
- Non-compliant use inconsistent with internal policy
- Lack of demonstrable workforce enablement evidence
Deliverables
AI Acceptable Use Baseline
Approved vs. prohibited use patterns, data rules, and escalation triggers.
Workforce Enablement Evidence Pack
Completion evidence and documentation language to support oversight and audit inquiry.
Safe Prompting & Output Review Guide
Practical guardrails for prompt hygiene and output verification.
Governance Integration Notes
How baseline training maps to internal policy, records retention, and review cadence.
Governance Lifecycle Integration
- Baseline: Establish policy-aligned use patterns and minimum control expectations across affected teams.
- Oversight: Assign accountable owners, decision rights, and escalation paths for AI-assisted activities.
- Monitoring: Define review cadence, metrics, and control checks aligned to operational reality.
- Documentation: Maintain version-controlled artifacts and evidence suitable for records retention and review.
- Audit Review: Enable internal audit and leadership review with traceable controls, decisions, and evidence.
Buyer Questions
Does this require sharing confidential data with the provider?
No. The program is designed for policy, controls, and safe-use practices. Participants can complete the program without submitting sensitive or proprietary data.
Who should attend?
All employees using AI
What evidence is produced for audit review?
Version-controlled artifacts (policy templates, oversight workbook outputs, and control-aligned documentation) suitable for internal audit requests and governance reviews.
How is it deployed?
On-demand delivery with enterprise licensing options. LMS and SSO integration can be included in rollout scoping.
How are artifacts maintained over time?
Artifacts are designed for version control and periodic review. Organizations can align updates to internal change management and records retention requirements.
Request Enterprise Pricing
For rollout scoping (seat counts, deployment model, LMS/SSO integration, and licensing options), request enterprise pricing and deployment scope.