Organization-Wide AI Policy

This section covers the creation and rollout of organization-wide AI-assisted development policies that standardize practices, governance, and expectations across all engineering teams. The organization-wide policy is the capstone deliverable of the transformation — it codifies the lessons, standards, and governance mechanisms developed through Phase 1 and Phase 2 into a formal, enforceable enterprise policy. This is not a rewrite of what already exists; it is the consolidation, formalization, and universal application of proven practices.

Policy Components

The Organization-Wide AI Policy MUST contain the following components:

1. Policy Statement and Scope

This section establishes the policy's authority and applicability:

• Authority — The policy is issued under the authority of the CTO and CISO, with approval from the executive leadership team
• Scope — The policy applies to all employees, contractors, and third parties who write, review, or deploy code within the organization, regardless of role or department
• Effective date — The date from which compliance is mandatory
• Review cycle — The policy MUST be reviewed and updated at minimum annually, or upon significant changes in technology, regulations, or organizational structure
• Relationship to other policies — Cross-references to Information Security Policy, Acceptable Use Policy, Data Classification Policy, and Code of Conduct

2. AI Tool Authorization

• Defines the approved AI development tools and their authorized configurations
• Establishes the AI Tool Assessment framework as the mandatory process for evaluating new tools
• Prohibits the use of unauthorized AI tools for any work-related code generation
• Defines the process for requesting evaluation of new tools

3. Data Protection Requirements

• Incorporates the data classification rules from Baseline Security Policies
• Defines Restricted data handling rules that prohibit Restricted data in AI prompts under any circumstances
• Establishes DLP controls as mandatory for all AI tool network traffic
• Requires data impact assessments for projects in Risk Tier 3 and above per Risk Assessment Scaling

4. Development Standards

• Mandates AI attribution metadata on all AI-assisted code per Pillar 1
• Requires human review of all AI-generated code before merge
• Establishes minimum code review standards for AI-assisted pull requests
• Mandates the Operating Model Lifecycle for all AI-assisted development initiatives
• Requires compliance with advanced prompt engineering standards per Advanced Prompt Engineering

5. Governance and Compliance

• Codifies the governance framework from Phase 2 as mandatory
• Defines risk tiers and their associated governance requirements
• Establishes audit requirements and retention periods
• Defines the exception and waiver process
• Mandates compliance reporting through the KPI Dashboard

6. Training and Certification

• Mandates completion of the training curriculum before AI tool access
• Requires annual recertification
• Defines advanced training requirements for specific roles (Tech Leads, Security Reviewers)
• Establishes the Maturity Certification as the team-level competency benchmark

7. Incident Response

• Integrates AI-related incidents into the organizational incident response plan
• Defines AI-specific incident categories and severity levels
• Establishes notification and escalation procedures for AI-related incidents
• Requires post-incident review and lessons-learned integration

8. Enforcement and Consequences

• Defines compliance monitoring mechanisms (automated and manual)
• Establishes a graduated enforcement approach: education, warning, access restriction, disciplinary action
• Requires all policy violations to be documented and tracked
• Defines appeal processes for enforcement actions

Rollout Strategy

The organization-wide policy rollout MUST follow a phased approach to ensure adoption without disruption.

Rollout Timeline

Phase	Duration	Activities
Draft and Review	4 weeks	Policy drafted by Governance Lead; reviewed by Security, Legal, Engineering Leadership, and Team Champions
Stakeholder Feedback	2 weeks	Policy shared with all engineering managers and Team Champions for comment; feedback incorporated
Executive Approval	2 weeks	Final review and approval by CTO, CISO, and Legal
Communication	2 weeks	Organization-wide communication campaign; town halls; FAQ published
Grace Period	4 weeks	Policy effective but violations result in education rather than enforcement
Full Enforcement	Ongoing	Policy fully enforced with graduated consequences

Rollout Milestones

• Policy draft completed and reviewed by core team
• Stakeholder feedback collected and incorporated
• Executive approval obtained
• Communication plan executed (all-hands, email, wiki, Slack)
• FAQ document published
• Policy acknowledgment signed by all engineering staff
• Grace period completed
• Full enforcement active

Communication Plan

Effective communication is critical to policy adoption. The following communication activities are REQUIRED:

Activity	Audience	Timing	Owner
Executive announcement	All engineering staff	Policy publication date	CTO
Policy overview town hall	All engineering staff	Within 1 week of publication	Governance Lead + Phase Lead
Manager briefing	All engineering managers	1 week before publication	Phase Lead
Team Champion deep-dive	All Team Champions	1 week before publication	Governance Lead
FAQ publication	All engineering staff	Publication date	Knowledge Sharing Lead
Slack/Teams channel announcement	All engineering staff	Publication date	Phase Lead
Monthly compliance updates	All engineering staff	Monthly during grace period	Governance Lead

Communication Principles

• Explain the "why" — Every communication MUST connect the policy to the organizational goals of quality, security, and productivity
• Acknowledge the journey — Reference the phases completed and the evidence gathered that supports the policy
• Be transparent about enforcement — Clearly communicate the grace period and what happens after
• Provide channels for questions — Every communication MUST include a path for questions and concerns
• Celebrate achievements — Highlight teams and individuals who exemplify excellent AI-assisted engineering practices

Enforcement Mechanisms

Automated Enforcement

The majority of policy enforcement SHOULD be automated through:

• CI/CD pipeline gates — Configured per CI/CD Pipeline Integration to block non-compliant code
• Tool configuration enforcement — Centrally managed configurations that prevent policy violations at the tool level
• Access management — Automated provisioning and deprovisioning based on training completion and policy acknowledgment status
• Audit alerting — Automated alerts for policy-relevant events (unauthorized tool access, configuration changes, anomalous usage)

Manual Enforcement

Automated enforcement is supplemented by:

• Governance audits — Monthly random sample reviews of AI-assisted PRs for compliance
• Team assessments — Quarterly assessments of team-level governance adherence as part of Maturity Certification
• Incident-triggered reviews — Deep-dive reviews triggered by security incidents or repeated violations

Graduated Consequence Framework

Violation Level	Response	Authority
First minor violation	Education: coaching session with Team Champion	Team Champion
Repeated minor violation	Formal warning: documented conversation with manager	Engineering Manager
First major violation	Access restriction: AI tool access suspended pending re-training	Governance Lead
Repeated major violation	Escalation: formal HR process; potential access revocation	Engineering Director + HR
Critical violation (data breach, deliberate circumvention)	Immediate access revocation; incident response; HR disciplinary process	CISO + HR

The organization-wide policy is a living document. It MUST evolve as AI technology advances, as new risks emerge, and as the organization's maturity deepens. The Continuous Improvement processes ensure that policy refinement is systematic rather than reactive.