AI Tool Adoption Governance#

Process, Policy & Standards Document — Version 1.0#

Purpose: This document establishes the organization’s end-to-end process for evaluating, approving, deploying, and continuously governing artificial intelligence (AI) tools. It applies to all AI-powered software — including coding assistants, generative content tools, data-analysis platforms, and autonomous agents — used by employees, contractors, and third parties on behalf of the organization.

Contents#

1. Scope & Applicability
2. Governance Principles
3. Roles & Responsibilities
4. AI Tool Classification Tiers
5. Adoption Lifecycle Process
6. Risk Assessment Framework
7. Data Classification & Usage Boundaries
8. Security Requirements
9. Legal, Compliance & IP
10. Employee Training & Awareness
11. Monitoring, Audit & Metrics
12. Exception & Escalation Process
13. Policy Violations & Enforcement
14. Review & Version Control

• Appendix A — Tool Intake Request Form
• Appendix B — Risk Assessment Scorecard
• Appendix C — Approved / Restricted Tool Registry

1. Scope & Applicability#

This policy applies to all individuals who use, evaluate, procure, or administer AI tools on behalf of the organization, including:

• Full-time and part-time employees across all departments
• Contractors, consultants, and managed service providers
• Third-party developers integrating AI capabilities into organization-owned systems
• Business units evaluating AI tools through vendor proof-of-concept engagements

This policy covers AI tools in the following categories (non-exhaustive):

Out of scope: Academic or personal use on personal devices with no access to company data or systems. However, employees are encouraged to follow these principles in all AI interactions.

2. Governance Principles#

All AI adoption decisions must be grounded in the following principles:

1. Human Oversight AI tools augment human judgment; they do not replace it. All material outputs from AI systems must be reviewed by a qualified human before being relied upon for decisions, published, or committed to production.

2. Data Minimization Only the minimum data necessary to complete a task should be submitted to an AI tool. Sensitive, regulated, or proprietary data should be anonymized or excluded unless a specific control is in place.

3. Transparency Employees must disclose AI use when it materially influences a work product delivered internally or externally, in accordance with the organization’s disclosure standards.

4. Accountability Every approved AI tool has a designated Tool Owner who is accountable for its ongoing governance, policy compliance, and incident response.

5. Security by Default AI tools must meet or exceed the organization’s standard vendor security baseline. Risk must be assessed before deployment, not after.

6. Continuous Review AI capabilities, vendor policies, and threat landscapes evolve rapidly. Governance must be a living process, not a one-time gate. Tools are re-assessed at least quarterly and whenever a material change occurs.

7. Proportionality Controls must be proportionate to risk. Low-risk tools with limited data access should not face the same approval burden as tools processing confidential IP or regulated data.

3. Roles & Responsibilities#

4. AI Tool Classification Tiers#

Every AI tool is assigned a risk tier based on the sensitivity of data it can access, the autonomy of its actions, and its integration depth with organization systems. The tier determines the approval pathway, required controls, and review frequency.

5. Adoption Lifecycle Process#

All AI tools must pass through the following six-stage lifecycle before general availability is granted. Stages may be compressed for Tier 1 tools but may not be skipped entirely.

Stage 1 — Intake & Classification#

Anyone may submit a Tool Intake Request (Appendix A). The submitter works with IT and Security to assign a Tier (§4). Prohibited Tier 4 tools are rejected at this stage with written rationale provided to the requester.

Exit criteria:

• Intake form submitted
• Tier assigned and documented
• Reject notification sent (if Tier 4)

Stage 2 — Risk Assessment#

Information Security and Legal complete the Risk Assessment Scorecard (Appendix B), evaluating data-handling practices, vendor security posture, contractual terms, and IP commitments. Tier 3 tools require an additional legal data-flow analysis.

Exit criteria:

• Completed Risk Assessment Scorecard
• Vendor security questionnaire returned
• DPA reviewed and signed (if required)

Stage 3 — Approval#

Tier 1: Manager approval via email. Tier 2 & 3: AI Governance Committee review in scheduled meeting or async via documented vote. Approval, conditional approval (with required mitigations), or rejection is recorded in the Tool Registry (Appendix C).

Exit criteria:

• Approval decision recorded
• Conditions documented (if conditional)
• Tool Registry updated

Stage 4 — Controlled Pilot#

Approved tools are deployed to a defined pilot group (recommended: 5–20 users for 30 days). A designated Tool Owner monitors for incidents, policy violations, and unexpected data flows. Pilot findings are presented to the approver before general availability.

Exit criteria:

• Pilot group defined and notified
• Tool Owner assigned
• Pilot review meeting held
• No material incidents or exceptions unresolved

Stage 5 — General Availability#

Following a successful pilot, IT provisions enterprise access, training is made available or mandatory (per tier), and the tool is published to the internal approved-tools catalog. The Tool Owner maintains the tool’s entry in the registry.

Exit criteria:

• Enterprise license provisioned
• Training completed (mandatory for Tier 2+)
• Approved-tools catalog updated
• Employee communications sent

Stage 6 — Ongoing Review & Renewal#

The Tool Owner monitors vendor communications for policy changes, new CVEs, and service updates. Reviews occur at the cadence defined by tier. At review, the Tool Owner completes an abbreviated refresh of the Risk Scorecard and escalates any changes that would alter the tool’s tier or conditions.

Exit criteria:

• Review completed at defined cadence
• Risk Scorecard refreshed
• Tool Registry entry updated
• Escalation sent if material change detected

6. Risk Assessment Framework#

Risk is evaluated across five domains. Each domain is scored 1–5 (1 = low risk, 5 = critical risk). The total score informs the tier assignment and the conditions attached to approval.

Tier mapping: Total 5–9 → Tier 1. Total 10–16 → Tier 2. Total 17–22 → Tier 3. Total ≥23 or any domain score of 5 → Tier 4 (Prohibited by default — exception process required).

7. Data Classification & Usage Boundaries#

The following table defines what data may and may not be submitted to AI tools at each classification level. Data owners are responsible for correctly classifying data before submitting it to any AI tool.

Absolute Prohibitions (all tiers)#

• Submitting authentication credentials, API keys, or secrets to any AI tool under any circumstances
• Submitting full database exports, customer lists, or bulk PII to generative AI tools
• Uploading documents subject to legal privilege or attorney-client confidentiality
• Using personal (non-enterprise) accounts on any AI tool to process Internal or above data

8. Security Requirements#

8.1 Baseline Requirements (All Tiers)#

• Multi-factor authentication enforced for all AI tool accounts
• Enterprise licensing used for all tools processing Internal data or above
• Single sign-on (SSO) via corporate identity provider required for Tier 2+
• Employee accounts deprovisioned within 24 hours of offboarding
• Tool access scoped to the minimum necessary permissions (least privilege)

8.2 Code and Agent Security#

• All AI-generated code must pass SAST and secret-scanning checks before merge
• Agentic tools (those that can write files, call APIs, or execute code) require an additional human approval step before any action affecting production systems
• Configuration files that influence AI agent behavior (e.g., rules files, MCP config) are treated as code and subject to peer review and version control
• Workspace Trust or equivalent isolation settings must be enabled on all AI-integrated development environments
• MR/PR size limits are recommended for AI-assisted contributions (suggested: ≤400 lines) to ensure reviewability

8.3 Supply Chain Controls#

• Dependencies generated or suggested by AI tools must be validated against the organization’s approved dependency list before introduction
• AI-suggested packages should be verified for authenticity and version currency before installation
• Dependency scanning runs in CI/CD on all pull requests, including AI-assisted ones

8.4 Incident Response#

• Any suspected exfiltration of confidential data via an AI tool is treated as a Severity 1 security incident and escalated to the CISO within one hour of discovery
• The Tool Owner for the affected tool is notified immediately and assists with containment
• Post-incident review includes assessment of whether the tool’s tier classification should be elevated or tool access suspended

9. Legal, Compliance & Intellectual Property#

9.1 Vendor Agreements#

• A Data Processing Agreement (DPA) is required before any Tier 2+ tool may process Internal or above data. Legal must review and countersign.
• The DPA must confirm that the vendor will not use the organization’s data to train its models, or provide a documented opt-out that IT enforces at the account level.
• Vendor terms of service are reviewed at each renewal and upon material vendor announcement. Changes that affect data use, training, or retention must be escalated to the AI Governance Committee.

9.2 Intellectual Property#

• Employees should review AI-generated content for potential reproduction of third-party copyrighted or open-source material before incorporating it into deliverables.
• For tools with a copyright indemnification commitment (e.g., enterprise coding assistants), employees must ensure they remain within the terms of that commitment.
• AI-generated source code is subject to the same license-compliance scanning applied to all other code contributions.
• Proprietary algorithms, trade secrets, and patentable innovations must not be submitted to external AI tools unless legal counsel has confirmed the engagement is protected.

9.3 Regulatory Compliance#

10. Employee Training & Awareness#

Training completion is tracked in the LMS. Access to Tier 2+ tools is contingent on completion of the relevant training modules. Non-completion is reported to the employee’s manager for follow-up.

11. Monitoring, Audit & Metrics#

11.1 Technical Monitoring#

• Usage logs for Tier 2+ tools retained for a minimum of 90 days for audit and incident response
• Secret scanning and SAST results aggregated into the central security dashboard
• DLP tooling (where deployed) monitors for bulk data transfers to AI tool endpoints
• Tool Owners subscribe to vendor security advisories and CVE feeds for approved tools

11.2 Governance Metrics#

The AI Governance Committee reviews the following metrics quarterly:

11.3 Annual Audit#

An annual internal audit of the AI governance program is conducted by Internal Audit or a designated third party. The audit assesses adherence to this policy, completeness of the Tool Registry, training compliance, and incident response effectiveness. Findings are reported to the AI Governance Committee and executive leadership.

12. Exception & Escalation Process#

A policy exception may be requested when a legitimate business need cannot be met within the standard framework. Exceptions are temporary, documented, and subject to enhanced monitoring.

Exception request process:

1. The requestor submits a written exception request to the AI Governance Committee, describing the business need, the specific policy provision being excepted, the proposed alternative controls, and a defined expiry date (maximum 90 days).
2. Information Security assesses the incremental risk and proposes mitigating controls.
3. The AI Governance Committee votes to approve, approve with conditions, or reject. Tier 4 exceptions additionally require executive sponsor sign-off.
4. Approved exceptions are logged in the Exception Register with conditions, expiry date, and assigned monitor.
5. Before expiry, the requestor must either remediate (bring into compliance) or submit a renewal request. Exceptions cannot be auto-renewed.

Escalation path: Any employee may escalate a governance concern directly to the CISO or General Counsel without going through their manager. Anonymous reporting is available via the ethics hotline. Retaliation against good-faith reporters is a violation of company policy.

13. Policy Violations & Enforcement#

Violations of this policy are taken seriously and may result in disciplinary action, up to and including termination of employment or contract. The severity of response is proportionate to the nature and impact of the violation.

Contractors and third parties are subject to equivalent obligations under their service agreements. Violations by third parties may result in contract termination.

14. Review & Version Control#

This document is reviewed quarterly by the AI Governance Committee and updated as required. An out-of-cycle review is triggered by any of the following:

• A Severity 1 AI-related security incident
• A material change in applicable law or regulation
• A significant vendor policy change affecting two or more approved tools
• The introduction of a new AI capability tier not covered by the current framework

Acknowledgment: All employees are required to acknowledge receipt and understanding of this policy annually via the HR system. New hires acknowledge during onboarding. Continued use of AI tools constitutes acceptance of the terms of this policy.

Appendix A — Tool Intake Request Form#

Submit this form to the AI Governance Committee to initiate evaluation of a new AI tool.

Appendix B — Risk Assessment Scorecard#

Completed by Information Security and Legal. Score each domain 1–5 per the criteria in §6.

Tier assignment:

Assessor: _______________________    Date: ___________    CISO Sign-off: _______________________

Appendix C — Approved / Restricted Tool Registry#

Maintained by each AI Tooling Owner. Reviewed by the AI Governance Committee quarterly. Only tools with status Approved may be used by employees.

Status definitions:

• Approved — may be used per conditions listed
• Conditional — approved with mandatory controls; access restricted until conditions met
• Under Review — evaluation in progress; do not use pending outcome
• Retired — previously approved but decommissioned
• Prohibited — must not be used; exception process required

[Organization Name] · AI Tool Adoption Governance Policy · Version 1.0 · INTERNAL — NOT FOR DISTRIBUTION · Questions: [ai-governance@organization.com]