AI Governance Policy Template for Marketing

# AI Governance Policy for Marketing **Document Version:** [VERSION_NUMBER] **Effective Date:** [DATE] **Last Reviewed:** [DATE] **Policy Owner:** [CMO_NAME], Chief Marketing Officer **Approval Authority:** [EXECUTIVE_SPONSOR_TITLE] --- ## 1. Executive Summary This policy establishes governance frameworks for the adoption, deployment, and management of artificial intelligence tools and systems within the [COMPANY_NAME] marketing department. The policy balances innovation velocity with risk management, ensuring AI initiatives align with corporate strategy, regulatory requirements, and brand values. **Policy Scope:** [DESCRIBE_SCOPE: e.g., "All marketing team members, vendors, and contractors using AI tools for customer-facing or internal marketing operations"] **Policy Objectives:** - Enable rapid, responsible AI adoption across marketing functions - Establish clear accountability and approval workflows - Protect customer data, brand reputation, and regulatory compliance - Ensure transparency in AI-driven marketing decisions - Maintain competitive advantage through controlled innovation --- ## 2. AI Tool Classification Framework All AI tools are classified by risk level to determine approval requirements and oversight intensity. | **Classification** | **Definition** | **Examples** | **Approval Required** | **Review Frequency** | |---|---|---|---|---| | **Tier 1: Low Risk** | Non-customer-facing, internal productivity tools with minimal data exposure | Grammar checking, scheduling assistants, internal summarization | Manager sign-off | Quarterly | | **Tier 2: Medium Risk** | Customer-facing or data-adjacent tools with moderate brand/compliance impact | Content generation, email personalization, audience segmentation | [APPROVAL_ROLE] + Legal review | Monthly | | **Tier 3: High Risk** | Customer-facing, sensitive data processing, or significant brand/regulatory implications | Chatbots, dynamic pricing, predictive customer modeling, autonomous campaign optimization | CMO + Legal + Compliance + [SPONSOR] | Weekly + quarterly audit | | **Tier 4: Restricted** | Prohibited without explicit executive approval | Deepfakes, autonomous customer communication without human review, real-time behavioral manipulation | Board-level approval required | N/A | --- ## 3. AI Tool Approval Workflow ### 3.1 Submission Requirements All new AI tools or significant expansions of existing tools require submission via [SUBMISSION_PROCESS/SYSTEM]. **Required Information:** - Tool name, vendor, and primary use case - Classification tier (self-assessed; reviewer will validate) - Data inputs: What data does this tool access? (customer data, internal data, third-party data) - Data outputs: What does the tool produce? How is it used downstream? - Customer impact: Does this tool affect customer experience, personalization, or decision-making? - Compliance considerations: GDPR, CCPA, industry-specific regulations, brand guidelines - Cost and resource requirements - Risk mitigation measures already in place - Vendor security certifications and SLAs - Pilot timeline and success metrics ### 3.2 Approval Timeline | **Tier** | **Submission to Decision** | **Decision Authority** | **Escalation Path** | |---|---|---|---| | Tier 1 | 3 business days | Direct manager | [ROLE_NAME] | | Tier 2 | 5 business days | [APPROVAL_ROLE] + Legal | CMO | | Tier 3 | 10 business days | CMO + Legal + Compliance + [SPONSOR] | CEO | | Tier 4 | 15+ business days | Board-level committee | Board | --- ## 4. Data Governance and Security Requirements ### 4.1 Data Classification Marketing teams must classify all data inputs to AI tools: - **Public:** No restrictions; can be shared with external AI vendors - **Internal:** Company confidential; requires vendor NDA and encryption - **Customer Personal Data:** PII, behavioral data, purchase history; requires explicit legal review and customer consent mechanisms - **Restricted:** Sensitive financial, health, or biometric data; prohibited from external AI tools without board approval ### 4.2 Vendor Requirements All AI vendors must meet the following minimum standards: - SOC 2 Type II certification (or equivalent) - Data processing agreement (DPA) compliant with [GDPR/CCPA/LOCAL_REGULATIONS] - Encryption in transit and at rest - No use of customer data for vendor model training without explicit opt-in - 30-day notice for security incidents - Annual security audit rights - Data deletion upon contract termination ### 4.3 Data Retention and Deletion - AI-generated outputs containing customer data must be retained only as long as operationally necessary - Minimum retention: [TIMEFRAME] - Maximum retention: [TIMEFRAME] - Deletion must be completed within [TIMEFRAME] of campaign/project closure - Quarterly audit of data retention compliance --- ## 5. Brand Safety and Output Quality Standards ### 5.1 Content Review Requirements | **Use Case** | **AI Output Type** | **Human Review Required** | **Approval Authority** | |---|---|---|---| | Email subject lines | Generative text | Yes, before send | Campaign manager | | Social media captions | Generative text | Yes, before publish | Social media manager | | Website copy | Generative text | Yes, before deploy | Content lead | | Customer service responses | Generative text | Yes, real-time or post-send review | [SUPPORT_LEAD] | | Audience segmentation | Algorithmic decision | Yes, before activation | Analytics lead | | Bid optimization | Algorithmic decision | Spot-check monthly | [PAID_MEDIA_LEAD] | | Predictive recommendations | Algorithmic decision | Quarterly bias audit | [DATA_SCIENCE_LEAD] | ### 5.2 Brand Safety Guardrails All AI tools must include or be configured with: - Tone and voice guidelines aligned to [BRAND_VOICE_DOCUMENT] - Prohibited topics and language filters: [LIST_EXAMPLES] - Fact-checking protocols for claims about [PRODUCT/SERVICE] - Bias detection and mitigation for protected characteristics - Escalation triggers for controversial or sensitive content --- ## 6. Transparency and Disclosure Requirements ### 6.1 Customer-Facing Disclosure When AI is used in customer-facing marketing, the following disclosure standards apply: - **AI-generated creative:** Disclose if [THRESHOLD_PERCENT]% or more of content is AI-generated - **Personalization:** Disclose use of predictive algorithms in email subject lines, product recommendations, or dynamic pricing - **Chatbots:** Always identify as AI-powered; provide human escalation option - **Deepfakes or synthetic media:** Explicit disclosure required; prohibited for [SPECIFIC_CONTEXTS] **Disclosure Format:** [PROVIDE_TEMPLATE_OR_EXAMPLES] ### 6.2 Internal Transparency - All AI-driven campaign decisions must be documented with rationale - Monthly AI usage report to [STAKEHOLDER_GROUP] - Quarterly review of AI tool performance against baseline metrics - Annual audit of AI governance compliance --- ## 7. Performance Monitoring and Audit ### 7.1 Key Metrics by Tier | **Tier** | **Monitoring Metrics** | **Review Cadence** | **Owner** | |---|---|---|---| | Tier 1 | Tool adoption, user satisfaction | Quarterly | Manager | | Tier 2 | Output quality, customer impact, cost efficiency | Monthly | [APPROVAL_ROLE] | | Tier 3 | Quality, compliance, bias, customer satisfaction, cost ROI | Weekly + monthly deep dive | CMO + Compliance | | Tier 4 | All Tier 3 metrics + board-level KPIs | Weekly | CEO + Board | ### 7.2 Audit and Compliance Review - **Quarterly:** Spot-check AI outputs for brand safety and accuracy - **Semi-annual:** Vendor security and compliance audit - **Annual:** Full governance policy review and update - **Incident-triggered:** Immediate review of any AI-related brand, compliance, or customer impact incidents --- ## 8. Roles and Responsibilities | **Role** | **Responsibilities** | |---|---| | **CMO** | Overall AI governance oversight; Tier 3+ approvals; escalation authority | | **AI Governance Lead** | [TITLE/ROLE]: Day-to-day policy administration; submission review; training | | **Legal & Compliance** | Data protection; regulatory compliance; vendor agreements; incident response | | **Data Security** | Vendor security vetting; data classification; breach investigation | | **Team Managers** | Tier 1 approvals; team training; monitoring tool usage | | **Individual Contributors** | Responsible use; reporting concerns; compliance with policy | --- ## 9. Training and Accountability ### 9.1 Required Training - **All marketing staff:** AI governance policy overview (annual, 30 minutes) - **Tool users (Tier 2+):** Responsible AI use and brand safety (before tool access, then annually) - **Approval authorities:** Full governance framework and decision-making (quarterly) - **Managers:** Oversight and monitoring responsibilities (semi-annual) ### 9.2 Violations and Consequences - **Minor violations** (e.g., using unapproved Tier 1 tool): Written warning + retraining - **Moderate violations** (e.g., sharing customer data with unapproved vendor): Suspension of AI tool access + investigation - **Severe violations** (e.g., circumventing approval process for Tier 3+ tools): Disciplinary action up to termination --- ## 10. Policy Review and Updates This policy will be reviewed and updated [FREQUENCY: quarterly/semi-annually/annually] or as needed in response to: - Regulatory changes - Significant AI technology shifts - Governance incidents or near-misses - Stakeholder feedback - Industry best practice updates **Next Scheduled Review:** [DATE] --- ## Appendix A: AI Tool Submission Form [LINK_TO_FORM_OR_SYSTEM] ## Appendix B: Vendor Security Checklist [LINK_TO_CHECKLIST] ## Appendix C: Brand Safety Guidelines [LINK_TO_GUIDELINES] ## Appendix D: Incident Reporting Process [LINK_TO_PROCESS] --- **Approval Signatures:** | **Role** | **Name** | **Date** | **Signature** | |---|---|---|---| | Chief Marketing Officer | [NAME] | [DATE] | | | Chief Legal Officer | [NAME] | [DATE] | | | Chief Information Security Officer | [NAME] | [DATE] | | | [EXECUTIVE_SPONSOR] | [NAME] | [DATE] | |