This document defines mandatory security, privacy, and governance rules for all personnel using artificial intelligence technologies. It covers internal operations, software development lifecycles, and client deliverables.
1. Scope and Applicability
This policy applies to all employees, contractors, and third parties accessing company networks or working on client deliverables. It governs all forms of AI, including large language models, code generation assistants, image generators, and machine learning APIs.
2. Approved AI Systems and Shadow AI Prohibition
Authorized Tools: Employees must strictly use AI platforms evaluated and formally approved by the Security and Legal teams.
Shadow AI Ban: Running company data or code through unapproved consumer-grade AI tools is strictly prohibited.
Vendor Data Protections: Any deployed tool requires enterprise terms prohibiting the vendor from using our inputs or prompts to train their foundational models.
3. Data Classification and Input Controls
Confidential Data: Do not input trade secrets, financial records, client credentials, system architecture diagrams, or API keys into any AI tool.
Regulated Information: Never submit personally identifiable information (PII), protected health information (PHI), or payment card data into AI models without tokenization or anonymization.
Data Minimization: Strip all non-essential context and identifiers before submitting queries to approved AI platforms.
4. AI in Software Engineering
License Compliance: Programmers must configure AI coding tools to block suggestions matching public code repositories with restrictive licenses like GPL.
Code Ownership: AI-generated code must integrate safely without creating intellectual property risks for clients.
Automated Scanning: All code generated by AI must pass the standard security pipeline. This includes static code analysis (SAST), dynamic testing (DAST), and software composition analysis (SCA).
Human Verification: Engineers remain directly accountable for every line of code. You must review, test, and debug all AI suggestions before merging into the main branch.
5. Infrastructure and Security Controls
Access Management: Access to AI APIs and development environments follows the principle of least privilege. Multi-factor authentication is mandatory.
Encryption: AI API transmissions require TLS 1.3 encryption in transit. All stored prompt histories and cached responses require AES-256 encryption at rest.
Zero Data Retention: Enterprise API agreements must enforce zero data retention rules on external vendor servers.
Adversarial Defense: Engineering teams building custom AI features must test against prompt injection, jailbreaking, and data extraction attacks.
6. Client Transparency and Governance
Written Consent: Teams must obtain written authorization from the client before using AI tools on custom deliverables or processing client datasets.
Attribution and Logs: Log all components in a client deliverable containing AI-generated code or content.
Bias and Quality Audits: Custom models built for clients require structured testing for accuracy, algorithmic bias, and edge-case reliability before release.
7. Roles and Responsibilities
Enforcement: The Chief Information Security Officer (CISO) holds final authority for enforcing these rules.
Legal Oversight: The Data Protection Officer (DPO) ensures all AI usage complies with regional data privacy laws.
Management Duty: Department heads must ensure their teams operate within these guidelines daily.
8. Policy Maintenance and Exceptions
Review Cycle: The security committee reviews and updates this document quarterly to address new technological threats.
Exceptions Process: Project managers needing temporary exceptions for unique client requirements must submit a formal request to the CISO for written approval.
9. Operational Processes and Training
Risk Assessment Framework: The security team evaluates new AI vendors against strict criteria, including data localization, compliance certifications, and security testing history, before granting approval.
Mandatory Training: All personnel must complete AI-specific security modules during onboarding and annually thereafter.
Internal Data Subject Rights: Employees retain the right to request access, correction, or deletion of their personal data processed by internal AI systems. Contact human resources to initiate a request.
10. Incident Management and Enforcement
Incident Reporting: Staff must report accidental disclosures of sensitive data into AI systems to the Security Incident Response Team within one hour.
Audit Logging: The company logs and monitors all enterprise AI platform interactions for compliance verification.
Compliance: Violations of this policy lead to disciplinary action. We will pursue legal action for intentional data exfiltration.
