An enterprise AI plan provides organizational security, governance, compliance, and access controls for AI services. It is safer than sending confidential data to consumer tools. section 1.6.1 section 6.8
Check these protections before using an enterprise AI service:
- Use private endpoints, IAM controls, encryption, auditing, and approved security settings where available. section 1.6.1
- Confirm data-handling policies, regulatory requirements, retention settings, and security-team approval. section 1.6.1 section 6.8
- Avoid using AI alone for critical regulated data; use trained staff or certified specialized software instead. section 6.8
Support-log anonymization
An approved enterprise tool can replace customer names, email addresses, and account numbers in many support logs while preserving structure. Test sample data, review edge cases, and remember that anonymization is not perfect. section 6.8
Table 1.6 Fundamental considerations for AI data security
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Concern
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Effect
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|---|---|
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Data movement
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Information sent to AI services leaves your corporate network for cloud processing, potentially exposing sensitive data.
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Data retention
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AI providers may store and retain submitted data for model training unless explicitly disabled.
|
|
Compliance
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Data handling must align with regulations like GDPR, the Health Insurance Portability and Accountability Act (HIPAA), Service Organization Control 2 (SOC 2), ISO 27001, and industry-specific standards.
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|
Model security
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Unauthorized access or adversarial attacks can compromise AI models, leading to data leakage, biased outputs, or manipulation.
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|
Access control
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Improper identity and access management (IAM) policies can result in unauthorized users gaining access to sensitive AI-generated insights.
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Encryption and data privacy
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Not all AI services offer end-to-end encryption or customer-managed encryption keys (CMEK), affecting data confidentiality.
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Auditability and logging
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Lack of robust logging can make it difficult to track data usage, detect anomalies, or comply with security audits.
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Use the security table to compare data movement, retention, compliance, model security, access control, and privacy concerns. section 1.6.1
