- Enterprise AI systems require robust security across data handling, access controls, and audit capabilities
- Key certifications to look for: SOC 2 Type II, ISO 27001, and industry-specific compliance (HIPAA, etc.)
- Vendor evaluation should cover data residency, encryption, access controls, and incident response
As enterprises adopt AI at scale, security has become the critical gating factor. AI systems often require access to sensitive data across the organization, making security architecture a board-level concern.
This guide provides a comprehensive framework for evaluating AI security. Whether you're a CISO assessing risk, a procurement team evaluating vendors, or a business leader sponsoring AI initiatives, you'll find practical guidance for ensuring your AI deployment meets enterprise security requirements.
AI Security Fundamentals
Enterprise AI security encompasses several key domains:
Data Security: How data is collected, processed, stored, and protected throughout the AI lifecycle.
Model Security: Protecting AI models from tampering, extraction, and adversarial attacks.
Access Security: Ensuring only authorized users and systems can access AI capabilities and underlying data.
Operational Security: Monitoring, logging, and responding to security events in AI systems.
Compliance Security: Meeting regulatory and contractual obligations for AI use.
Data Protection Requirements
AI systems must protect data at every stage:
At Rest: All stored data encrypted with enterprise-grade algorithms (AES-256 or equivalent)
In Transit: TLS 1.3 for all data transmission, including internal service communication
In Processing: Secure enclaves or equivalent for sensitive computation
In Output: Preventing data leakage through AI-generated content
Data Residency: Options for data location to meet regulatory requirements
Access Control Architecture
Robust access controls are essential:
Authentication: SSO integration, MFA support, session management
Authorization: Role-based access (RBAC), attribute-based access (ABAC)
Data-level permissions: AI respects existing document and system permissions
Audit logging: Complete record of all access and actions
Principle of least privilege: AI accesses only what's needed for each task
Compliance & Certifications
Key certifications to evaluate:
SOC 2 Type II: Independent audit of security controls, tested over time
ISO 27001: International standard for information security management
HIPAA: Required for healthcare data (US)
GDPR: Required for EU personal data
FedRAMP: Required for US government use
Ensure certifications are current and cover the specific services you'll use.
Vendor Evaluation Framework
When evaluating AI vendors, assess:
Security Architecture
- Where is data processed and stored?
- What encryption is used?
- How are keys managed?
Access Controls
- SSO/SAML integration?
- Granular permission controls?
- Admin audit capabilities?
Compliance
- Current certifications?
- Compliance roadmap?
- Willing to sign BAA/DPA?
Incident Response
- SLA for security incidents?
- Notification procedures?
- Post-incident reporting?
Security Practices
- Penetration testing frequency?
- Bug bounty program?
- Security team size and expertise?
Enterprise-Grade Security with Kolossus
Kolossus is built for enterprise security requirements:
- SOC 2 Type II certified with annual audits
- End-to-end encryption for data at rest and in transit
- SSO/SAML integration with all major identity providers
- Granular permissions that respect your existing access controls
- Complete audit logging of all AI actions and data access
- Data residency options for regulatory compliance
Deploy AI with confidence that your data is protected.
Written by
Kolossus Team
Product & Research
Expert in AI agents and enterprise automation. Sharing insights on how organizations can leverage AI to transform their workflows.
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