Agent Mode AI

CRITICAL INFRASTRUCTURE

Enterprise Risk and Governance

Essential guidance for managing risks, ensuring compliance, and maintaining control in autonomous AI deployments across your organization.

🛡️ SOC 2 Compliant
🔒 ISO 27001
✅ GDPR Ready
🏥 HIPAA Aligned

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Security

Protect against threats, vulnerabilities, and unauthorized access to AI systems

Compliance

Meet regulatory requirements across jurisdictions and industry standards

Privacy

Safeguard sensitive data and ensure user privacy throughout AI operations

Ethics

Implement responsible AI practices ensuring fairness, transparency, and accountability

Contents

Three-Tier Governance Model

Understanding the essential governance structure for enterprise AI deployment ensures proper oversight, management, and control at every organizational level.

Governance Hierarchy

Strategic Oversight

Board-level committees and executive sponsors define AI strategy, risk appetite, and ethical guidelines. Regular reviews ensure alignment with business objectives.

Operational Management

Cross-functional teams manage day-to-day AI operations, monitor performance metrics, and ensure compliance with established policies and procedures.

Technical Controls

Automated monitoring, audit trails, and technical safeguards provide real-time governance enforcement and rapid incident response capabilities.

Compliance Standards

Navigate the essential compliance standards that govern AI deployment in enterprise environments. Understanding these frameworks is crucial for maintaining trust and meeting regulatory requirements.

GDPR

The General Data Protection Regulation sets strict guidelines for data collection and processing. Key requirements include explicit consent, data minimization, right to explanation for AI decisions, and data portability.

SOC 2 Type 2

Service Organization Control 2 certification demonstrates commitment to security, availability, processing integrity, confidentiality, and privacy through continuous monitoring and regular audits.

ISO 27001

International standard for information security management systems (ISMS), providing a systematic approach to managing sensitive company information and ensuring comprehensive security controls.

HIPAA

Health Insurance Portability and Accountability Act ensures protection of patient health information. Critical for AI systems handling medical data, requiring strict access controls and audit trails.

EU AI ACT

Upcoming comprehensive AI regulation categorizing AI systems by risk level. Mandates transparency, human oversight, and specific requirements for high-risk AI applications in critical sectors.

NIST AI RMF

The NIST AI Risk Management Framework provides voluntary guidance for managing AI risks throughout the lifecycle, focusing on trustworthy and responsible AI development and deployment.

90 Day Implementation Plan

Days 1-30: Assessment & Foundation

Discovery Phase
• Conduct comprehensive risk assessment
• Map current AI initiatives and data flows
• Identify applicable compliance requirements
• Establish baseline security metrics
• Form governance committee
• Define roles and responsibilities

Days 31-60: Control Implementation

Build Phase
• Deploy technical security controls
• Implement access management systems
• Create audit logging infrastructure
• Develop policies and procedures
• Train key stakeholders and teams
• Establish monitoring dashboards

Days 61-90: Validation & Optimization

Refine Phase
• Conduct initial compliance audits
• Perform penetration testing
• Run tabletop exercises
• Refine based on findings
• Document lessons learned
• Establish continuous improvement process

Essential Security Measures

Access Control

Implement zero-trust architecture with role-based permissions, multi-factor authentication, and principle of least privilege for all AI system access.

Data Protection

Encrypt data at rest and in transit, implement tokenization for sensitive data, and use secure enclaves for model training and inference.

Model Security

Deploy input validation, output filtering, and adversarial testing to protect against prompt injection and model manipulation attacks.

Monitoring & Audit

Establish comprehensive logging, real-time monitoring, and immutable audit trails for all AI decisions and system activities.

Incident Response

Create AI-specific incident response procedures, including automated detection, escalation protocols, and recovery plans.

Continuous Validation

Regular security assessments, penetration testing, and red team exercises specifically targeting AI vulnerabilities.

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