Compliance and Governance Automation

Use AI to automate SOC 2, HIPAA, and PCI-DSS compliance — continuous evidence collection, policy generation, and audit preparation.

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Compliance isn’t a checkbox you hit once a year. It’s a continuous practice — and AI turns the quarterly panic into an always-ready state.

🔄 Quick Recall: In the previous lesson, you built AI-powered monitoring and incident response. Compliance ensures your security practices meet regulatory standards — and AI proves it continuously, not just at audit time.

Compliance Framework Mapping

Understanding Your Requirements

Map our technology stack to compliance requirements:

Stack:
- AWS (EKS, RDS, S3, Lambda)
- Kubernetes 1.29
- PostgreSQL with PII data
- REST API serving healthcare clients

Compliance requirements: SOC 2 Type II, HIPAA

For each compliance control, show:
1. The control requirement (in plain language)
2. Which AWS service / tool provides evidence
3. What configuration is needed
4. How to automate evidence collection
5. Common audit findings for this control

Focus on the top 20 highest-risk controls.

Policy Generation

Security Policy Framework

Generate an information security policy for our organization:

Company: SaaS company, 50 employees, healthcare data
Compliance: SOC 2, HIPAA
Cloud: AWS

Sections needed:
1. Access Control Policy
   - User provisioning/deprovisioning
   - MFA requirements
   - Privileged access management
   - Access review cadence
2. Incident Response Policy
   - Classification criteria
   - Response procedures
   - Communication requirements
   - Regulatory notification timelines
3. Data Protection Policy
   - Classification scheme
   - Encryption requirements
   - Retention and disposal
   - Breach notification
4. Change Management Policy
   - Change approval process
   - Emergency change procedures
   - Rollback requirements

For each section:
- Standard policy language
- [CUSTOMIZE] markers where we need to insert our specifics
- Implementation guidance

✅ Quick Check: Your access control policy requires quarterly access reviews. It’s been 5 months since the last review. An auditor finds this gap. What’s the AI-powered fix, both for the current gap and to prevent it in the future? (Answer: For the current gap: run the review immediately and document a remediation plan. For prevention: automate the review — AI scripts that query IAM users monthly, flag accounts with excessive privileges or no activity in 90 days, and generate a review report for the security team. The report goes out automatically; the team just reviews and acts on it. Automation turns a forgotten quarterly task into a monthly automated report.)

Evidence Collection Automation

AWS Evidence Script Generation

Generate scripts to automatically collect SOC 2 evidence
from our AWS environment:

Controls to cover:
1. CC6.1 - Logical access controls
   → IAM users, roles, policies, MFA status
2. CC6.2 - Authentication mechanisms
   → Password policy, MFA enforcement
3. CC6.3 - Access authorization
   → IAM policy attachments, role assignments
4. CC7.1 - System monitoring
   → CloudTrail status, GuardDuty findings
5. CC7.2 - Anomaly detection
   → CloudWatch alerts, Security Hub findings
6. CC8.1 - Change management
   → CodePipeline deployments, approval records

For each control, generate:
- AWS CLI command to extract evidence
- Expected output format
- How to store as audit artifact
- Schedule (daily, weekly, monthly)

Compliance Dashboard

Design a compliance monitoring dashboard that shows:

1. Overall compliance score (% of controls passing)
2. Control-by-control status (red/yellow/green)
3. Evidence collection status (automated vs. manual)
4. Open findings and remediation deadlines
5. Upcoming audit milestones

Data sources:
- AWS Config rules
- AWS Security Hub
- Custom compliance scripts
- Jira tickets for remediation items

Describe the dashboard layout and the queries/metrics
for each section.

Audit Preparation

Pre-Audit Readiness Check

Generate a SOC 2 Type II audit readiness checklist:

Audit period: [start] to [end]
Scope: Our SaaS application and supporting infrastructure
Auditor: [firm name]

For each Trust Services Criteria:
1. Security (CC series)
2. Availability (A series)
3. Confidentiality (C series)

Check:
- Is automated evidence collection configured? [Y/N]
- Is the evidence complete for the full audit period? [Y/N]
- Are there any gaps in evidence? [describe]
- Are all policies current and approved? [Y/N]
- Are all identified risks documented with mitigations? [Y/N]

Generate the checklist with specific items for each criteria.

Practice Exercise

Map your tech stack to one compliance framework using the mapping prompt
Generate a security policy section using AI and customize it for your organization
Create an evidence collection script for one SOC 2 control

Key Takeaways

Continuous compliance (automated evidence collection) eliminates the quarterly audit scramble
AI-generated policies are frameworks — customize them to match your actual practices, not aspirational ones
Compliance scope expansion has real costs — AI helps quantify them before architecture decisions
Evidence automation saves hundreds of hours per audit cycle
The best compliance program runs like monitoring: always on, always current, always auditable

Up Next

In the next lesson, you’ll learn advanced threat defense — proactive security measures including threat modeling, penetration test support, and zero-trust architecture with AI.

Knowledge Check

1. Your SOC 2 audit is in 3 months. Your team has been collecting compliance evidence manually — screenshots, spreadsheets, email confirmations. What's the AI-powered alternative?

Start collecting evidence faster Implement continuous compliance: automated evidence collection from your infrastructure (AWS Config, CloudTrail, Kubernetes audit logs), AI-generated compliance reports mapping evidence to SOC 2 controls, and real-time dashboards showing compliance status. By audit time, all evidence is already organized and current — no scramble needed Hire a compliance consultant

2. AI generates a security policy document for your organization. It's 40 pages of comprehensive policies covering access control, incident response, data protection, and more. Should you adopt it as-is?

Yes — AI covered everything No — AI generates comprehensive but generic policies. You need to customize for your actual practices: What's your specific access review cadence? Who approves production access? What's your actual data classification scheme? Use AI's output as a framework and edit each section to reflect what your organization actually does. A policy that describes what you do is enforceable; one that describes an ideal is not 40 pages is too long — compress it

3. Your company processes credit card data (PCI-DSS scope). An engineer proposes storing card numbers in a new microservice to 'simplify the architecture.' How does AI help evaluate this decision?

AI can't evaluate architecture decisions AI maps the proposal to PCI-DSS requirements: adding a new service that stores card data expands your compliance scope (more systems to audit, more controls to implement, more evidence to collect). AI calculates the compliance cost of scope expansion vs. the engineering benefit of simpler architecture — often, the compliance cost far exceeds the engineering savings If it simplifies architecture, do it

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