SOC 2 Checklist for AI & Machine Learning
AI startups face unique security challenges around data privacy and model integrity. Your SOC 2 audit needs to prove you protect sensitive training data and prevent prompt injection or model theft.
Critical AI-ML Controls
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Complete SOC 2 Checklist
Broken down by compliance domain for AI & Machine Learning teams.
Data Governance & Privacy
- Sensitive user data scrubbed or anonymized before being used for model training.
- Clear opt-out mechanism for users who do not want their data used for training.
- Audit trail for all datasets used to train production models.
- Encryption of data at rest in vector databases and object storage.
Model & Infrastructure Security
- Model weights and parameters stored in encrypted, access-restricted storage.
- Inference APIs protected by rate limiting and authentication.
- Regular security testing for AI-specific vulnerabilities (e.g., prompt injection).
- Logical separation of training and inference environments.
Operational Controls
- Monitoring for model drift and anomalous inference patterns.
- Documented process for model versioning and rollback.
- Formal AI Acceptable Use Policy for employees.
- Human-in-the-loop (HITL) processes for high-stakes AI decisions.
Evidence pack to prepare
- •Access review records with approvals
- •Change management tickets with reviewers
- •Incident response runbooks and recent drills
- •Vendor risk assessment summaries
- •System inventory and data flow diagrams
AI & Machine Learning audit timeline
- 1.Week 1–2: Define scope and control owners
- 2.Week 3–5: Implement evidence collection workflows
- 3.Week 6–8: Run internal readiness review
- 4.Week 9–12: Complete auditor fieldwork and remediation
Common AI & Machine Learning Pitfalls
Storing sensitive training data in unencrypted S3 buckets.
Lack of visibility into third-party LLM provider data handling (e.g., OpenAI Enterprise BAAs).
Assuming standard web application firewalls (WAFs) protect against prompt injection.
Failure to document the "black box" nature of AI models during risk assessments.
Raphael N
Head of Compliance Strategy
Raphael leads go-to-market compliance strategy for high-growth SaaS and AI teams. With over a decade of experience across Big Four firms and fintech startups, he specializes in translating complex SOC 2 requirements into automated, engineering-friendly workflows.
Frequently Asked Questions
What is the first step in SOC 2 Checklist for AI & Machine Learning?
The first step is conducting a gap analysis to understand your current security posture relative to SOC 2 requirements. This identifies what controls you already have and what needs to be implemented.
How long does SOC 2 Checklist for AI & Machine Learning typically take?
For most mid-sized companies, the process takes 3-6 months. This includes 2-3 months for readiness prep and control implementation, followed by the audit period and report generation.
What are the core requirements for SOC 2 Checklist for AI & Machine Learning?
Core requirements include established security policies, evidence of operational controls (like access reviews and vulnerability scans), and documented risk management processes aligned with SOC 2 standards.
Can we automate SOC 2 Checklist for AI & Machine Learning?
Yes, compliance automation platforms can reduce manual effort by up to 80% through continuous evidence collection and automated control monitoring. However, you still need to define and own the underlying security processes.
About RiscLens
Our mission is to provide transparency and clarity to early-stage technology companies navigating the complexities of SOC 2 (System and Organization Controls 2) compliance.
Who we serve
Built specifically for early-stage and growing technology companies—SaaS, fintech, and healthcare tech—preparing for their first SOC 2 audit or responding to enterprise customer requirements.
What we provide
Clarity before commitment. We help teams understand realistic cost ranges, timeline expectations, and common gaps before they engage auditors or expensive compliance vendors.
Our Boundaries
We do not provide legal advice, audit services, or certifications. Our assessments support internal planning—they are not a substitute for professional compliance guidance.
SOC 2 (System and Organization Controls 2) is a voluntary compliance standard for service organizations, developed by the AICPA, which specifies how organizations should manage customer data based on the Trust Services Criteria: security, availability, processing integrity, confidentiality, and privacy.
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