Use Case Triage
Purpose, owner, users, affected people, decision criticality and model type.
AI GOVERNANCE × GRC × CYBERSECURITY
Govern AI before AI governs risk.
I’m Tegh Virk — a GRC, audit, and information security professional applying proven control thinking to AI governance, responsible AI, model risk, and enterprise AI assurance. Govern.
AI Governance FocusNIST AI RMF · ISO/IEC 42001
Trust LayerRisk · Controls · Assurance
FoundationCISA · Security+ · ISO Audit
AI GOVERNANCE ROUTESSELECT MODULE
AI GOVERNANCE · MODEL INVENTORY · IMPACT ASSESSMENT · HUMAN OVERSIGHT · DATA GOVERNANCE · MODEL MONITORING · GENAI RISK · TRANSPARENCY · THIRD-PARTY AI · AI INCIDENT RESPONSE ·
02 / GOVERNANCE OPERATING SYSTEM
Turn AI principles into operational controls.
The governance layer connects strategy, ownership, risk classification, data governance, human oversight, testing, monitoring, third-party assurance, and incident management into one auditable control environment.
CONTROL STACKLIVE
GOV-01AI Inventory & Ownership
Identify models, use cases, vendors, accountable owners, business purpose and lifecycle status.
RISK-02AI Impact & Risk Assessment
Classify potential harms, affected stakeholders, data sensitivity, security and regulatory exposure.
HUM-03Human Oversight
Define decision rights, escalation paths, override authority and review requirements.
MON-04Post-Deployment Monitoring
Track model quality, drift, incidents, complaints, control failures and material changes.
03 / AI LIFECYCLE ASSURANCE
Governance follows the model from idea to retirement.
The strongest AI governance program is not a one-time compliance review. It follows the system lifecycle—before procurement or development, through testing and deployment, and into continuous monitoring and eventual retirement.
AI Impact Assessment
Risk tier, privacy, security, safety, fairness, transparency and legal impact.
Testing & Evaluation
Robustness, misuse, hallucination, prompt-injection, bias and control effectiveness.
Monitoring & Change
Drift, incidents, model updates, vendor changes, user feedback and re-approval.
AI
ASSURANCE
ASSURANCE
01INTAKE
02ASSESS
03TEST
04APPROVE
05MONITOR
06RETIRE
04 / REGULATORY & RISK RADAR
One control layer. Multiple AI regimes.
The portfolio centers on translating AI requirements into reusable governance controls instead of managing every framework in isolation.
NIST AI RMF
Use the Govern, Map, Measure and Manage functions to structure trustworthy AI risk management.
ISO/IEC 42001
Build an Artificial Intelligence Management System with policies, objectives, risk treatment and continual improvement.
NIST GenAI Profile
Extend AI risk management to generative-AI risks and corresponding risk-management actions.
EU AI Act
Risk-based obligations, AI literacy, GPAI governance and transparency requirements inform enterprise control design.
MODEL RISKLEGALSECURITYTRUST
05 / EXPERIENCE BRIDGE
Existing GRC depth, redirected toward AI assurance.
My AI-governance positioning is grounded in real audit, security, access, process-control and compliance work—not a fictional AI job title.
2026
Stanford Health Care — IT Intern
Clinical and enterprise technology support across ServiceNow, Epic, Workday, access workflows, software governance, audit readiness and endpoint operations.
2022 — Present
Fabrinet — Process Technician
Controlled documentation, quality compliance, audit evidence, CAPA, traceability, test procedures and change control in electronics manufacturing.
2021 — 2022
PwC — Associate, IT Audit
NIST-based assessments, ITGC / SOX / ISO 27001 audit work, ISMS policies, control validation, risk reporting and security awareness.
2021
Deloitte — Audit Intern
Third-party compliance, data risk assessments, security-standard exceptions, evidence gathering, maturity assessments and remediation recommendations.
06 / TRUST CREDENTIALS
Audit credentials behind the AI governance story.
CISA
Certified Information Systems Auditor · ISACA
Security+
CompTIA Security+
CSM
Certified Scrum Master · Scrum Alliance
ISO/IEC 27701
Lead Auditor credential
NIST AI RMF · ISO/IEC 42001 · GenAI Governance
Portfolio focus: control mapping, AI inventories, impact assessments, human oversight, AI vendor risk, model monitoring, AI incident response and regulatory traceability.
UPES · Stanford · UC Santa Cruz · Year Up United
B.Tech Computer Science, Product Market Fit, Project & Program Management, and Network Security.
07 / CONTACT
Building the control layer for responsible enterprise AI.
Open to AI Governance, Responsible AI, GRC, AI Risk, IT Audit, Cybersecurity, Trust & Safety, and Information Security conversations.