AI Governance & Compliance — Responsibility and Risk Assessment
AI GOVERNANCE & COMPLIANCE — RESPONSIBILITY AND RISK

This page describes my work — Victoria — focused on AI governance, compliance, and responsibility frameworks.

Technical architecture, knowledge access design, and decision enforcement are addressed in collaboration with Karol, who provides technical and psychological insight into human–AI interaction and decision-making.

AI systems increasingly support decisions that carry legal, financial, and reputational consequences.

My role is to ensure that such systems are governed responsibly, deployed transparently, and remain defensible when their use is questioned.

This is not legal representation.
This is governance, accountability, and risk control.

When governance support is needed

Organizations typically engage governance and compliance support in one of the following situations:

1. Before implementation
When an organization is considering an AI system or automation, but has not yet started development.

2. During design or procurement
When a technical proposal or vendor solution already exists and requires independent governance review.

3. After deployment
When an AI system is already operational but has not undergone a structured governance or compliance assessment.

AI governance audits

I conduct governance and compliance assessments for organizations planning, building, or already deploying AI systems.

Typical audit scope includes:

• AI use-case definition and classification
• data sources and data flows
• knowledge base location and ownership
• decision authority and human oversight
• regulatory and organizational risk exposure

Audit deliverables

• governance and responsibility report
• compliance readiness assessment
• allowed / restricted / prohibited use mapping
• recommendations for technical enforcement

Governance framework

The Protex AI Governance Framework provides a structured reference model used across governance assessments and pilot engagements.

It defines responsibility, decision boundaries, and enforcement logic for AI-supported systems.

View Governance Framework
Background

My background combines legal education, accounting, and organizational governance.

This allows me to assess AI systems not only through regulation, but through operational responsibility, accountability, and long-term organizational impact.

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