SAN FRANCISCO -
June 24, 2025 -
PRLog -- Before regulations lock in and risks snowball, lay down a pragmatic framework that inventories every model, assigns accountable owners, embeds proven standards (NIST, ISO/IEC 42001), and hard-wires continuous monitoring. The action plan below shows how to move from scattered experiments to a disciplined, risk-tiered governance foundation—fast.
Waiting for perfect regulations or tools is a recipe for falling behind. Start pragmatic, start now, and scale intelligently.
Key Steps: - Audit & Risk-Assess Existing AI: Don't fly blind.
- Inventory: Catalog all AI/ML systems in use or development (including "shadow IT" and vendor-provided AI).
- Risk Tiering: Classify each system based on potential impact using frameworks like the EU AI Act categories (Unacceptable, High, Limited, Minimal Risk). Focus first on High-Risk applications (e.g., HR, lending, healthcare, critical infrastructure, law enforcement). What's the potential harm if it fails (bias, safety, security, financial)?
- Assign Clear Ownership & Structure: Governance fails without accountability.
- Establish an AI Governance Council: A cross-functional team is non-negotiable. Include senior leaders from:
- Legal & Compliance: Regulatory navigation, contractual risks.
- Technology/Data Science: Technical implementation, tooling, model development standards.
- Ethics/Responsible AI Office: Championing fairness, societal impact, ethical frameworks.
- Read More: https://www.natepatel.com/p/building-your-ai-governance-foundation
Visit Site: https://www.natepatel.com (https://www.natepatel.com/
p/building-your-
ai-governance-
foundation)
Account Phone Number