Executive Guide: AI Risk Management and Value Delivery Integrating Global Frameworks, Lean Flow, and Systems Thinking

Executive Summary

Artificial Intelligence (AI) is transforming how organizations operate, offering unprecedented opportunities for automation, insight, and value creation. Yet with this innovation comes a broad spectrum of risks—from ethical dilemmas to compliance failures, operational disruptions, and model bias. To address these concerns, organizations need structured, flexible, and adaptive frameworks for AI risk management.

This guide unites the most effective tools and philosophies:

• IBM’s AI Ladder for data maturity and trust;
• PMI’s CPMAI methodology for AI project governance;
• NIST’s AI Risk Management Framework (AI RMF);
• The Amplio University approach by Al Shalloway, grounded in Lean, Systems Thinking, and Value Stream Management;
• Global standards such as the EU AI Act and ISO/IEC governance practices.

By weaving these frameworks together with Lean Flow principles like the Quickest Valuable Release (QVR), Theory of Constraints (TOC), and GILB Planguage metrics, this guide provides a practical, globally informed roadmap to manage risk while enhancing organizational agility and value delivery.