Not All AI Is Equal
Not All AI Is Equal
Not all AI systems carry the same level of risk—and treating them as if they do can leave organizations over-governing low-risk tools while under-governing the systems that matter most. Chapter 2: Not All AI Is Equal introduces a practical approach to classifying AI based on two critical dimensions: autonomy and data sensitivity.
You'll learn how to move beyond a simple inventory of AI tools and create a tiered risk view that shows where meaningful exposure is concentrated. The chapter explores four AI risk tiers, from embedded and invisible AI to predictive models, generative and conversational tools, and agentic systems capable of taking actions in production environments. It also explains how governance controls should change with each tier rather than applying the same process to every AI system.
The chapter then takes you from framework to execution—covering intake and classification methods, stakeholder involvement, vendor capability changes, automated discovery, review triggers, and a 30/90/365-day roadmap for building a continuously governed, board-reportable tiering program.
What You'll Experience in This Chapter
- Understand why AI risk needs to be differentiated rather than governed through one uniform process.
- Explore the four AI risk tiers based on autonomy and data sensitivity.
- Learn how to apply the right governance posture to each tier.
- Build a practical AI risk classification process using intake forms, self-attestation, contracts, and automated discovery.
- Identify capability changes and re-review triggers that can silently increase an AI system's risk.
- Establish governance for Tier 3–4 systems, including compensating controls and accountable ownership.
- Follow the 30/90/365-day roadmap from initial classification to an operational, board-reportable program.
- Avoid common failure modes such as one-time classification, excluding internally built AI, or making every tool feel like a high-risk review.
Tools & Templates
This chapter includes an AI Risk Tiering Scorecard, Vendor Capability-Change Questionnaire, Tier 3–4 Review Board Charter, Board Reporting one-pager, and sample SDLC ticket-field language for internally built AI systems.
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