AI Governance Is Failing Because We’re Regulating Models Instead of Behavior

2026-05-14 · Source: HackerNoon · Field: Legal & Regulatory — Compliance & Risk Management, Regulatory Affairs & Government Relations · Depth: Advanced, short

Summary

Harsh Verma, an AI and cybersecurity innovator, argues that current AI governance frameworks are failing because they focus on regulating AI models themselves rather than the behavior and applications of these models. Published on May 14th, 2026, the article contends that regulating the underlying technology is ineffective due to its rapid evolution and diverse applications. Instead, Verma advocates for a shift towards a behavior-based regulatory approach, where the focus is on the outcomes and impacts of AI systems in specific contexts. This perspective suggests that effective governance requires understanding how AI is deployed and interacts with users and society, rather than attempting to control its internal mechanisms.

Key takeaway

For Policy Makers and Directors of AI/ML developing regulatory frameworks, your current approach of regulating AI models directly is likely to be ineffective and quickly outdated. You should pivot to a behavior-based governance strategy, focusing on the specific applications and societal impacts of AI systems. This shift will enable more adaptable and relevant oversight, ensuring that regulations remain pertinent as AI technology evolves.

Key insights

AI governance should regulate model behavior and applications, not the models themselves.

Principles

• Regulate AI outcomes, not internal mechanisms.
• Focus on AI's societal impact and deployment.

In practice

• Shift regulatory focus to AI application contexts.
• Develop frameworks for behavior-based AI oversight.

Topics

• AI Governance
• AI Regulation
• AI Ethics
• Responsible AI Development
• Behavior-Based AI Governance

Best for: Policy Maker, Legal Professional, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by HackerNoon.