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    AI Risk: From Policy to Practice | NIST AI RMF & Governance

    20 min
    |
    |
    27 mai 2026
    AIBusinessTechnology

    Bridge the gap between AI principles and practice. Learn how to use the NIST AI RMF for provable governance and combat costly AI hallucinations in your enterprise.

    AI Risk: From Policy to Practice | NIST AI RMF & Governance

    Meilleure citation de AI Risk: From Policy to Practice | NIST AI RMF & Governance

    “

    If you’re responsible for AI at any level, you need to move from 'policy' to 'provable governance.' It’s about moving from 'we hope our engineers read the policy' to 'the system won't let the engineers violate the policy.'

    ”

    Cette leçon audio a été créée par un membre de la communauté BeFreed

    Question posée

    Artificial intelligence risk management

    Voix des présentateurs
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    Sources de connaissances
    NIST AI RMF Implementation Guide 2026 — GLACIS
    link
    https://www.glacis.io/guide-nist-ai-rmf
    EU AI Act Article 9 — Risk Management System: practitioner guide — EKM Global Consulting
    link
    https://ekmgc.de/insights/article-9-rms-practitioner-guide.html
    NIST AI RMF vs ISO 42001: 5 key differences (and how to use them together) | SecureSlate Blog
    link
    https://getsecureslate.com/blog/nist-ai-rmf-vs-iso-42001-5-key-differences
    Mapping AI Controls to NIST AI RMF and ISO 42001
    link
    https://data443.com/blog/mapping-ai-controls-to-nist-ai-rmf-and-iso-42001/
    The Four Shifts AI Governance Has Failed to Make
    link
    https://www.tejasviaddagada.com/article/the-four-shifts-ai-governance-has-failed-to-make

    Foire aux questions

    The principle-practice gap occurs when organizations establish high-level AI principles like fairness and transparency but fail to implement them within their software's code. As discussed in 'AI Risk: From Policy to Practice,' many companies struggle because their written policies do not actually control how their AI behaves in real-time. Closing this gap requires moving beyond aspirations toward the 'plumbing' of provable governance to ensure reliability.

    AI hallucinations have become a crisis of reliability for modern enterprises, leading to over $67 billion in global losses in 2024 alone. Data shows that 47% of enterprise users have admitted to making major business decisions based on these hallucinations. This makes AI risk management a matter of basic business survival rather than just an ethical concern, as organizations must ensure their systems provide accurate and dependable outputs.

    The NIST AI Risk Management Framework (AI RMF) provides a structured approach for organizations to move from theoretical policy to provable governance. By following this framework, businesses can better manage the risks associated with AI behavior and reliability. In 2026, the NIST AI RMF continues to evolve to help leaders bridge the gap between their stated AI principles and the actual technical implementation of their software.

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    Points clés

    1

    Beyond the Policy Document

    2

    The Architecture of Trust

    3:19
    3:48
    3

    Governing from the Top Down

    5:56
    4

    Mapping the Context of Risk

    7:59
    8:38
    5

    The Art of Measurement

    6

    Managing the Risk Lifecycle

    12:25
    13:23
    7

    Navigating the Regulatory Landscape

    8

    A Practical Playbook for AI Risk

    17:14
    18:04
    18:27
    9

    Reflecting on the Path Ahead

    19:59
    20:11

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