AI Governance & Risk

Responsible AI frameworks

Principles, policies, roles and review processes that fit how your organization builds and buys AI.

Vue d’ensemble

Many organizations have published AI principles, but far fewer have turned them into decisions people can act on. A responsible AI framework connects high-level commitments, such as fairness, transparency, accountability and safety, to the specific policies, roles and review steps that apply when a team wants to build or buy an AI system.

We design frameworks that fit your organization's size, risk appetite and existing governance. That includes an AI policy and acceptable use standards, a risk-tiering method, defined roles for business owners, technical owners and oversight functions, and a review process proportionate to risk.

We align the framework with recognized standards such as the NIST AI Risk Management Framework and ISO/IEC 42001, and connect it to your existing risk, privacy, security and procurement processes rather than creating a parallel bureaucracy. The result is a framework your teams understand and can follow, with clear routes for approving new use cases quickly.

Ce que vous obtenez

  1. 01Responsible AI principles and AI policy
  2. 02Acceptable use standards for employees, including generative AI tools
  3. 03Risk-tiering methodology and use-case intake process
  4. 04Roles, responsibilities and decision rights, including an AI oversight forum
  5. 05Review and approval workflow integrated with existing processes

Technologies que nous maîtrisons

  • NIST AI Risk Management Framework
  • ISO/IEC 42001
  • OECD AI Principles
  • ServiceNow
  • OneTrust
  • Microsoft Purview

Nous sommes indépendants des éditeurs : les outils sont choisis en fonction de vos besoins et de vos investissements existants.

Les questions que l’on nous pose souvent

We are a small organization. Do we need a full framework?

You need a proportionate one. Smaller organizations can start with a clear acceptable use policy, a simple intake and risk-tiering step and named owners, then add depth as AI use grows.

How does this fit with our existing risk management?

We build on your existing risk, privacy, security and procurement processes wherever possible. AI-specific steps are added only where existing controls do not cover AI risks, rather than creating a separate system.

Analyses

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