KLA vs OneTrust
OneTrust is a comprehensive enterprise platform for privacy, security, and AI governance. KLA Digital focuses on runtime AI governance with decision-time controls and verifiable evidence exports.
OneTrust is strong for enterprise-wide governance orchestration across privacy, security, and AI. KLA is built for runtime AI governance: decision-time controls, approval queues, and integrity-verified evidence exports.
For ML platform, compliance, risk, and product teams shipping agentic workflows into regulated environments.
Dernière mise à jour: 13 janv. 2026 · Version v1.0 · Pas d'avis juridique.
À qui s'adresse cette page
Un cadrage côté acheteur (pas un dunk).
For ML platform, compliance, risk, and product teams shipping agentic workflows into regulated environments.
À quoi sert réellement OneTrust
Fondé dans leur travail principal (et où il se chevauche).
OneTrust is a comprehensive enterprise platform for privacy, security, and governance, serving over 14,000 customers globally. Their AI Governance module extends this platform to address EU AI Act and responsible AI requirements.
Chevauchement
- Both address AI governance and EU AI Act compliance.
- Both support audit readiness: OneTrust through enterprise program orchestration, KLA through runtime decision evidence.
- Enterprise organizations often use both: OneTrust for governance orchestration, KLA for AI-specific runtime controls.
Les points forts de OneTrust
Reconnaître ce que l'outil fait bien, puis le séparer des produits livrables de la vérification.
- Enterprise-scale governance across privacy, security, AI, and ESG in one platform.
- Deep privacy expertise from years of GDPR and CCPA implementation.
- Risk assessment workflows with mature methodology.
- Extensive connectors to enterprise systems (ServiceNow, Salesforce, SAP).
- Global presence with multi-jurisdictional compliance support.
Lorsque les équipes réglementées ont encore besoin d'une couche séparée
- Runtime evidence capture from actual AI agent executions, not assessments.
- Decision-time policy enforcement that gates high-risk AI actions.
- Live approval queues integrated into AI agent execution paths.
- Independent verification of evidence integrity with cryptographic proofs.
Out-of-the-box vs build-it- yourself
Un juste partage entre ce qui expédie comme le workflow primaire et ce que vous assemblez à travers les systèmes.
Clé en main
- Enterprise-wide governance orchestration across privacy, security, and AI.
- AI system inventory and data mapping workflows.
- Algorithmic impact assessments and risk scoring.
- Policy management and workflow automation.
- Vendor risk management for AI suppliers.
Possible, mais vous le construisez
- Policy-as-code checkpoints that execute during AI agent decisions.
- Human approval workflows that pause AI execution until reviewed.
- Evidence capture tied to actual AI executions, not reconstructed later.
- Integrity-verified evidence packs that auditors can validate independently.
Exemple concret de workflow réglementé
Un scénario qui montre où chaque couche correspond.
Loan application denial
An AI system denies a loan application. Enterprise governance programs document policies, while runtime governance captures what actually happened at decision time.
Où OneTrust aide
- Document credit decisioning policies and conduct risk assessments.
- Track compliance status and inventory AI systems across the organization.
- Coordinate governance workflows across multiple business units.
Où KLA aide
- Capture the actual decision record with inputs, outputs, and policy checkpoint evaluation.
- Record human approval with timestamp and approver context if review was required.
- Export integrity-verified evidence pack proving this evidence has not been modified.
Décision rapide
Quand choisir (et quand acheter les deux).
Choisissez OneTrust lorsque
- You need enterprise-wide governance across privacy, security, and AI in one platform.
- You have mature privacy programs and want AI governance to integrate with existing workflows.
- Your organization is large and complex with multiple business units and jurisdictions.
- Risk assessments and inventories are your primary compliance activities.
Choisissez KLA lorsque
- You are deploying AI agents that make decisions requiring human oversight.
- Runtime evidence matters more than policy documentation alone.
- Auditors need proof of what actually happened, not just what should happen.
- High-risk classifications under Annex III require demonstrable controls.
Quand ne pas acheter KLA
- You only need enterprise governance orchestration without AI runtime controls.
- Risk assessments and policy documentation are sufficient for your compliance needs.
Si vous achetez les deux
- Use OneTrust for enterprise governance orchestration and privacy program management.
- Use KLA for AI-specific runtime governance and audit-grade evidence exports.
Ce que KLA ne fait pas
- KLA is not an enterprise-wide governance orchestration platform.
- KLA is not designed to manage privacy programs or vendor risk.
- KLA is not a replacement for multi-jurisdictional compliance dashboards.
La boucle de commande de KLA (Gouvern / Mesure / Prouve)
Qu'est-ce que « preuve de qualité d'audit » signifie dans les produits primitifs.
Gouverner
- Les points de contrôle qui bloquent ou exigent un examen des mesures à haut risque.
- Files d'attente d'approbation contextuelles par rôle
Mesure
- Examens d'échantillonnage selon le degré de risque (base + éclatement pendant les incidents ou après les changements).
- Suivi des quasi-incidents (étapes bloquées / presque bloquées) comme signal de contrôle mesurable.
Prouvez
- Piste d'audit infalsifiable, en append-only, avec horodatage externe et vérification de l'intégrité.
- Les paquets d'exportation Evidence Room (manifest + checksums) permettent aux vérificateurs de vérifier indépendamment.
Remarque : certains contrôles (SSO, examen workflows, fenêtres de rétention) dépendent du plan. Voir / prix.
Liste de contrôle de la DP (téléchargeable)
Un artefact d'achat partageable (contenu de référence).
# Liste de contrôle de la DP : KLA vs OneTrust Utilisez ceci pour évaluer si l'outillage « observabilité / passerelle / gouvernance » couvre réellement les produits livrables de la vérification pour l'agent réglementé workflows. ## Doit avoir (produits livrables de la vérification) - Cartographie des exportations de type Annex IV (champs de documentation technique -> preuves) - Dossiers de surveillance humaine (attentes d'approbation, escalade, interventions) - Plan de surveillance après la mise en marché + politique d'échantillonnage en fonction du risque - Histoire de vérification évidente (vérifications d'intégrité + rétention longue) Demandez OneTrust (et votre équipe) - Can you enforce decision-time controls (block/review/allow) for high-risk actions in production? - How do you distinguish “human annotation” from “human approval” for business actions? - Can you export a self-contained evidence bundle (manifest + checksums), not just raw logs/traces? - What is the retention posture (e.g., 7+ years) and how can an auditor verify integrity independently? - How do you capture evidence from AI agent executions specifically? - How do your approval workflows integrate with AI agent execution paths?
Sources & références
Références publiques utilisées pour garder cette page exacte et équitable.
Remarque : les capacités du produit changent. Si vous remarquez quelque chose de désuet, veuillez le signaler via /contact.