IBM watsonx.governance (original) (raw)
Accelerate ROI with smarter AI governance, risk and compliance
See AI. Control AI. Realize AI value.
As AI systems expand across organizations, they need visibility, accountability and continuous oversight to manage risk and scale AI effectively. IBM watsonx.governance delivers an enterprise AI assurance layer - combining AI-native governance with enterprise-grade Governance, Risk and Compliance (GRC) across hybrid, multi-vendor environments.
- Connect AI assets, risks, and policies across operational, third-party, business continuity, and IT risks, not just AI-specific ones
- Translate policies into controls, enforce them through AI control planes, and maintain continuous audit-ready reporting
- Tap into one of the largest networks of AI-related compliance content, with dramatically reduced compliance cost and friction without lock-in.
Recognized by leading analysts in AI governance, risk, and compliance
Features
Power up with enterprise AI assurance at scale
Governance Graph — the foundation to assess exposure
Understanding enterprise context goes beyond a static inventory. The Governance Graph gives you a living, connected map of your entire AI estate, capturing rich relationships from AI assets through policies, enterprise AI risks, and regulatory requirements. You can trace what AI in use, for what purpose, under what controls, and whether those controls are working, across platforms, and production environments.
Control — from informed exposure to enforceable governance
Most governance approaches treat AI risk in isolation from enterprise operations. watsonx.governance takes a different approach, integrating AI risk with IT, operational, third-party, and business continuity risk, with AI-driven automations for control mapping and compliance applicability, so governance keeps your teams moving rather than slowing them down.
Closing the loop between intent and reality
Once controls are defined, they need to be enforced and measured. Breaches, risk signals, and corrective actions flow back continuously closing the loop between governance intent and operational reality. Every AI use case is tied to business objectives and tracked against real KPIs, so you always know what's working, what isn't, and where to invest next.
AI governance in action
Use cases
Put AI Governance to work
Regardless of where you intend to employ AI in your business, watsonx.governance supports multiple high-impact use cases across industries and functions.
Track and validate AI business value
Align AI use cases directly to strategic objectives and define business KPIs to track performance. Monitor outcome progression through dashboards and workflows-ensuring AI systems are accountable for delivering the value they were designed to achieve.
Strengthen third-party and ecosystem AI risk oversight
Leverage integrated partnerships with providers like D&B, RiskRecon, Security Scorecard and Rapid Ratings to assess third-party risk and incident exposure. Gain deeper visibility into vendor dependencies and risk posture.
Automate compliance and audit processes
Leverage one of the industry’s largest regulatory ecosystems (200+ frameworks) through integrated compliance data partners. Map obligations directly to AI systems and automate applicability, evidence collection and audit-ready reporting processes. This helps to reduce the cost, friction and latency of compliance processes.
Case studies
From governance to value. Real results.
Infosys
Infosys leveraged watsonx.governance to achieve a 150% increase in operational efficiency, accelerating AI project velocity without compromising oversight with over 2,700 AI use cases across functions and geographies.
150%
increase in operational efficiency
Pricing
Pricing tiers
Explore IBM watsonx.governance purchasing options to manage, monitor and scale responsible, transparent AI across cloud and on‑prem environments.