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watsonx.governance

Now available—govern generative AI models built on any platform and deployed on cloud or on-premises

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Govern AI models anywhere

IBM® watsonx.governance™ was built to help you direct, manage and monitor the artificial intelligence (AI) activities of your organization .

  • Govern generative AI (gen AI) and machine learning (ML) models from any vendor including IBM® watsonx.ai™, Amazon Sagemaker and Bedrock, Google Vertex and Microsoft Azure.
  • Evaluate and monitor for model health, accuracy, drift, bias and gen AI quality. 
  • Access powerful governance, risk and compliance capabilities featuring workflows with approvals, customizable dashboards, risk scorecards and reports.
  • Use factsheet capabilities to collect and document model metadata automatically across the AI model lifecycle.
IDC Spotlight: AI Governance: An Imperative for Harmonizing Innovation and Responsibility

IBM expands watsonx portfolio on AWS
Get the ebook: Build responsible AI workflows with AI governance
Preparing for the EU AI Act: How new AI regulations could impact your business
Benefits The value of building responsible AI Compliance capabilities 

Manage AI to address compliance policies, including the EU AI Act, worldwide—a nutrition label for AI.

 Read more Risk management

Detect and mitigate risks proactively. Monitor fairness, bias, drift and new LLM metrics.

 Read more Lifecycle governance

Manage, monitor and govern AI models from IBM, open-source communities and other model providers.

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Compliance capabilities 
Automate the identification of regulatory changes and translation into enforceable policies, including the upcoming AI regulations from the EU AI Act. Map regulatory requirements to internal risk data by using a single repository to manage regulatory content. Access factsheets—a nutrition label for AI—for an always up-to-date view of model lifecycle metadata in support of requests and audits. See capabilities in action
Risk management
Establish tolerances and alerts, proactively detecting accuracy, performance and new LLM metrics while also mitigating bias and drift. Access automated and scalable governance, risk and compliance tools that cover operational risk, policy management compliance and financial management. Use a single repository to maintain the results of risk assessments, key indicators, issue management and actions plans related to risk management. See capabilities in action
Lifecycle governance
Automate model monitoring, management and documentation across the AI lifecycle for increased scalability and accountability. Use model inventory to organize and track the AI development progress. Enhance stakeholder collaboration and communication by using dynamic user-based dashboards, charts and dimensional reporting. See capabilities in action
Use cases Watsonx.governance can be configured to meet the needs of your organization. Credit risk

Implement fair, transparent approval processes. Monitor with alerts to proactively detect risks and avoid inaccurate, unfair or biased decisions. Automate the capture and documentation of model metadata with factsheets in support credit decisions.  

 Customer care

Monitor chats for red flags regarding toxicity, personal information or off-topic conversations and alert when responses are outside of social norms. Support business process outsourcing activities across finance, human resources and procurement with dashboards and customizable workflows.

 Supply chain management

Promote transparency and accountability within supply chains. Proactively detect and mitigate any potential bias or errors in the system to optimize logistics, shorten cycles and reduce energy consumption.
Partner with us to deliver enhanced commercial solutions managed with watsonx.governance, to better address clients’ needs.
Client stories Businesses are excited about the prospect of driving responsible, ethical decisions across their organization with watsonx.governance. Explore more client stories EY

“The EY.ai Confidence Index methodology/solution enabled by watsonx.governance will strengthen EY clients’ ability to measure, manage and mitigate risks by helping to empower confidence in the data, models, processes, and technology making up their solutions through an empirical and quantitative assessment of the underlying AI solution/model.”


— Mario Schlener, Global FS Risk Technology Lead, Lead Risk Consulting Canada, Co-Lead Global Responsible AI, EY

 

 

 Tech Mahindra

“We understand our clients’ needs in bringing together and managing disparate tools, applications, and workflows, and we feel confident about IBM’s open approach and new watsonx.governance capabilities along with TechM amplifAI offerings will allow us to help them scale and realize the full potential of generative AI within their businesses.”

— Hasit Trivedi, CTO Digital Technologies and Global Head AI, Tech Mahindra

 

 NTT DATA Business Solutions

“We look forward to delivering on the promise of responsible AI by leveraging the watsonx.governance capabilities to support both regulatory requirements that have already emerged, as well as fundamental enterprise-wide requirements for an AI lifecycle control.”


— Per Falck Jensen, Vice President, Managing Director, Denmark Head of Sales Nordic Region, NTT DATA Business Solutions
Resources
IBM is named a leader in the IDC MarketScape: Worldwide AI Governance Platforms 2023 Why AI governance is a business imperative for scaling enterprise artificial intelligence Stay in control: The AI governance imperative with a guest speaker from IDC Successful AI needs governance, the ability to direct, manage and monitor the AI activities of your organization Find out how well prepared your organization is to scale AI responsibly by answering these short questions across the three main themes of strategy, technology and culture How IBM’s Chief Privacy Office is building on the company’s trustworthy AI framework and is scaling automation to address AI regulatory requirements A look into IBM’s AI ethics governance framework Best practices for augmenting human intelligence with AI Bring light to the black box: 3 reasons why organizations struggle with adopting AI 3 reasons why your organization needs responsible AI Read about a 3-step approach to build governance systems capable of monitoring ethical AI Discover 4 strategies for scaling AI responsibly IBM’s multidisciplinary approach is advancing responsible AI See how the IBM Office of Privacy and Responsible Technology automates global privacy and AI compliance tasks for ML models managed by IBM
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Get started with your governance strategy to direct, manage and monitor your organization’s AI activities.

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Footnotes

IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM’s sole discretion. See Pricing for more detail. Unless otherwise specified under Software pricing, all features, capabilities, and potential updates refer exclusively to SaaS. IBM makes no representation that SaaS and software features and capabilities will be the same.