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AI Governance

Champion responsible AI adoption

Manage artificial intelligence systems and mitigate risk to demonstrate trust.

  • Maintain an inventory of machine learning and AI technology across your business 
  • Assess AI models for bias, fairness, and transparency against global laws and frameworks 
  • Evaluate use cases, surface risks, and govern every decision-making phase of AI development 

Graphic depicting widgets from the AI governance product module

Extend your data privacy, security, and governance programs into your use of AI

As AI adoption expands, businesses need to enact proactive AI governance to drive responsible use of data across the organization. Know where AI/ML is being used, built, or procured with an inventory of AI technology, MLOps integrations, and workflows for compliance and risk management.

Graphic depicting a table of AI projects and their stages

As business stakeholders begin to embrace generative AI, enterprises require an AI governance framework that breaks down data siloes and ensures smooth oversight. Scale AI governance with lightweight intake assessments and surface potential risk for AI systems throughout the AI lifecycle.

Graphic depicting inventory details for 2 separate models and the data related to them

Artificial intelligence introduces complex risks across your organization, from known risks across privacy, cybersecurity, and GRC to more nascent AI ethics risks such as model drift, fairness, and transparency. Assess AI against your business’ established responsible use policies as well as global regulatory requirements and frameworks to ensure effective oversight. 

Graphic depicting tables of AI risks and controls and data elements for each

June 04, 2024

Governing data for AI

In this webinar, we’ll look at the AI development lifecycle and key considerations for governing each phase.

Customer spotlight

We're looking to extend our work in AI governance on top of the existing privacy program components and structure and partnering with OneTrust to carry this out.
Head of Privacy by Design, Telecommunications Company

 Meet emerging AI regulation requirements and build trust


Gain a deeper understanding of AI systems, identify potential risks, and develop strategies to mitigate those risks in line with the NIST AI RMF. 


Assess AI systems using the OECD Framework for Classification of AI Systems checklist and address gaps under each of the principles.  


Evaluate projects for risk in accordance with the European AI Act risk categories, conduct conformity assessments, and demonstrate transparency. 

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