Responsible AI with Azure
Develop, use, and govern AI solutions responsibly with Azure AI.
Confidently scale the next generation of safe, responsible AI applications
Azure AI empowers organizations to scale AI with confidence and turn responsible AI into a competitive advantage.
Microsoft experts in AI research, policy, and engineering collaborate to develop practical tools and methodologies that support AI security, privacy, safety and quality and embed them directly into the Azure AI platform. With built-in tools and configurable controls for AI governance, you can shift from reactive risk management to a more agile, responsible-by-design approach that accelerates innovation.
Innovate with confidence
Confidently scale AI across your organization with industry-leading technologies and best practices that help manage risk, improve accuracy, protect privacy, reinforce transparency, and simplify compliance.
Reinforce responsible AI in production
Use counterfactuals to understand what’s needed to produce a specific outcome and causal analysis to proactively apply new policies and effect real-world change. Then, track and optimize model performance in production with model monitoring. Simplify inference data collection and get timely alerts on data drift, feature attribute drift, and data quality issues to continually improve model performance and business outcomes.
Govern for transparency and accountability
Protect and govern your machine learning assets with enterprise privacy and security controls, 60+ compliance certifications, and machine learning operations (MLOps). Easily track and understand data lineage and use the connector for Microsoft Purview to streamline metadata storage and perform faster root cause analyses. Export responsible AI scorecards (preview) for your machine learning models to contextualize responsible AI metrics for business stakeholders and foster proactive collaboration.
Build responsibly for trusted outcomes
Operationalize responsible AI to deliver trusted outcomes. Assess models for fairness, reliability, and explainability
Make real-time, data-driven decisions with confidence. Monitor and optimize AI model performance in production
Protect and govern your machine learning assets for transparency, accountability, and compliance across stakeholder groups
Related products
Azure Machine Learning
Use an enterprise-grade service for the end-to-end machine learning lifecycle.
Driving Business Value with Responsible AI webinar
Watch on demand: Driving Business Value with Responsible AI.
Resources and documentation
Tools
- Understand your models
- Improve the fairness of your models
- Assess the errors of your models
- Improve decision making
- Generate responsible AI scorecards
- Create a responsible AI dashboard
- Continuous model monitoring
- How to evaluate foundation models using your own test data
- Discovery, lineage tracking, and AI governance with Microsoft Purview
- Responsible AI Accelerator for Healthcare
- Responsible AI Accelerator for Financial Services
Build your machine learning skills with Azure
Learn more about machine learning on Azure and participate in hands-on tutorials with a 30-day learning journey. By the end, you'll be prepared to take the Azure Data Scientist Associate Certification.
Customers are putting responsible AI into practice
"With Azure Machine Learning and the Responsible AI dashboard, we have the tools we need to understand, refine, and explain our outcomes so we can better serve our patients."
Dr. Justin Green, Leadership and Management Fellow at Health Education England North & Orthopedic Surgical Registrar
"With model interpretability in Azure Machine Learning, we have a high degree of confidence that our machine learning model is generating meaningful and fair results."
Daniel Engberg, Head of Data Analytics and AI, Scandinavian Airlines (SAS)
