Learn how to identify enterprise AI risks and direct mitigation by tracing where bias enters the AI lifecycle, weighing harmful content and intellectual property risks by impact and likelihood, and distinguishing reliability failures such as hallucinations, data quality degradation, and model drift, and matching controls and production monitoring to each risk type.
AI Business - AI Risks and Direct Mitigation Strategies
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AI Business - AI Risks and Direct Mitigation Strategies
This course is part of AWS AI Business Strategist Professional Certificate
Instructor: AWS Instructor
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Gain insight into a topic and learn the fundamentals.
2 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Apply risk controls and monitoring mechanisms to AI systems
Differentiate harmful content and intellectual property risks in AI systems, and choose mitigations based on impact and likelihood
Differentiate risks related to AI system reliability (hallucinations, data quality degradation, model drift) and appropriate mitigation strategies
Skills you'll gain
- Enterprise Risk Management (ERM)
- Digital Transformation
- Intellectual Property
- Business Strategy
- Artificial Intelligence
- Legal Risk
- Strategic Decision-Making
- Innovation
- Technology Strategies
- Risk Management
- Business Risk Management
- Risk Analysis
- Generative AI
- Operational Risk
- Data-Driven Decision-Making
- Risk Mitigation
- Risk Control
- Business Transformation
Tools you'll learn
Details to know
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Recently updated!
October 2026
Assessments
14 assignments
Taught in English
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This course is part of the AWS AI Business Strategist Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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- Gain a foundational understanding of a subject or tool
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There are 3 modules in this course
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