Artificial Intelligence (AI) refers to tasks performed by computer systems that typically require human intelligence. Quality management is the process of ensuring that products and services meet specified standards and customer expectations. In the field of AI, this means we need to ensure that the design and implementation of AI systems can meet predetermined performance standards and reliably complete assigned tasks. This online learning aims to help any participant interested in AI gain a preliminary understanding of a series of key issues in enterprise AI applications, laying the foundation for a more comprehensive understanding of the risks, responsibilities and challenges companies may face when adopting AI, and why companies need a comprehensive framework to ensure the effective and safe use of AI. In addition, this course uses simulation cases, interactive tests, etc. to introduce AI‑related regulations worldwide. By analysing these regulations, learners can understand the regulatory requirements for AI in different countries and regions and their potential impact on corporate strategy and operations. Finally, this course explores quality management methods for achieving AI compliance, including best practices and tools to help learners broaden their understanding of responsible AI use. These methods enable companies to ensure that the design and deployment of their AI systems comply with relevant ethical, legal and social standards, thereby protecting user rights and public interests while innovating.

• Identify the three pain points of AI: compliance, scalability, and responsible use
• Trigger internal activities to reduce legal risks and performance challenges of AI
• Learn where to start with a directional guide to AI quality
• Gain support to obtain internal commitment to launch AI quality projects
• Support personal development

• Anyone interested in the field of artificial intelligence.

• What is an AI system
• Why quality management is an integral part of AI
• Risks, responsibilities and challenges of using AI in enterprises
• Standards and regulations to consider
• How to ensure quality management and the quality of AI components