Technical stakeholders need to weigh the usefulness of GenAI tools against their limits and the information those tools may handle. This course explores safe-use practices, sensitive-data considerations, output review, and human oversight in technical workflows. An included microLab lets learners apply those considerations to realistic decisions; application-security risks in AI systems are addressed separately in the GenAI Application Security Series.

Participants in this course will learn the following:

• Understand the importance of safeguarding sensitive data. Protecting data is crucial when using GenAI tools.
• Learn to critically evaluate AI-generated outputs. Ensuring quality and security in outputs is essential.
• Implement secure coding and architectural practices. These practices help maintain system integrity.
• Adopt strategies for innovation without compromising security. Balancing creativity and safety is key.
• Apply safe-use patterns to minimize risks. Structured workflows enhance security.
• Ensure human oversight in critical decisions. Oversight maintains quality and security.
• Continuously improve GenAI practices. Adapting to evolving threats and policies is necessary.