Duration: 60 Minutes

Description

Introduces the complete lifecycle of an AI solution from concept through retirement.

Topics Covered

• Problem Identification
• Data Collection
• Data Preparation
• Model Development
• Model Testing
• Deployment
• Monitoring
• Maintenance
• Retirement
• Continuous Improvement

Learning Outcomes

Participants will:

• Describe the AI lifecycle.
• Identify governance checkpoints.
• Understand model monitoring.
• Recognise lifecycle risks.
• Define board oversight activities.

Executive Discussion

At which lifecycle stages should the Board become involved?

SkillSim Exercise

Identify governance gates throughout an AI project.