Aligning AI Governance, AI Development Lifecycle, and Systems Development Lifecycle Processes

The fusion of AI Governance, AI Development Life cycle (AIDLC), and System Development Life cycle (SDLC) processes share a common foundation of prioritizing responsible and ethical AI development. Both emphasize the need for clearly defined guidelines and principles that guide the entire lifecycle of AI systems. This includes establishing accountability structures, risk assessment procedures, and clear documentation practices. Both frameworks also stress the importance of data ethics, ensuring that the data used to train and operate AI models is collected and handled responsibly, focusing on fairness, privacy, and transparency.