During which phase of the AI system life cycle do you implement a data strategy?

The design phase is where a data strategy is implemented in the AI system life cycle because this phase is crucial for establishing how data will be gathered, analyzed, and utilized throughout the system's operation. In the design phase, considerations such as the types of data needed, data quality, sources of data, and legal and ethical implications of data usage are addressed. This strategy forms the foundation for the entire project, guiding not only data collection but also ensuring that the design choices align with governance, compliance, and performance objectives.

Establishing a robust data strategy during the design phase allows teams to anticipate challenges related to data availability, integrity, and security, which could impact subsequent phases, including implementation, testing, and evaluation. Therefore, the decisions made in this initial stage significantly influence the success of the overall AI system.