Methodology for selecting AI/ML tools
Selecting the right AI/ML tools for continuous testing, quality, security, and feedback involves a comprehensive methodology that ensures the chosen tools align with organizational goals, integrate seamlessly with existing systems, and effectively address specific challenges within these domains. When distinguishing between generative AI tools (which generate new data or content) and predictive AI tools (which predict outcomes based on input data), the selection process must account for unique considerations related to the functionality, application, and potential impact of these technologies.
Figure 8.10 shows a structured methodology for selecting AI/ML tools, highlighting differences in selecting generative versus predictive AI tools.
Figure 8.10 – Methodology for selecting AI/ML tools
Each of the steps is described in the following list:
- Define objectives and requirements:
- For both: Clearly outline...
