
When you are building an AI/ML product, it’s paramount that you define clear success metrics from the beginning.
These metrics will help guide the AI product development lifecycle and ensure that your team converges on the right product that solves business problems/user needs.
There are two ways to assess AI/ML product success:
1) Business outcomes
Business outcomes are the most important success metrics for AI products (and AI adoption in general). These are business objectives that result in tangible value created and captured by AI/ML products.
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