Critical to any project in ML, we need to set expectations about accuracy, precision, recall, F-score, etc. Let’s assume the client wants “good” results rather than a quantitative benchmark. That makes the project easier to price out, as there are fewer iterations. In general, the quality of the AI grows with the size of the dataset.