Three Takeaways From Our Survey Of Top ML Teams

Arize AI's recent survey of 945 data scientists, ML engineers, technical executives, and others highlights key challenges faced by MLOps teams. Troubleshooting model issues remains a significant problem for many, with 84.3% of respondents reporting delays in detecting and diagnosing problems at least some of the time. Additionally, communication between ML teams and business executives is often hindered, with over half of data scientists and ML engineers encountering issues with quantifying ROI or explaining machine learning concepts to stakeholders. While explainability remains important, it should not be relied upon solely; instead, a proactive approach to model performance management is recommended.