Jellyfish’s AI Impact Framework provides a model to measure AI adoption, productivity, and business outcomes. While 90% of teams now use AI coding tools, only about 30% see significant benefits, showing that adoption alone is insufficient. The framework highlights three pillars: driving adoption by unblocking non-users and increasing power users, boosting productivity by reducing cycle times and increasing PR throughput, and achieving outcomes like higher growth allocation and fewer bugs. Data shows senior engineers initially benefited more, but juniors are catching up. Success requires clear metrics, segmentation, and regular reviews with stakeholders.

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