A quality engineering perspective on measuring AI adoption success using the DORA AI Capabilities Model. The approach advocates for small, iterative experiments with targeted metrics rather than chasing vanity metrics like code coverage or bug counts. The DORA AI Capabilities Model Report identifies seven key capabilities and provides guidance on prioritization, measurement, and common obstacles. The post also references DORA's ROI of AI-Assisted Software Development report to justify the upfront investment needed before teams cross the 'J-curve of AI value realization'.
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