governance and compliance

Outlines practical checklists for deploying AI from pilot to production. Covers goal alignment, data quality and labeling, model selection and evaluation, infrastructure and MLOps, privacy, security and compliance, bias and fairness reviews, human-in-the-loop, performance SLAs, cost/ROI tracking, monitoring and incident response, documentation, and change management to ensure safe, reliable, scalable AI.