<ul><li>MLOps is the discipline of managing the lifecycle of machine learning models in production — from development to deployment, monitoring, and continuous improvement.</li><li>MLOps ensures that AI solutions are scalable, reliable, and maintainable, delivering consistent value in the real world.</li><li>Key components of MLOps include automated model monitoring and retraining, data validation pipelines, continuous integration and deployment (CI/CD) pipelines, model explainability and governance, and defined workflows and collaboration tools.</li><li>As an AI Product Manager, understanding the impact of MLOps is crucial for making strategic decisions and integrating them into AI strategy to ensure AI projects go beyond experimentation and deliver real business value.</li></ul>

MLOps Explained for Non-Engineers: What Every AI PM Should Know

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