Accelerating AI Maturity: A Framework for Reducing Development Lifecycles and Increasing Predictive Accuracy

The Model Manager framework is a means of giving structure to the end-to-end lifecycle of machine learning models to resolve the problems with the maturity of AI applications within companies and corporations. The evidence presented in this study shows that implementing this framework has led to a reduction in the average model development time by 30% and an increase in predictive accuracy of models by 23%. Not only does this framework serve to codify and automate the best practices for MLOps (such as advanced versioning and continuous model evaluation) through the integration of AI governance, but it will also help transition from the current fragmented way of working to a cohesive, scientific, and extensible process. When we decide to improve our activities in the Model Manager Framework, but as a sound business strategy that creates ethical, scalable, and high performing AI.