4 Steps to Successful Model Operations
Organizations are developing AI and ML models at an increasing rate to gain new insights, continue their digital transformation and reimagine their business. With multiple and often siloed teams developing AI models across the enterprise, a variety of tools and processes are more than likely employed.
Organizations have been using models to help with business decisions for decades. However, AI and machine learning models introduce new risks into model operationalization (post-development). Many model operations processes are manual or managed using home-grown solutions that constantly need to be updated as new technologies, tools and governance requirements are introduced. As a result, over half of the models developed do not get deployed, and those that are take months to operationalize, often leading to suboptimal outcomes and delayed or diminished value.
This ebook will walk you through the 4 steps that any organization can take to successfully operationalize AI/ML or any other type of model.