MLOps – A Key Lever In Revolutionizing AI/ML Adoption For Industries

As the world slowly but surely emerges out of the Global Pandemic situation, the role of Artificial Intelligence and Machine Learning in driving digital business transformation has greatly increased. The impetus to move to the cloud and the growing number of ML models which saw phenomenal growth during the Pandemic, is expected to sustain over a period going forward. However, while operationalizing Artificial Intelligence, it has been found that merely 27% of the projects piloted by organizations successfully move to production. The anomaly between what AI/ML can achieve and what it is currently capable of, arises out of several challenges – most of them are related to model development, iteration, deployment and monitoring. These issues need to be addressed if AI/ML has to revolutionize the global business landscape. Organizations that have already started their journey to operationalize AI/ML or are developing Proofs of Concept (PoC) can pre-empt some of the challenges by proactively integrating best-practices in MLOps to ensure the smooth development of models and address issues of scalability. This compendium compiled by NASSCOM in association with Genpact and EY encapsulates the best practices to guide organizations on effective set up, management, and scaling of ML operations.