Machine Learning Operations Offer Agility, Spur Innovation - AI Summary

This all contributes to the bottom line: a 2021 global study by McKinsey found that companies that successfully scale AI can add as much as 20 percent to their earnings before interest and taxes (EBIT). Over the last several years, Capital One has developed MLOps best practices that apply across industries: balancing user needs, adopting a common, cloud-based technology stack and foundational platforms, leveraging open-source tools, and ensuring the right level of accessibility and governance for both data and models. To build consistent processes and workflows while satisfying both groups, David recommends meeting with the application design team and subject matter experts across a breadth of use cases. Open-source ML tools (code and programs freely available for anyone to use and adapt) are core ingredients in creating a strong cloud foundation and unified tech stack. Using existing open-source tools means the business does not need to devote precious technical resources to reinventing the wheel, quickening the pace at which teams can build and deploy models.