A recent McKinsey article discusses the challenges and requirements for scaling AI beyond occasional science experiments. The article talks to the importance of a comprehensive focus on the end-to-end ML lifecycle, instead of only focusing on model development or prototyping.

The article also calls for a standardized approach enabled by a common technology stack and coordinated teams to produce repeatable, scalable, and effective AI across the enterprise. Standardization and coordination would span across the entire ML lifecycle including data management and operations, model development, model deployment, and ongoing performance monitoring and management.

At C3 AI, we couldn’t agree more. Over the past decade, we developed and continuously improved the C3 AI Platform to be the comprehensive enterprise AI development and operating platform that McKinsey advocates for. In addition to our enterprise AI platform, we also delivered industry-specific enterprise AI applications – C3 AI Applications – that speed up time to value through pre-defined industry specific data models, readily available connectors to common enterprise systems, configurable analytics and ML pipelines, and rich workflows and user interfaces.

The purpose-built AI platform along with a centralized CEO-endorsed cross-functional team, as McKinsey articulates, sets the foundation for the AI factory to rapidly develop enterprise AI applications and maintain large scale AI deployments. At C3 AI, we work with the world’s largest organizations including Shell, Enel, Engie, Bank of America, Koch Industries, and many others to set up and enable such AI factories with our enterprise AI platform and pre-built enterprise AI applications. Today, C3 AI enables the world’s largest AI production footprint with 1.7 billion daily predictions and over 24 trillion data elements managed to improve the lives of 50 million businesses and consumers.

As the McKinsey article emphasizes, the bar for AI keeps increasing at a speed never seen before. Companies are competing to move beyond the uncoordinated AI experiments and ad-hoc applications. Industry leaders have already started to operationalize AI at scale across their organizations; for others, their capability to scale AI will be a defining competitive advantage over the next few decades.

About the author

Turker Coskun is a group manager of product marketing at C3 AI where he leads a team of product marketing managers to define, execute, and continuously improve commercial and go-to-market strategies for C3 AI Applications. Turker holds an MBA from Harvard Business School and a Bachelor of Science in electrical engineering from Bilkent University in Turkey. Prior to C3 AI, Turker was an Engagement Manager at McKinsey’s San Francisco office.