Success Factor 03 Industrialize AI tools and teams to create an AI core Another priority for Achievers involves learning engineers, data scientists, data- building an AI core: an operational domain experts and systems engineers. data and AI platform that taps into companies’ talent, technology and data To build AI cores, Achievers harness ecosystems, allowing firms to balance the power of internal and external data, experimentation and execution. An AI making that data trustworthy and storing core helps organizations productize their it in a single enterprise-grade cloud AI applications and integrate AI into other platform—complete with appropriate applications, which makes differentiation usage, monitoring and security policies. with AI more seamless. To extract value from their data quickly An AI core also works across the cloud and effectively, Achievers are also continuum (e.g. from migration to 32% more likely, on average, than innovation), provides end-to-end data Experimenters to either develop custom- capabilities (foundation, management built machine learning applications or and governance), manages the machine work with a partner that offers solutions- learning lifecycle (workflow, model as-a-service. Achievers are also more likely training, model deployment) and than Innovators to use AI for innovation, provides self-service capabilities. AI tapping into readily available developer cores are, in turn, managed by dedicated networks that can swiftly productionize interdisciplinary teams of machine and scale successful pilots. The art of AI maturity—Advancing from practice to performance 23