Strategy and Vision created the aspirational, architectural, and programmatic framework for our AI strategy; Ecosystem Architecture built the infrastructure, data, and application foundations. No doubt you have noticed that we’ve not yet discussed any specific AI-driven workloads. Take this as a lesson concerning the foundational nature of data and your data platform to any big dreams you have about artificial intelligence, for the success of any AI workload is absolutely and critically dependent on your success with strategy, vision, and – particularly - ecosystem architecture discussed above.

Our Workloads pillar gets to what’s on the mind of most folks when they think about artificial intelligence: How will we use AI to solve real-world challenges?

“Workload” is not a throwaway word. It is rather a specific term that we use precisely because I value its imprecision. App-centric people speak in terms of apps, integration-centric people speak in terms of integrations, etc. Workloads cover it all. They are, simply put, a collection of one or more apps, chatbots, visualizations, integrations, data models, etc. working towards the same end. “Workload” is essentially the combination of the front-end and back-end required to produce an AI-driven response or action.