How Power Platform scales generative AI across an organization
Power Platform scales AI and the data platform by providing a composable means of both data collection and delivery of insights and AI capability back to the user. Meanwhile, the great, often unsung capability of Power Platform is not the “app”, rather the ability (via Dataverse) of data transacted in a Power Platform solution to hydrate downstream data distribution scenarios such as analytical workloads, enterprise search, and—you guessed it—whatever AI infused workload you dream up. Let’s explore this.
RAG and the fundamentals of AI acting on enterprise data
CIOs and enterprise architects need not be experts in the technical mechanics of AI to formulate and execute an effective AI strategy. That said, it is critical that leaders driving their AI strategy understand this basic concept of how institutional AI—that is to say, AI workloads specific to your organization—both requires and acts on enterprise data. This approach is what we call “Retrieval Augmented Generation” or “RAG”, which you may have heard of. The name is quite literal: Here we are augmenting the generative pre-trained (and now you know what “GPT” stands for) model with data that we have retrieved from the organization’s data estate.
White Paper: “Crafting Your Future-Ready Enterprise AI Strategy”
It is yet unknown if artificial intelligence is more akin to a “great inventions” of the 19th and 20th centuries, or if it will ultimately represent another more incremental evolution of existing capabilities. The former—as seems more likely given the immense investments being made today—will present significant challenges to nearly every organization that, having become accustomed to incremental change, is suddenly faced with a “great inventions” caliber paradigm shift that AI seems to portend. This white paper explores foundational concepts for AI technology and your AI strategy, five pillars for your AI strategy—data consolidation, data readiness, incremental AI, differential AI, scaling AI—and trends that are likely to shape AI in organizations going forward.