SAS
Assembly Line
Industrial-grade AI: Transforming Data into Insights and Outcomes
Data fabrics can simplify the AI and Analytics lifecycle for enterprises by weaving together a unified layer for data management and integration across some of the endpoints within an industrial environment. However, existing enterprise data fabrics may not be “industrial grade” enough for many Industrial AI use cases. They often require a “big bang” approach of migrating and standardizing data in cloud-based data lakes and may not handle the complex data types encountered on the industrial edge—data that is often unstructured, time-sensitive, and critical for real-time decision making in industrial AI use cases.
Breakthroughs in Gen AI have expanded the Industrial AI toolset - especially for use cases that address the sector’s skills gaps by enhancing knowledge retention and transfer and augmenting the workforce with “Assistants” and “Copilots” - and promise to have a sweeping impact on the way users across every industry interact with complex technology. Although perceived itself as an expensive AI solution, the wave of investments triggered by Gen AI is driving innovation and lowering costs across the broader AI landscape, offering new opportunities for scale deployment of tried and tested AI modeling techniques trained on each organization’s own industrial datasets.