SAP Fiori Elements offers a streamlined, metadata-driven approach for building enterprise-ready user interfaces. It significantly reduces frontend development effort while enforcing consistency and usability aligned with the SAP Fiori design guidelines. When integrated with SAP Machine Learning (ML) capabilities, Fiori Elements becomes even more powerful—enabling users to access intelligent insights and predictive features directly within their day-to-day business applications.
This article explores how to effectively use SAP Fiori Elements in combination with SAP Machine Learning to build intelligent, insight-driven enterprise applications.
SAP provides several machine learning services and frameworks through its Business Technology Platform (SAP BTP), including:
These services allow organizations to extract actionable insights from data using predictive, classification, or recommendation models. Integrating these insights into Fiori applications makes them more context-aware and decision-supportive.
The typical pattern is to expose machine learning results through OData services that are consumed by the Fiori Elements application. These can be:
The ML model may be trained and deployed in SAP AI Core or HANA, and invoked from the ABAP backend or CAP-based service.
Using annotations like @UI.lineItem and @UI.identification, you can bind predicted values to the UI:
@UI.lineItem: [{ position: 10, label: 'Predicted Delivery Date' }]
PredictedDeliveryDate
Or visually highlight confidence levels or risk using @UI.DataPoint with criticality:
@UI.dataPoint: {
value: 'RiskScore',
criticality: 'RiskLevel'
}
Users can trigger ML inference from within the app via custom actions (e.g., "Run Prediction"). This can be done using:
A Fiori Elements list report displays sales orders. An ML model predicts the likelihood of order fulfillment delays, which is shown using a risk indicator on the object page.
Using SAP AI Business Services, invoice documents are automatically classified. A Fiori Elements app shows the classification result and confidence score, allowing the user to review or override.
A procurement app suggests alternative vendors based on historical performance and pricing using a recommendation model, embedded via backend annotations.
Integrating SAP Fiori Elements with SAP Machine Learning brings the power of artificial intelligence into daily business workflows—without requiring heavy frontend development. By exposing ML predictions through OData services and binding them with annotations, developers can build scalable, intelligent, and user-friendly applications that drive smarter decisions. As enterprises move toward intelligent ERP, this synergy between Fiori Elements and machine learning is essential to delivering the next generation of SAP applications.