SAP AI Core: What Mid-Sized Companies Need to Know Now

Artificial intelligence in SAP is no longer a thing of the future. While large corporations are already building dedicated AI teams and running initial production systems, many mid-sized companies are still at the beginning. The good news: getting started has never been easier than right now.

With AI Core, SAP has created a central platform that integrates machine learning and generative AI directly into the SAP landscape. In this article, we explain what SAP AI Core specifically delivers, which use cases are relevant for mid-sized companies, and why now is the right time to act.

What Is SAP AI Core?

SAP AI Core is the central AI infrastructure within the SAP Business Technology Platform (BTP). The platform provides a scalable runtime environment in which machine learning models can be trained, managed, and operated in production.

At its core, SAP AI Core offers three essential functions: First, the ability to train and deploy custom ML models in a managed Kubernetes environment. Second, access to pre-trained AI services via SAP AI Business Services. And third — since the integration of generative AI — access to Large Language Models (LLMs) via the Generative AI Hub.

Especially relevant for mid-sized companies: SAP AI Core does not require a dedicated data science team. Many use cases can be implemented with pre-configured services and low-code approaches. Integration into existing S/4HANA systems is done via standardized APIs.

Practical Use Cases for Mid-Sized Companies

The question our clients ask most frequently: "Where does AI in SAP deliver truly measurable value?" Here are four use cases that we have already successfully implemented for mid-sized companies:

1. Intelligent Document Processing

Incoming invoices, delivery notes, orders — the SAP Document Information Extraction Service automatically recognizes document types, extracts relevant fields, and creates posting suggestions. For one of our clients, manual processing time in accounts payable was reduced by 70%. The system continuously learns from clerk corrections and improves its recognition rate over time.

2. Predictive Maintenance

In manufacturing, machine data from IoT sensors can be analyzed with SAP AI Core to predict failures before they occur. Vibration patterns, temperature curves, and energy consumption are evaluated in real time. The results flow directly into maintenance planning in SAP PM — including automatic notification creation.

3. Log Analysis and Anomaly Detection

SAP systems generate millions of log entries daily. AI-powered anomaly detection identifies unusual patterns — such as sudden performance drops, atypical user activities, or data inconsistencies — long before a human administrator would notice them. This use case is particularly relevant for companies with limited basis resources.

4. Intelligent Purchase Recommendations

By analyzing historical order data, seasonal patterns, and external factors, SAP AI Core generates more precise purchase recommendations than traditional MRP runs. Especially for items with irregular consumption or strong seasonal fluctuations, ML-based demand planning significantly outperforms traditional methods.

Why Act Now?

Three reasons speak for engaging with SAP AI Core now — not in two years:

Competitive Advantage: Companies that integrate AI into their core processes early build an advantage that is hard to catch up on later. Data quality improves with every iteration, and employees develop AI competence that doesn't emerge overnight.

SAP Is Investing Heavily: SAP has declared AI a strategic priority. This means: integration is continuously becoming easier, new pre-built scenarios are added regularly, and the platform is maturing rapidly. Those who start now benefit from every further development.

Entry Barriers Are Dropping: Thanks to low-code tools, pre-configured services, and BTP integration, getting started is significantly easier than two years ago. An initial pilot project can go live within 4–6 weeks.

How Gineex Helps

Our AI Division combines two competencies that rarely come together: deep SAP know-how and solid AI expertise. Our specialized ABAP developers understand SAP architecture in depth, while our ML experts master the latest methods in machine learning and generative AI.

This combination is crucial, because AI in SAP rarely fails because of the AI itself. It fails because of integration — due to insufficient data quality, inadequate process connectivity, or a lack of understanding of SAP data structures.