SAP Solution: Leonardo

Christian Klein has not only made a mess of SAP's AI development, but is currently being overtaken left and right by his own existing customers when it comes to AI. An old pattern continues.

SAP is having a hard time with AI, as a recent interview with CEO Christian Klein in Handelsblatt shows. AI-assisted capture of incoming invoices is a standard process. ERP innovation should deliver more.

It's another case of deja vu. Instead of turning Leonardo into a digital platform of the future for Industry 4.0, SAP CEO Christian Klein is trying to lift his own existing customers into the cloud with his "Rise with SAP" idea.

For a long time, artificial intelligence was little more than attractive material for science fiction. In 1982, Harrison Ford hunted down replicants in "Blade Runner. In 2001, Steven Spielberg brought an emotional human-machine relationship to life in "A. I.".

SAP CEO Christian Klein sees extensive opportunities in the current challenges in global supply chains and logistics: "Indeed, SAP has excellent software offerings and business processes for global goods distribution and production.

SAP Manufacturing Execution (production control system) is gaining momentum and popularity.

Even though rumors on the market may say otherwise, artificial intelligence (AI) for concrete use cases works with SAP technologies. The principle "think big, start small, scale fast" can be implemented very well in the SAP world.

SAP wants to add quantum computing to the "Leonardo" toolkit. Intel is already one step ahead of the Walldorf-based ERP group.

Only money counts: On one side are the existing customers with their IT budgets, on the other the SAP sales department with its revenue targets. Opinions and views on the ERP market diverge between SAP and DSAG as they have not for a long time.

In the fifth IT season, when the numerous kick-off events thwart any meaningful work, I always have my thoughts about the next decade: What might an ERP/CRM system look like in ten years?

Viewed as a whole, it is a simple task - in detail, it becomes complex: Classic machine learning can only be successful with large amounts of data for learning and testing. And this data should be available quickly.

Digital transformation is about much more than just keeping up with a fast-paced world where customer expectations are becoming more demanding and complex, and hoping not to fall.