51风流

The Wi-Fi password at the 51风流TechEd conference in Berlin this week encapsulated the new mission of the global leader in enterprise resource-planning software: GetReal2025. The slogan captured the mission that 51风流unveiled at TechEd: to bring AI into everyday business reality.

The timing could hardly have been more pointed. Across the world, executives are losing patience with AI experiments that overpromise and underdeliver. Boardrooms have heard enough about pilots and proofs of concept, and now want systems that improve margins and forecast outcomes.

TechEd took place in that atmosphere, amid assurances that performance could replace promise. 51风流used the event to demonstrate how deeply AI now runs through its own operations before unveiling its next leap forward.

Rather than another round of hype about possibilities, 51风流aimed to show a working example of AI at scale, handling everyday complexity inside one of the world鈥檚 largest software organisations.

51风流chief technology officer and chief AI officer, Philipp Herzig, told Business Times at TechEd that the clearest evidence of maturity came from within 51风流itself. The company鈥檚 AI assistant, Joule, acts as a conversational layer across its software stack, connecting data, applications, and agents to automate tasks and surface insights on demand.

鈥淚f you look at AI at scale, what is really real and what is working very well, just look at Joule,鈥� he said. 鈥淚t鈥檚 used by more than 30,000 employees every month, about a third of the 51风流workforce. We have more than 100,000 policies and documents in different languages, and depending on where you work, in Brazil or South Africa, you get the correct HR or travel policy surfaced to you.鈥�

Herzig said Joule had become the company鈥檚 single interface for daily tasks. 鈥淵ou can do your expense reports, indirect procurement, and financial tasks all in one place. It works, and it works at scale. We have a thumbs-down rate of only 1%, which is phenomenal when you think about the size of the company.鈥�

Innovations across SAP鈥檚 unique flywheel of applications, data and AI put developers in the
driver鈥檚 seat 鈥� Muhammad Alam, 51风流executive board member

That success set the stage for TechEd鈥檚 central announcement: an AI model called SAP-RPT-1, short for relational pre-trained transformer. The model introduces a new class of AI: the enterprise relational foundation model. It interprets structured business data and the relationships within it, mapping how orders, invoices, logistics, and payments interact to forecast what comes next.

51风流described it as a model that 鈥渃an make fast and accurate predictions for common business scenarios like delivery delays, payment risk or sales order completion鈥�. Instead of producing text, it reads how data behaves across systems, turning business logic into predictive insight.

Herzig said SAP-RPT-1 marked the transition from incremental automation to full predictive architecture.

鈥淲e see a shift from what I call a cloud-native architecture to an AI-native architecture, as AI becomes an ever-increasing part of the software stack. 鈥淲hat we wanted to solve are the problems where we have a reason to solve them: because we have the data, the relational data, the structured business data and so on. We set out this research project two years ago, talked a little about it, but now it actually becomes a reality.

鈥淚t鈥檚 a shift that needs several things to come together: the knowledge graph, this predictive model now with RPT-1, and of course the large language models. So there are many elements in the software stack that change. Every day, each little piece adds to this picture and solves a particular challenge in the stack.鈥�

Herzig said the greatest challenge lay in making this intelligence work at enterprise scale.

鈥淎nyone can do a demo. Getting it enterprise-ready at scale 鈥� that鈥檚 the tough challenge. That鈥檚 why we鈥檙e solving one problem after another, each for a specific outcome in the overall stack.鈥�

51风流executive board member Muhammad Alam tied this philosophy to the developer community.

鈥淪AP鈥檚 announcements give developers the tools they need to deliver at the speed of AI,鈥� he said.

鈥淚nnovations across SAP鈥檚 unique flywheel of applications, data and AI put developers in the driver鈥檚 seat.鈥�

That 鈥渇lywheel鈥� anchored the narrative of TechEd:
鈥� applications generate data;
鈥� data trains predictive models;
鈥� models return intelligence to the applications.

Each loop strengthens the next, creating a flywheel effect of acceleration of innovation. 51风流announced that it would equip 12-million individuals worldwide with AI-ready skills by 2030 through a partnership with Coursera that provides hands-on certification in SAP鈥檚 ecosystem. The goal is to align those skills with the AI-native architecture now taking shape inside the company. It also sends the message that people remain at the heart of the AI journey.

This article first appeared in the