Why enterprise AI superusers are going best-of-suite

If you’re still looking for best-in-class or best-of-breed when it comes to your enterprise management systems, it might be time to raise your expectations.

According to Stephan de Barse, president of the global Business Suite for SAP, a new gold standard has emerged — a superlative he calls “best of suite.”

In de Barse’s view, the competitive arena for enterprise management now exists within an integrated framework of AI, data, and core applications. That elevates it from a narrower proving ground, where being a “best of breed” provider checks only one or two of those boxes.

And while being “best of suite” isn’t all about AI, the rapid acceleration of AI-centered workflows meant that SAP needed to think differently about the role of AI in enterprise management. This outcome — a clear path and proximity for AI to easily navigate between divisions and functions — is one of the ways the SAP Business Suite lives up to the new designation.

“Many companies treat AI like a separate layer somewhere in the technology stack,” said de Barse. “That way, it’s disconnected from your end-to-end business processes and disconnected from your data strategy. The moment AI doesn’t make it back to the end-to-end business-process context it’s very, very difficult to drive value.”

AI with suite-wide sweep

According to McKinsey’s on-going tracking of enterprise AI from the C-Suite perspective — captured in regular releases of its State of AI reports — the percentage of organizations that report using AI in three or more divisions more than doubled between 2021 and 2025. Use of AI in four or more company divisions tripled across that time period. Companies using AI across five or more divisions — while starting smaller at 4% of those surveyed in 2021 — posted quadruple growth, forecasting near enterprise-wide ubiquity for AI use.

This trajectory toward AI native enterprises is significant. Where the AI ROI conversation was once centered around generalized productivity powered by LLMs, de Barse has watched it reach hard improvements in both the P&L (e.g. improvement of topline revenue) and the Balance Sheet (e.g. improvement of working capital).

He cited the example of an AI agent on the commercial side of an enterprise forecasting deals likely to close. This would send a signal to manufacturing to increase capacity and procurement to line up raw materials.

“If you think about the entire value chain, from sourcing components to getting a product in the hands of customers, that has to be orchestrated by a series of agents that can help organizations reach better decisions and improve business results,” de Barse said. “Customers want to work with us to get there, because they understand this must be across business processes.”

Best in suite meets best in orchestration

SAP’s own proprietary AI interface is known as Joule, which de Barse described as a “superorchestrator” — a single, accessible entry point to all business applications that, in aggregate, determine how an enterprise runs and employees work, as well as the customer experience.

With Joule, “you ask questions, but you also give instructions,” de Barse said. “You don’t have to log into five different applications to do something — it’s all being orchestrated by Joule. So the way we think about interacting with software becomes different.”

For manufacturers, that can mean an easy conversational prompt to forecast potential supply-chain disruptions and arrive at a solve. In the finance context, it means instant insight into the cash conversion cycle relative to working capital.

“At the enterprise level, this is happening at an unprecedented pace,” he said.

In de Barse’s view, these capabilities also call for cultural shifts within organizations — leaning away from optimizing current processes to rethinking how entire functions should be done, so that what becomes automated and tasked to agents is operating in “best-of-suite” condition.

“It’s pretty exciting. This,” he said, “is the opportunity.”