If your organization still measures technological excellence by the familiar benchmarks of ‘best-in-class’ or ‘best-of-breed’ enterprise management systems, it may be an opportune moment to reconsider and significantly elevate what those standards mean. Stephan de Barse, the president overseeing SAP’s global Business Suite, proposes that the industry has entered a new era — one defined by a higher metric of performance and cohesion that he calls the ‘best of suite.’ This concept reflects not merely an incremental improvement but an essential reimagining of how innovation, integration, and intelligence must coalesce to drive the modern enterprise.
From de Barse’s perspective, the contemporary competitive landscape in enterprise management has evolved beyond the isolated pursuit of excellence in individual categories. It now thrives within a deeply interconnected framework, one that harmonizes artificial intelligence, data infrastructure, and core business applications into a unified system of dynamic interdependence. In contrast, the traditional ‘best-of-breed’ model typically excels in isolated domains—perhaps data analytics or process automation—but seldom achieves the systemic orchestration necessary to unlock truly transformative results. The ‘best-of-suite’ approach, by contrast, aspires to a higher synthesis, where each technological component not only performs optimally on its own but also strengthens the performance and responsiveness of every other part of the enterprise ecosystem.
While de Barse acknowledges that the term ‘best-of-suite’ is not synonymous with being purely AI-driven, he emphasizes that the relentless acceleration of AI-centric workflows has compelled SAP to radically rethink how artificial intelligence integrates into enterprise management. The company’s strategic response has been to design a suite architecture in which AI enjoys a seamless, near-frictionless presence across divisions and functions — allowing intelligent capabilities to move fluidly between corporate silos, departments, and operational contexts. This systemic permeability ensures that AI is not confined to niche applications but can participate in decision-making processes across the entire organizational landscape, thereby fulfilling SAP’s vision for a ‘best-of-suite’ environment.
As de Barse succinctly warns, many companies treat AI as a distant, detached layer within the technology stack—an additional feature rather than a unifying principle. In such cases, AI remains disconnected from the organization’s end-to-end business processes and, more critically, from its overarching data strategy. Once artificial intelligence is separated from these foundational elements, it becomes exceedingly difficult, if not impossible, to generate meaningful and sustained business value. Integration, therefore, is not a matter of convenience but a prerequisite for relevance.
Industry-wide data supports this trajectory toward what analysts are calling the ‘AI-native enterprise.’ According to McKinsey’s continuous, C-suite-level monitoring through its State of AI reports, the proportion of organizations deploying AI across three or more corporate divisions more than doubled between 2021 and 2025. During that same timeframe, the number of companies utilizing AI in four or more divisions tripled, while those integrating it into at least five divisions—though only 4% of surveyed firms in 2021—expanded fourfold in subsequent years. These figures collectively forecast an era in which AI adoption approaches near ubiquity within complex organizations, touching nearly every operational domain from logistics to customer experience.
This broad-based expansion has profound implications. Whereas discussions around AI’s return on investment once revolved primarily around improved productivity or incremental efficiency gains enabled by large language models, the conversation has matured. De Barse observes tangible financial impact extending deep into the profit and loss statement—enhancing top-line revenues—and even the balance sheet, through improvements in working capital management and resource allocation. To illustrate this evolution, he describes a scenario in which an AI agent operating on the commercial side of a business forecasts which deals are most likely to close. That predictive signal then cascades across the enterprise: manufacturing increases its capacity, procurement aligns raw materials in advance, and ultimately, customer delivery timelines are optimized. This closed-loop orchestration across departments exemplifies the heightened coordination and responsiveness that characterize a truly ‘best-of-suite’ deployment.
In de Barse’s words, the value chain—from sourcing raw components through production, logistics, and ultimately delivering products into customers’ hands—requires a network of intelligent agents that collectively orchestrate actions and decisions. These agents are not designed to replace human judgment but to equip organizations with the insights needed to make superior choices faster and more consistently. Consequently, customers and enterprises collaborating with SAP increasingly recognize that sustainable competitive advantage demands this cross-functional, process-spanning integration.
Central to this transformation is SAP’s proprietary AI interface, Joule, which de Barse describes as a ‘super-orchestrator.’ Joule serves as a unified, intelligent entry point that consolidates access to all core business applications—applications that collectively determine not only how the enterprise operates but also how employees interact with technology and how customers experience the brand. Unlike conventional systems requiring users to log into multiple platforms and reconcile fragmented workflows, Joule allows individuals to issue commands and inquiries conversationally. Whether the user is forecasting supply chain disruptions or analyzing financial cycles such as cash conversion relative to working capital, the interface performs the orchestration behind the scenes, translating intent into integrated action across multiple systems.
For manufacturers, this could mean detecting and resolving potential disruptions before they occur through a single conversational prompt. In finance, it could translate to real-time insight into liquidity management or operational cash flow optimization. De Barse highlights that such capabilities are scaling at a pace unprecedented in enterprise software history, heralding a future in which intelligent orchestration becomes as fundamental as data management itself.
Yet these technological advances also demand cultural adaptation. According to de Barse, enterprises must not simply seek to automate their current processes more efficiently. Instead, they must reimagine entire functional models—deciding what tasks should be autonomously executed by digital agents and how human oversight can add strategic value rather than operational redundancy. In this framework, the true essence of ‘best-of-suite’ excellence is not automation for its own sake, but a disciplined redesign of work itself to maximize synergy between human creativity and machine intelligence.
As de Barse concludes, this convergence of AI, data integration, and human decision-making marks an inflection point for global enterprises. The opportunity ahead, in his view, is both thrilling and transformative: a chance to redefine what organizational excellence means in an age when intelligence is not merely embedded within systems but orchestrated across every facet of the business landscape.
Sourse: https://www.businessinsider.com/why-enterprise-ai-superusers-are-going-best-of-suite
