From the Factory Floor to the Data Layer: How Leading Companies Are Rewriting the Rules of Agility
The challenge business leaders face today is not any single disruption, it is the collision of all of them at once. Geopolitical volatility is redrawing supply chains faster than procurement cycles can adapt.
Regulatory frameworks are shifting across multiple jurisdictions simultaneously. Energy costs, labor markets, and customer expectations are each moving in their own direction, often in direct conflict.
The question I am most often asked, across industries and geographies, is a version of the same thing: how do we build an organization that can absorb continuous turbulence without losing operational coherence?
My answer is increasingly the same: you cannot manage permanent disruption reactively. You build systems that can anticipate, adapt, and act—autonomously, at scale, and in real time. That is what business AI, properly embedded into an organization’s digital core, now makes possible. And the clearest evidence I can offer comes from our customers, many of whom shared their incredible AI innovation journeys at our recent flagship SAP Sapphire events.
Data is the foundation, not an afterthought
Ericsson’s journey is instructive precisely because the company confronted a truth that many organizations are still resisting. As Esra Kocatürk Norell, vice president of Customer Experience and Enterprise IT at Ericsson, put it directly: “Once you scale AI, it stops being an AI problem and becomes a data problem.”
That insight drove a deliberate investment in a unified business data fabric built with SAP Business Data Cloud, a governed architecture that allows data to remain in place while centrally managing business semantics, governance, and lifecycle policies.
More than 85,000 users are now live on the unified AI platform Joule, with Ericsson moving confidently from experimentation to enterprise-wide execution. The company is advancing on two parallel fronts: modernizing its ERP backbone through RISE with SAP while simultaneously unlocking AI-driven value in decision-making, efficiency, and new business models.
What Ericsson demonstrates is that the path to trusted, repeatable AI runs through data governance, and that building that foundation early is a strategic advantage, not a cost.
From the digital core to the physical world
If Ericsson illustrates what AI transformation looks like at the level of data architecture, Martur Fompak International, a global leader in automotive seating and interior systems, shows what it looks like on the shop floor. The company has deployed an autonomous intralogistics model enabled by Joule and embodied AI capabilities from SAP, working with robotics partner Humanoid to integrate AI-powered robots directly into live manufacturing operations.
The system connects production signals and business context to autonomous physical execution. Guided by material data, storage locations, sequencing, and production priorities, humanoid robots now execute material flows across the manufacturing environment—identifying, transporting, and delivering materials to the line while continuously confirming back into SAP systems.
The logic is about “combining cognitive autonomy with physical automation,” Özlem Altınışık, Group Intelligent Technologies director at Martur Fompak International, described it, to “transform execution, accelerate decisions, and scale intelligent enterprise capabilities across the organization.”
Early results show increased throughput and fewer errors, with a future target of up to five times greater work efficiency set for mass production. Martur Fompak International was the sole winner in the AI Excellence category at the 2026 SAP Innovation Awards, recognition not just of the technology, but of the willingness to reimagine factory environments.
Speed, scale, and the intelligent platform
Prysmian, the global cable solutions leader with €20 billion in revenue and operations spanning more than 50 countries, took a different but equally decisive path. The company completed its evolution to an AI-ready cloud platform through RISE with SAP in just four months, then used that foundation to pursue more than 100 AI use cases across its business. The results are measurable: 70% automation of repetitive activities, an 80% reduction in implementation time for new solutions, and 50% acceleration in time-to-market for new products.
What strikes me about Prysmian’s journey is how it reframes the role of enterprise technology. Giovanni Cauteruccio, group CIO and digital officer at Prysmian, described embedded AI as “a key differentiator, enabling us to accelerate solution deployment and strengthen AI skills and culture across the organization.”
In other words, the platform is not simply a system of record, but a capability-building engine that makes the organization smarter over time.
Architecture of agility
Viewed together, these three stories point toward something larger than the sum of their parts. The Autonomous Enterprise is not a distant aspiration. It is being built now, by organizations that have made a deliberate commitment to embedding AI into their operational core as a fundamental design principle instead of a feature.
What makes this possible is the convergence of a governed data foundation, an intelligent ERP platform, and AI capabilities that extend from the desktop to the production line to the supply chain. When these elements are properly integrated, organizations gain something that no amount of reactive management can provide: the ability to sense, decide, and act faster than disruption can mount.
Uncertainty is not going away. The organizations that will navigate it best are the ones building systems today that turn volatility into signal and signal into advantage.
Manos Raptopoulos is global president of Customer Success Europe, APAC, Middle East & Africa and a member of the Extended Board of SAP SE.
