Introduction
In the world of enterprise technology, the buzz around artificial intelligence has long outpaced the tangible results that businesses actually see. When Alexander Rinke, co‑founder and co‑CEO of Celonis, opened the stage at Celosphere 2025 in Munich, he did so with a stark statistic: only eleven percent of companies report measurable benefits from their AI initiatives. That figure, he argued, is not a symptom of poor adoption but a sign that the context in which AI is deployed is fundamentally wrong. The premise is simple yet profound—AI can only be effective when it is anchored to the real, messy processes that drive a company’s day‑to‑day operations. Celosphere 2025 was not a showcase of flashy new algorithms; it was a deep dive into how a living, data‑rich model of an enterprise can become the connective tissue that turns isolated experiments into scalable, outcome‑driven AI.
Main Content
Process Intelligence as the Backbone
At the heart of Celonis’ approach is what Rinke calls a “living digital twin” of an organization’s operations. The foundation of this twin is the Data Core, a data infrastructure that pulls raw data from every source system—ERP, CRM, supply‑chain platforms, even spreadsheets and browser activity—into a unified repository that can be queried in near real time. By freeing processes from the constraints of legacy systems, the Data Core provides the breadth of visibility that traditional systems of record simply cannot match.
On top of this foundation sits the Process Intelligence Graph, a system‑agnostic, graph‑based model that stitches together data across applications, devices, and business rules. Every transaction, every exception, every KPI becomes a node or edge in a continuously updated replica of how the organization actually operates. This graph is not a static map; it evolves as new data streams in, ensuring that the model reflects the current state of the business rather than a snapshot from a few months ago.
The Build Experience built on top of the graph empowers users to analyze where processes stall, design future states with clear outcomes and guardrails, and then operate those states with humans, systems, and AI agents working in harmony. The orchestration engine, now generally available, can trigger and monitor every step in a flow, turning a series of disjointed tasks into a single, observable process that can be optimized end‑to‑end.
Real‑World Impact
Celosphere 2025 was not just a theoretical exposition; it was a showcase of real‑world success stories. Mercedes‑Benz, for instance, leveraged the platform to weave together data from plants, suppliers, and logistics during the semiconductor crisis. The result was a rapid, data‑driven response that cut through the chaos of fragmented information. The partnership has since expanded to cover eight of the company’s ten most critical processes, illustrating how process intelligence can become the connective tissue that unites disparate parts of a global organization.
Vinmar, a global plastics distributor, used Celonis to automate its entire order‑to‑cash cycle for a $3 billion unit, achieving a 40 percent lift in productivity. The company is now tackling the non‑algorithmic aspects of order matching, building an AI agent that can intelligently allocate purchase and sales orders across thousands of edge cases. Uniper, in collaboration with Microsoft, demonstrated how process‑aware AI copilots can predict maintenance needs for hydropower plants, clustering jobs to reduce downtime and emissions.
These stories underscore a key point: measurable ROI is not a function of deploying a new AI model, but of embedding that model within a living process context that can be observed, measured, and iterated upon.
Composable Enterprise AI
Beyond the individual use cases, Celosphere 2025 highlighted a broader shift toward composable AI—an architecture that allows AI solutions to be assembled across multiple ecosystems rather than locked into a single vendor. Rinke emphasized the importance of open ecosystems, citing integrations with Microsoft Fabric, Databricks, and Bloomfilter that enable zero‑copy, bidirectional lakehouse access. Customers can now query process data in place with minimal latency, creating a seamless flow between data lakes, analytics, and AI services.
The announcement of MCP Server support for embedding the Process Intelligence Graph directly into agentic AI platforms such as Amazon Bedrock and Microsoft Copilot Studio further illustrates this composability. Instead of competing on who has the best proprietary agent, the focus shifts to how well agents can collaborate through shared context and models that mirror real business operations.
Context Beyond Technology
The closing moments of the keynote took a philosophical turn. Venezuelan opposition leader María Corina Machado joined via satellite to discuss how her movement used data, encrypted communication, and civic coordination to expose election fraud. Her remarks—“Technology can be a weapon or a liberator; it depends on who holds the context”—resonated with the audience. The same principles of transparency, accountability, and context that underpin process intelligence in business are equally vital in democratic societies. Context is not merely a technical construct; it is a human one, rooted in culture, governance, and shared purpose.
Conclusion
Celosphere 2025 marked a watershed moment for enterprise AI. The event shifted the narrative from experimentation to execution, from isolated pilots to outcome‑driven operations grounded in process intelligence. By building a living digital twin, providing a unified graph of operations, and enabling composable AI across ecosystems, Celonis has laid the groundwork for enterprises that can adapt instantly, innovate freely, and improve continuously. The real triumph lies not in the technology itself but in the cultural shift that accompanies it—teams that can see their processes in context, leaders who understand the value of data-driven decisions, and organizations that treat AI as a tool for transformation rather than a novelty.
Call to Action
If you’re ready to move beyond AI pilots and unlock measurable ROI, start by mapping your core processes with a data‑centric approach. Explore how a living digital twin can reveal hidden bottlenecks, and consider integrating AI agents that operate within that context. Whether you’re in manufacturing, supply chain, or any other domain, the principles of process intelligence and composable AI are universally applicable. Reach out to your technology partners, evaluate platforms that offer real‑time data integration and graph‑based modeling, and begin the journey toward an enterprise that learns, adapts, and thrives in a data‑driven world.