Celonis: Process Intelligence is Essential for Enterprise AI ROI

7 hours ago7 min read

The accelerating adoption of artificial intelligence across the corporate landscape is creating a paradoxical chasm between technological ambition and tangible financial return, a challenge that Alex Rinke, co-founder and co-CEO of the process intelligence firm Celonis, identifies as a fundamental problem of context. Enterprise leaders are under immense pressure to demonstrate measurable ROI from their AI investments, a pressure intensified by the rise of autonomous agents and volatile global supply chains disrupted by new tariffs.The core issue, Rinke argues, is not the sophistication of the AI models themselves, but their frequent lack of grounding in the intricate, real-world workflows of a business. Without this deep, process-level understanding, AI initiatives risk degenerating into what he pointedly calls 'just an internal social experiment,' a costly endeavor that fails to impact the bottom line.This central thesis will be unpacked at the upcoming Celosphere 2025 event, a three-day gathering dedicated to bridging this very gap by showcasing how Celonis’s Process Intelligence Platform serves as the essential substrate for what they term 'enterprise AI,' enabling continuous operational improvement and scalable value creation. The urgency of this mission is underscored by a recent Gartner survey revealing a stark disconnect: while 64% of board members rank AI as a top-three priority, a mere 10% of organizations report meaningful financial returns, highlighting a widespread failure to transition from pilot projects to production-grade systems that generate profit.This trend, however, is not universal. A Forrester Total Economic Impact study commissioned for Celonis presents a compelling counter-narrative, finding that organizations leveraging its platform achieved a staggering 383% ROI over three years, with payback occurring in just six months.The study details one company’s journey to improving sales order automation from 33% to 86%, saving $24. 5 million, and estimates total benefits of $44.1 million over three years derived from accelerated automation, reduced process inefficiencies, and enhanced operational visibility. These figures point to a broader pattern: companies that successfully modernize legacy systems and deliberately align AI deployment with core process optimization are the ones seeing rapid payback and sustained competitive advantages.The event will spotlight real-world implementations from global enterprises building what Celonis terms 'future-fit' operations. For instance, pharmaceutical giant AstraZeneca utilized the Celonis platform as the foundational layer for its partnership with OpenAI, successfully reducing excess inventory while ensuring the uninterrupted flow of critical medicines—a delicate balance in a high-stakes industry.Similarly, the State of Oklahoma deployed the technology to answer procurement status questions at an unprecedented scale, unlocking over $10 million in value from its bureaucratic processes, while Cosentino now clears blocked sales orders up to five times faster using an AI-powered credit management assistant built on the platform. A significant portion of the conference’s discourse will inevitably focus on the next frontier: agentic AI.Rinke emphasizes that the paradigm shift from AI-as-advisor to AI-as-actor fundamentally changes the risk calculus. When an AI agent can autonomously trigger a purchase order, reroute a multimillion-dollar shipment, or approve a financial exception, the consequences of faulty or incomplete business context are no longer mere recommendations but can escalate into catastrophic outcomes executed at machine speed.The Celonis Orchestration Engine is being positioned as a crucial control mechanism, designed to coordinate these autonomous agents alongside human workers and legacy systems, preventing the chaos of agents working at cross-purposes, duplicating efforts, or allowing critical procedural steps to fall through the digital cracks. This challenge is further compounded by the current era of global trade volatility, where new tariffs create cascading effects across procurement, logistics, and compliance.Each policy shift can necessitate changes across thousands of SKUs, forcing the renegotiation of supplier contracts, the rerouting of complex logistics networks, and the rebalancing of entire inventory systems. Traditional AI systems, often trained on static historical data, struggle to adapt to such real-time, high-dimensional variability.Process intelligence, Rinke contends, provides the necessary real-time visibility into how these external shocks ripple through internal operations, a capability demonstrated by customers like Smurfit Westrock, which uses PI to optimize inventory and contain costs amid tariff uncertainty, and ASOS, which leverages it to enhance supply chain efficiency and maintain its customer experience standards. The strategic differentiator for Celonis, according to Rinke, is its architectural philosophy of treating process intelligence not as a peripheral point solution but as the foundational layer of the entire enterprise technology stack.Unlike bolt-on optimization tools, the Celonis platform aims to create a living digital twin of business operations—a continuously updated, context-rich model that allows AI to operate effectively across the entire spectrum from deep analysis to autonomous execution. This comprehensive visibility, which spans both digital systems and offline human tasks, is what Rinke believes is 'critical for true intelligent automation.' Furthermore, this capability is bolstered by the company's 'Free the Process' movement, an initiative promoting openness through open APIs, full customer access to their own process data, and a growing partner ecosystem that includes firms like The Hackett Group, ClearOps, and Lobster. For Rinke, this open, interoperable foundation is what ultimately transforms AI from a scattered set of promising experiments into a coherent, reliable enterprise engine.He describes it as a virtuous cycle or a flywheel effect: 'Better understanding leads to better optimization, which enables better AI — and that, in turn, drives even greater understanding. There is no AI without PI. ' This symbiotic relationship between process intelligence and artificial intelligence may well be the defining factor separating the few enterprises that achieve monumental ROI from the many still lost in the pilot phase.

#featured

#Celosphere 2025

#process intelligence

#enterprise AI

#ROI

#AI agents

#supply chain

#Celonis

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