Presented by Celonis
The implementation of artificial intelligence is accelerating, but the results often differ from expectations. Enterprise leaders are under pressure to demonstrate a measurable return on investment in AI solutions – especially as the utilize of autonomous agents increases and global tariffs disrupt supply chains.
The problem isn’t artificial intelligence itself, says Alex Rinke, co-founder and co-founder of Celonis, a global leader in process intelligence. “To be successful, enterprise AI must understand the context of business processes and how to improve them,” he explains. Without this business context, AI may become, as Rinke puts it, “just an internal social experiment.”
Next week Celosphere 2025 will tackle the AI ROI challenge head-on. The three-day event combines customer strategies, hands-on workshops and live demonstrations, highlighting enhancements to the Celonis Process Intelligence (PI) platform that assist enterprises leverage PI-powered “enterprise AI” to continuously improve operations, creating measurable business value at scale.
Focus on measurable ROI
Focused on achieving ROI in AI, the event reflects three challenges facing technology and business leaders as they move from pilot to production: legacy systems, breakneck industry change, and agent-based AI. According to Gartner64% of board members currently rank AI as one of their top three priorities, but only 10% of organizations are seeing significant financial gains.
Celonis customers are bucking this trend. AND Forrester Total Economic Impact Study found that organizations using the platform achieved a 383% ROI in three years, with payback in just six months. One company improved sales order automation from 33% to 86%, saving $24.5 million. The study estimated total benefits over three years of $44.1 million from faster automation, less inefficiency and greater process transparency. These numbers underscore a broader pattern – companies that modernize dated systems and adapt artificial intelligence to optimize processes see faster cost recovery and sustainable profits.
Real companies, real results
Celosphere will highlight how global enterprises are building operations fit for the future. Mercedes-Benz Group AG and Vinmar Group will showcase AI-powered, composable PI-based solutions, and attendees will see demonstrations of PI-enabled agents in real production environments.
Among the notable success stories:
AstraZenecapharmaceutical company, reduced excess inventory while maintaining the flow of key medicines, using Celonis as the basis for its OpenAI partnership.
State of Oklahoma can answer order status questions at scale, unlocking over $10 million in value.
Cosentino clears blocked sales orders up to 5 times faster using an AI-powered credit management assistant.
We’re raising the stakes for agentic AI
Multiple sessions will focus on coordinating AI agents. The shift from AI as advisor to AI as actor changes everything, Rinke says.
“An agent must understand not only what to do, but also how your particular company actually works,” he explains. “Process intelligence provides these rails.”
This leap from recommendation to autonomous action raises the stakes exponentially. When agents can independently trigger orders, reroute shipments, or approve exceptions, bad context can mean disastrously bad results at scale.
Celosphere participants will be able to see with their own eyes how companies utilize the Celonis Orchestration Engine to coordinate AI agents with people and systems. Effective orchestration is a key safeguard against the chaos of agents working for different purposes, duplicating activities, or allowing key steps to get lost.
Dealing with tariffs and supply chain shocks
Volatility in global trade isn’t just a headline – it’s an operational nightmare changing the way companies deploy artificial intelligence, Rinke says.
The up-to-date tariffs have a cascading effect across procurement, logistics and compliance. Each policy change can cascade across thousands of SKUs – forcing up-to-date supplier agreements, supply redirection, and inventory rebalancing. For AI systems trained in stationary conditions, it is almost impossible to predict this variability. Customary AI systems struggle with this variability, but process intelligence gives organizations real-time visibility into how changes are impacting operations.
Celosphere’s case studies will show how companies turn disruption into advantage. Smurfit Westrock uses PI to optimize inventory and reduce costs in the face of tariff uncertainty, while ASOS uses PI to optimize supply chain operations, raise efficiency, reduce costs and continually deliver an exceptional customer experience.
Platform point solutions
Rinke argues that Celonis’ advantage lies in treating process intelligence not as an add-on, but as the foundation of the enterprise stack. Unlike integrated optimization tools, the Celonis platform creates a living digital twin of business operations – a continuously updated, context-enriched model that enables AI to operate effectively from analysis to execution.
“What sets Celonis apart is the visibility between systems and offline tasks, which is crucial for true intelligent automation,” says Rinke. “The platform offers comprehensive capabilities spanning process analysis, design and orchestration, rather than a point solution.”
“Free the Process” and the Future of Artificial Intelligence
Celonis continues to advocate for openness through the “Free the Process” movement, promoting fair competition and freeing businesses from established closures. By providing organizations with full access to their own process data, open APIs and a growing network of partners including The Hackett Group, ClearOps and Lobster, Celonis is building the connective tissue for a up-to-date era of interoperable automation.
For Rinke, this open foundation transforms AI from a set of experiments into an enterprise engine. “Process intelligence creates a flywheel,” he says. “Better understanding leads to better optimization, which enables better AI, which in turn leads to even greater understanding. There is no AI without PI.”
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