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    Home»AI News»Inside Celosphere 2025: Why there’s no ‘enterprise AI’ without process intelligence
    Inside Celosphere 2025: Why there’s no ‘enterprise AI’ without process intelligence
    AI News

    Inside Celosphere 2025: Why there’s no ‘enterprise AI’ without process intelligence

    adminBy adminOctober 31, 2025No Comments5 Mins Read
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    Presented by Celonis

    AI adoption is accelerating, but results often lag expectations. And enterprise leaders are under pressure to prove measurable ROI from the AI solutions — especially as the use of autonomous agents rises and global tariffs disrupt supply chains.

    The issue isn’t the AI itself, says Alex Rinke, co-founder and co-CEO of Celonis, a global leader in process intelligence. “To succeed, enterprise AI needs to understand the context of a business’s processes — and how to improve them,” he explains. Without this business context, AI risks becoming, as Rinke puts it, “just an internal social experiment.”

    Next week’s Celosphere 2025 will tackle the AI ROI challenge head-on. The three-day event brings together customer strategies, hands-on workshops, and live demonstrations, highlighting enhancements to the Celonis Process Intelligence (PI) Platform that help enterprises harness ‘enterprise AI,’ powered by PI, to continuously improve operations, creating measurable business value at scale.

    Focus on measurable ROI

    The event’s focus on achieving AI ROI reflects three challenges facing technology and business leaders moving from pilot to production: obsolete systems, break-neck industry change, and agentic AI. According to Gartner, 64% of board members now view AI as a top-three priority — yet only 10% of organizations report meaningful financial returns.

    Celonis customers are bucking that trend. A Forrester Total Economic Impact study found organizations using its platform achieved 383% ROI over 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 $44.1 million in total benefits over three years, driven by faster automation, reduced inefficiencies, and higher process visibility. These numbers underscore a broader pattern — companies that modernize outdated systems and align AI with process optimization see faster payback and sustained gains.

    Real companies, real results

    Celosphere will spotlight how global enterprises are building “future-fit” operations. Mercedes-Benz Group AG and Vinmar Group will showcase AI-driven, composable solutions, powered by PI, and attendees will see demonstrations of PI enabling agents in live production environments.

    Among the notable success stories:

    AstraZeneca, the pharmaceutical company, reduced excess inventory while keeping critical medicines flowing by using Celonis as a foundation for its OpenAI partnership.

    The State of Oklahoma can answer procurement status questions at scale, unlocking over $10 million in value.

    Cosentino clears blocked sales orders up to 5x faster using an AI-powered credit management assistant.

    Raising the stakes for agentic AI

    Numerous sessions will focus on orchestrating AI agents. The shift from AI-as-advisor to AI-as-actor, changes everything, says Rinke.

    “The agent needs to understand not just what to do, but how your specific business actually works,” he explains. “Process intelligence provides those rails."

    This leap from recommendation to autonomous action raises the stakes exponentially. When agents can independently trigger purchase orders, reroute shipments, or approve exceptions, bad context can mean catastrophically bad outcomes at scale.

    Celosphere attendees will get to see first-hand how companies are using the Celonis Orchestration Engine to coordinate AI agents alongside people and systems. Effective orchestration is a crucial protection against the chaos of agents working at cross-purposes, duplicating actions, or letting crucial steps fall through the cracks.

    Navigating tariffs and supply chain shocks

    Global trade volatility isn't just a headline — it's an operational nightmare reshaping how companies deploy AI, Rinke says.

    New tariffs trigger cascading effects across procurement, logistics, and compliance. Each policy shift can cascade across thousands of SKUs — forcing new supplier contracts, rerouted shipments, and rebalanced inventories. For AI systems trained on static conditions, that volatility is almost impossible to predict. Traditional AI systems struggle with such variability — but process intelligence gives organizations real-time visibility into how changes ripple through operations.

    Celosphere case studies will show how companies turn disruption into advantage. Smurfit Westrock uses PI to optimize inventory and reduce costs amid tariff uncertainty, while ASOS leverages PI to optimize its supply chain operations, enhancing efficiency, reducing costs, and continuing to deliver an outstanding customer experience.

    Platform over point solutions

    Rinke argues that Celonis’ edge lies in treating process intelligence not as an add-on, but as the foundation of the enterprise stack. Unlike bolt-on optimization tools, the Celonis platform creates a living digital twin of business operations — a continuously updated model enriched by context that lets AI operate effectively from analysis to execution.

    “What sets Celonis apart is visibility across systems and offline tasks, which is critical for true intelligent automation,” Rinke says. “The platform offers comprehensive capabilities spanning process analysis, design, and orchestration rather than a point solution.”

    “Free the Process” and the future of AI

    Celonis continues to champion openness through its “Free the Process” movement, promoting fair competition and freeing enterprises from legacy lock-in. By giving organizations full access to their own process data, open APIs, and a growing partner network that includes The Hackett Group, ClearOps, and Lobster, Celonis is building the connective tissue for a new era of interoperable automation.

    For Rinke, this open foundation is what turns 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 — and that, in turn, drives even greater understanding. There is no AI without PI."

    Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.



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