Introduced by Celonis
AI adoption is accelerating, however outcomes typically lag expectations. And enterprise leaders are below stress to show measurable ROI from the AI options — particularly as using autonomous brokers rises and world tariffs disrupt provide chains.
The problem isn’t the AI itself, says Alex Rinke, co-founder and co-CEO of Celonis, a worldwide chief in course of intelligence. “To succeed, enterprise AI wants to know the context of a enterprise’s processes — and how one can enhance them,” he explains. With out this enterprise context, AI dangers turning into, as Rinke places it, “simply an inside social experiment.”
Subsequent week’s Celosphere 2025 will deal with the AI ROI problem head-on. The three-day occasion brings collectively buyer methods, hands-on workshops, and reside demonstrations, highlighting enhancements to the Celonis Course of Intelligence (PI) Platform that assist enterprises harness ‘enterprise AI,’ powered by PI, to constantly enhance operations, creating measurable enterprise worth at scale.
Give attention to measurable ROI
The occasion’s give attention to attaining AI ROI displays three challenges going through expertise and enterprise leaders shifting from pilot to manufacturing: out of date programs, break-neck trade change, and agentic AI. According to Gartner, 64% of board members now view AI as a top-three precedence — but solely 10% of organizations report significant monetary returns.
Celonis clients are bucking that development. A Forrester Total Economic Impact study discovered organizations utilizing its platform achieved 383% ROI over three years, with payback in simply six months. One firm improved gross sales order automation from 33% to 86%, saving $24.5 million. The research estimated $44.1 million in complete advantages over three years, pushed by quicker automation, decreased inefficiencies, and better course of visibility. These numbers underscore a broader sample — firms that modernize outdated programs and align AI with course of optimization see quicker payback and sustained good points.
Actual firms, actual outcomes
Celosphere will highlight how world enterprises are constructing “future-fit” operations. Mercedes-Benz Group AG and Vinmar Group will showcase AI-driven, composable options, powered by PI, and attendees will see demonstrations of PI enabling brokers in reside manufacturing environments.
Among the many notable success tales:
AstraZeneca, the pharmaceutical firm, decreased extra stock whereas holding important medicines flowing through the use of Celonis as a basis for its OpenAI partnership.
The State of Oklahoma can reply procurement standing questions at scale, unlocking over $10 million in worth.
Cosentino clears blocked gross sales orders as much as 5x quicker utilizing an AI-powered credit score administration assistant.
Elevating the stakes for agentic AI
Quite a few periods will give attention to orchestrating AI brokers. The shift from AI-as-advisor to AI-as-actor, modifications all the things, says Rinke.
“The agent wants to know not simply what to do, however how your particular enterprise truly works,” he explains. “Course of intelligence gives these rails.”
This leap from suggestion to autonomous motion raises the stakes exponentially. When brokers can independently set off buy orders, reroute shipments, or approve exceptions, unhealthy context can imply catastrophically unhealthy outcomes at scale.
Celosphere attendees will get to see first-hand how firms are utilizing the Celonis Orchestration Engine to coordinate AI brokers alongside individuals and programs. Efficient orchestration is an important safety towards the chaos of brokers working at cross-purposes, duplicating actions, or letting essential steps fall by means of the cracks.
Navigating tariffs and provide chain shocks
International commerce volatility is not only a headline — it is an operational nightmare reshaping how firms deploy AI, Rinke says.
New tariffs set off cascading results throughout procurement, logistics, and compliance. Every coverage shift can cascade throughout hundreds of SKUs — forcing new provider contracts, rerouted shipments, and rebalanced inventories. For AI programs educated on static circumstances, that volatility is sort of unimaginable to foretell. Conventional AI programs wrestle with such variability — however course of intelligence offers organizations real-time visibility into how modifications ripple by means of operations.
Celosphere case research will present how firms flip disruption into benefit. Smurfit Westrock makes use of PI to optimize stock and scale back prices amid tariff uncertainty, whereas ASOS leverages PI to optimize its provide chain operations, enhancing effectivity, decreasing prices, and persevering with to ship an excellent buyer expertise.
Platform over level options
Rinke argues that Celonis’ edge lies in treating course of intelligence not as an add-on, however as the muse of the enterprise stack. In contrast to bolt-on optimization instruments, the Celonis platform creates a residing digital twin of enterprise operations — a constantly up to date mannequin enriched by context that lets AI function successfully from evaluation to execution.
“What units Celonis aside is visibility throughout programs and offline duties, which is important for true clever automation,” Rinke says. “The platform affords complete capabilities spanning course of evaluation, design, and orchestration somewhat than a degree answer.”
“Free the Course of” and the way forward for AI
Celonis continues to champion openness by means of its “Free the Course of” motion, selling truthful competitors and liberating enterprises from legacy lock-in. By giving organizations full entry to their very own course of information, open APIs, and a rising accomplice community that features The Hackett Group, ClearOps, and Lobster, Celonis is constructing the connective tissue for a brand new period of interoperable automation.
For Rinke, this open basis is what turns AI from a set of experiments into an enterprise engine. “Course of intelligence creates a flywheel,” he says. “Higher understanding results in higher optimization, which allows higher AI — and that, in flip, drives even higher understanding. There isn’t a AI with out PI.”
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