Introduced by SAP
Ten years in the past, Western Sugar decided that will show prescient: transfer from on-premise SAP ECC to SAP S/4HANA Cloud Public Version. On the time, synthetic intelligence wasn't a precedence on most roadmaps. The corporate was merely attempting to flee what Director of Company Controlling, Richard Caluori, calls "a trainwreck:” a heavily customized ERP system so laden with custom ABAP code that it had become unupgradable.
Today, that early cloud adoption is proving to be the foundation for Western Sugar's AI transformation. As SAP accelerates its rollout of business AI capabilities across finance, supply chain, HR, and more, Western Sugar finds itself uniquely positioned to take advantage of the technology.
"We didn't transfer to the cloud enthusiastic about AI," Caluori says. "However that call to embrace clear core rules and standardized processes turned out to be precisely what we would have liked when AI capabilities grew to become obtainable. The clear knowledge, the standardized workflows, the disciplined processes, all of that groundwork we laid for fundamental operational causes is now the inspiration that makes AI work. We have been prepared with out even figuring out it."
Building AI readiness with a clean core ERP foundation
Western Sugar's journey began with a familiar enterprise problem: technical debt. Years of on-premise customization had created a system that was nearly impossible to maintain or upgrade.
"As a result of we have been on premise, we may do our personal coding in ABAP, and through the years we created such a large number with our inner coding that the software program was not upgradable," Caluori explains. "The rapid advantages of transferring to public cloud have been clear: decreased infrastructure burden and entry to straightforward processes refined by SAP. They've been on this enterprise for 40 to 50 years, and so they put all their expertise into this one answer. Now upgrades simply work."
But the most significant advantage proved to be the clean core philosophy inherent in public cloud deployments, which means the software is maintained and upgraded by SAP. This approach, combined with robust API connectivity, created an environment where Western Sugar's IT department could easily integrate systems.
In SAP S/4HANA Cloud Public Edition, this model keeps core ERP logic standardized and upgradeable, while extensions and integrations are handled through SAP-supported APIs and services.
"Ultimately, now we have decrease whole price of possession, a greater product, and the information high quality and course of self-discipline that's important for AI adoption," Caluori says.
This clean core foundation — standardized, continuously updated, and API-connected — is what makes embedded AI viable inside SAP Cloud ERP.
How clean core processes in SAP enabled AI automation
When SAP began rolling out SAP Business AI capabilities inside SAP S/4HANA Cloud Public Edition, Caluori was amped to improve processes through automation and standardization in ways they'd never previously imagined. The company's first major AI implementation focused on central invoice management.
Today, invoices arrive from external sources and pass through the firewall. If they meet predefined AI confidence thresholds, SAP Business AI automatically posts them with zero human keyboard input. Each transaction is continuously evaluated using a traffic-light model: green items are processed automatically, yellow items are routed for review, and red items are flagged for immediate attention.
"As a result of the bill simply flows by means of the system robotically, we're held to a excessive customary," he says. "The AI-driven performance solely works if the entire course of chain, from buying requisition to buy order to receiving to issuing is clear, so we're continuously enhancing these upstream processes to satisfy the calls for of our AI improvements."
Quantifying the operational impact of AI automation
Caluori estimates Western Sugar has achieved six-figure direct cost savings through AI automation, not accounting for improved visibility and control.
"Once I log into my pc now, I can see instantly in actual time what's happening throughout the procurement facet," he says. "I’ve a complete cockpit view that I didn't have earlier than. As a result of I’ve way more visibility, I’ve way more management over operations."
The company is now expanding AI adoption into new areas. With Western Sugar's recent transition to SAP's three-speed landscape, Caluori is targeting month-end closing processes for AI automation.
"My objective is that AI handles the overwhelming majority of the month-end shut," he says. "Over time, as AI learns what we're doing and the way we shut the books, the objective is to automate over 50 % of the month's finish closing actions. We're additionally trying ahead to AI-managed procurement networks, and proactive reporting and intelligence, all of which can quickly be attainable."
Western Sugar is also developing predictive maintenance AI for its manufacturing equipment — a critical capability for its large-scale facilities, where equipment failures can halt production and lead to losses in the hundreds of thousands of dollars. These efforts build on SAP’s AI and analytics capabilities across asset management and manufacturing systems.
"We've began an inner workforce engaged on predictive analytics with AI, the place the system can inform us upfront if we have to be on alert for particular tools — {that a} specific machine may break down within the subsequent two or three days or perhaps weeks," Caluori explains. "If we are able to proactively tackle these points earlier than they trigger manufacturing stoppages, it will save us thousands and thousands of {dollars}."
Managing organizational change alongside AI adoption
While the technology itself has delivered clear benefits, the organizational impact has been more complex. For Western Sugar, modernizing its core systems early — by moving to SAP’s cloud and embracing standardized, upgrade-driven processes — required not just new workflows, but a fundamental shift in how employees thought about change itself.
For Caluori, that readiness is non-negotiable. “Change management is the number-one key to success,” he says. “We had to do a lot of change management, not only around business processes, but around employee behavior as well.”
That work paid off over time, in part because cloud adoption normalized continuous change. As upgrades became routine rather than disruptive, employees grew more comfortable with evolution as an operating condition.
“Now, when SAP comes with a new upgrade, they know change is coming,” Caluori explains. “The mindset has shifted to being eager to see what improvements the next update will bring.”
And that cultural shift has proven critical as Western Sugar moves beyond system upgrades and into more advanced initiatives.
“Now people are even eager to move into AI — the bigger projects,” he adds.
However, that cultural readiness must be driven from the top. At Western Sugar, executive leadership — many of whom came from large international organizations — understands the competitive necessity of staying current with technology. That top-down commitment has helped normalize continuous change and created the foundation required to pursue AI strategically.
Lessons in AI readiness from Western Sugar
For companies considering their own AI journeys, Western Sugar's experience offers a clear lesson: AI readiness begins long before AI adoption. The clean core, standardized processes, and strong data quality that Western Sugar established a decade ago, driven purely by the need to escape technical debt, proved to be exactly what AI required. And while Caluori acknowledges the advantage an early start gave them, he says the second-best time to start is now.
"It’s a must to embrace these modifications, in any other case you're left behind," Caluori says. "That steady enchancment is what SAP offers us, and now with AI capabilities built-in all through, we're seeing advantages we couldn't have imagined once we began this journey."
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