SAP and its partners are moving AI from slideware to production by embedding SAP Business AI and SAP Business Technology Platform (SAP BTP) into specific workflows that cut cycle times, shrink proof-of-concept windows, and rewire core planning processes. Reported on December 22, three customer use cases show how partner-led designs are using SAP’s embedded AI capabilities to raise process throughput, normalize experimentation, and create an ERP core that can scale AI scenarios across plants, regions, and business units.
Is SAP Business AI an Embedded Engine?
SAP positions SAP Business AI as a set of purpose-built, domain-rich capabilities embedded across its applications to automate processes, support decision-making, and improve employee productivity. Plus, SAP BTP is framed as an amplifier for this foundation, enabling integration, extension, and custom AI solutions in a scalable, secure environment that can span departments and regions.
Process Automation Cutting Cycle Times
For frozen-food manufacturer FRoSTA, partners sovanta AG and Amista identified invoice processing as a major operational bottleneck and redesigned it using SAP Build Process Automation and SAP Document AI. Invoices that previously required several minutes of manual effort now move through the system in under a minute, with about 60% fully automated. That allows employees to focus on exception handling and supplier collaboration rather than repetitive data entry, the article notes.
The FRoSTA example illustrates how combining partner process expertise with SAP Business AI and SAP BTP shifts organizations from narrow task automation to connected, intelligent workflows that can scale across functions and geographies. What begins as a single automation use case becomes the basis for a broader automation strategy that accelerates processes, reduces manual work, and tightens the link among data, people, and decisions.
Making AI More Accessible
The article stresses the scarcity of specialized AI talent and positions SAP partners as a bridge that makes AI more accessible to business teams. Aspen Pumps, working with NTT DATA, used low-code tools in SAP Build for workflow design and orchestration, along with SAP AI Core for model execution, to rapidly build 12 automation bots for activities such as invoice validation, order routing, and interpreting CAD drawings to speed quote creation.
Many proof-of-concept initiatives at Aspen Pumps were completed in under a week, showing how embedded intelligent capabilities and low-code tooling can normalize experimentation and shorten the path from idea to production. Innovation becomes a routine, distributed activity when AI is available inside existing tools, rather than a scarce capability gated by specialist teams, the article adds.
Future-Ready Architectures
On the architecture side, leaders now prioritize platforms that scale with AI ambitions while preserving core stability—Al Ghurair Iron and Steel (AGIS) is a reference case. Working with Deloitte, AGIS reimagined its production planning using SAP Business AI embedded in SAP S/4HANA Cloud, private edition, coupled with SAP BTP for integration and extension; planning cycles dropped from 15 minutes of manual coordination to less than five minutes.
The AGIS solution has been replicated across multiple locations, with more than 400 calculations automated, which shifts staff time from spreadsheet maintenance to analysis and optimization. This case reportedly supports the broader claim that when SAP Business AI and SAP BTP are combined with partner expertise, companies gain a scalable foundation that can extend across plants, regions, and business units, connecting SAP and non-SAP environments into what SAP describes as a cohesive, intelligent landscape.
What This Means for ERP Insiders
AI-infused workflows are redefining ERP value creation. The FRoSTA and Aspen Pumps examples show that value comes from deeply reworked workflows that marry domain expertise with tools like SAP Build, SAP Document AI, and SAP AI Core, not from isolated models or generic automation. For roadmap and product owners, this is a shift toward packaged, outcome-specific AI scenarios that can be replicated and extended quickly, turning process redesign into a core competitive discipline rather than a one-off project.
Low-code and embedded AI are reshaping how ERP innovation is resourced. Aspen Pumps’ ability to stand up 12 bots, with proofs of concept completed in under a week, illustrates how low-code and embedded AI capabilities move experimentation closer to the teams that own the work. For ERP vendors and system integrators, this means partner offerings, enablement, and governance models must assume that business-aligned teams will drive more of the innovation cycle, with central IT and product organizations setting guardrails and reusable patterns rather than acting as the sole builders.
AI-ready ERP architectures are becoming the backbone for operational reinvention. The AGIS story, with planning cycles cut by two-thirds and more than 400 calculations automated on SAP S/4HANA Cloud, private edition and SAP BTP, shows how core ERP platforms are evolving into strategic engines for AI-infused planning and execution. For enterprise architects and transformation leaders, this highlights that future resilience depends on architectures that can scale embedded AI scenarios across locations and mixed SAP and non-SAP estates, allowing operations teams to iterate on AI-driven planning and optimization without destabilizing the core.
