The big keynote topic was expanding on this week’s announcement of a batch of new Illuminate Agents, Workday’s term for its agentic AI solutions, and the theme it wishes to push for its next 20 years as a business. These new tools include agents designed for Contingent Sourcing, Contract Intelligence & Negotiation, Document-Driven Accounting, Self-Service and Supplier Contracts. The contract agents in particular got a little extra ‘bump’ on stage from the presence of Jerry Ting, Founder/CEO of Evisort and VP at Workday.

This is because Evisort is a leading AI-native document intelligence platform which Workday acquired last fall as a potential SAP Ariba slayer on the Contract Lifecycle Management (CLM) front. As of March, Evisort’s tools became available through Workday Contract Intelligence and Workday CLM, and as of this month, Ting is now the Workday VP in charge of all things agentic AI across the Workday organization.

“Agents is the next generation of workers,” Ting declared on stage at the O2 InterContinental London venue, very much convinced that by 2045 Workday will be the ERP tool you use to manage both human and artificial employees. This was a view echoed by Daniel Pell, VP and UKI Country Leader on stage as part of his keynote, and later in a private panel at Workday Elevate London.

Talking to ERP Today, Pell stressed the difference between generative AI and agentic AI, saying that while both have a place in organizations, the agent edge comes from the “immediate reactions” possible with agents.

“[An agent] starts to understand what’s important,” he explained. “Say you’re creating a job description for a very senior executive […] it’s going to keep it confidential and it knows that because of the parameter.”

But with some potential businesses still unsure what agents exactly are as they continue to get their heads around the very notion of AI from a beginner POV, it begs the question of where agents fit into the concept of AI copilots, standalone products that remain available on the GenAI market from some vendors.

Workday Elevate and AI

Last fall, president & chief product officer of Workday rival SAP SuccessFactors, Dan Beck, told ERP Today that you won’t see SAP or its flagship HCM product “marketing a host of different AI agents”, pointing out that AI agents are by nature simply a day-to-day element of what defines an AI copilot.

At the same panel, Prasun Shah, Global CTO & AI Lead, Workforce Consulting for PwC, admitted that some clients using copilots are confused, asking “I’ve got [Microsoft] Copilot – isn’t that agentic?”

“There’s a good and a bad about what Copilot has done. It’s created the buzz around generative AI […] But the big difference between generative AI and agentic is that [the latter] is actually doing work for you inside the enterprise model.”

With one client, Shah cleared the confusion by discussing the ‘pyramid’ of human workers in their company, with those at the bottom level having a lower level of skills but developing their way ‘higher’ through the pyramid.

“The model in future will be interacting with a pyramid of agents […] As you move up the value chain of agents, you have agents with specialisms […] and some higher-order agents I loosely call the ‘headless Hydras’ who are managing a network of agents [which] they’ll orchestrate to run a particular job.”

‘Headless Hydras’ will be managing a network of agents in the pyramid

This goes back to Jerry Ting’s prediction for both the future of Workday and the workforce, especially as IT and HR functions merge ever closer on the business front. It also underlines that in the Workday view, GenAI and copilots are human-led, offering portals for ad hoc creation and app journeys using AI technology. Agentic AI meanwhile is not centered around the spontaneous or the start-up of a system, as it is instead more task-led. The difference in comparison to SAP is that companies like Workday and Salesforce are announcing each new agent on its own terms, rather than as facets of a batch update. Each one gets its moment in the spotlight  – and, handily, helps to highlight a new feature of the expanding Workday family as with the Evisort example from earlier.

At the same panel ERP Today was a Salesforce SVP, in a good reminder of the partnership between WDAY and SFDC. With Salesforce on its side, Workforce has the power to integrate its HCM/financial nature with the huge swathes of CRM data that comes with Salesforce’s formidable market strength.

It’s a canny move that will help Workday and its AI evolve ever further over the next few decades. In addition, the vendor would be wise to consider two other considerations for a fruitful and continued existence. Firstly, concentrating further on the SME sector with its recently announced Workday Go offering. Details have been limited regarding the offering, and at Workday Elevate London it was represented by a quick slide and little else.

Secondly, the HCM side of things was positioned stronger than the financial one in this year’s Elevate keynote. And yet, the most intriguing part of a presentation from AI VP Kathy Pham was a display of Workday’s AI-driven prowess in keeping up with all the latest tariff turbulence, a bread-and-butter-meets-AI financial tool that is vital to businesses now and likely to be for the next 20 years should the world become more turbulent.

This is how Workday should elevate next.

What this means for ERP Insiders

Agentic AI and Strategic Vision: At Workday Elevate London 2025, Workday emphasized its 20th anniversary by outlining its forward-looking strategy centered on agentic AI. The unveiling of new Illuminate Agents — including solutions for contingent sourcing, contract negotiation, and document-driven accounting — signals Workday’s ambition to redefine enterprise automation.

Differentiating Agentic AI from Generative AI: At Elevate, executives from Workday, PwC, and Salesforce drew a clear line between generative AI and agentic AI. The latter focuses on autonomous, context-aware task execution within enterprise systems, positioned by Workday as core functional assets. The vendor highlighted a future where human and artificial, agentic employees are managed within the same ERP framework.

Growth Levers and Market Positioning: Workday continues to invest in its SME footprint with the so-far under-publicized Workday Go and is enhancing its financial tools, such as tariff management capabilities, to match the strength of its HCM offerings. The company’s strategic alliance with Salesforce also boosts its ability to connect HCM and finance functions with CRM data, strengthening its appeal across broader business ecosystems as it looks to scale over the next two decades.

The post Workday turns 20. What now for the HCM giant? appeared first on ERP Today.

It’s not just a tech refresh—it’s a bid to future-proof the company against industry upheaval and redefine what enterprise IT can deliver across a 6,000-user, 140-location footprint.

Semler’s legacy infrastructure included 45-year-old systems built on mainframes, Lotus Notes, and custom code. Reliable? Sure. Agile and scalable? Not so much.

“The system worked, but our customers demanded more,” says Christensen. “Volkswagen Group, our key OEM partner, expects digital innovation. Internally, our teams needed smarter workflows and real-time data. We couldn’t deliver that with old tech.”

Enter: a cloud-based ERP overhaul using Microsoft Dynamics 365, enhanced with Icelandic ISV Anetta’s automotive layer. With rollout scheduled for September 2026, Semler is staging a “big bang” go-live across 4,000 users in a single day. That means not just migrating data—but transforming processes, retraining staff, and building an entirely new operating model.—

Embracing Generative AI and Azure Innovation

Semler didn’t stop at Dynamics. The company has embedded Azure OpenAI into its ecosystem with a custom-built language model called “Semler GPT.” Originally a proof-of-concept Power App in 2023, the assistant has matured into a full enterprise AI companion.

“One use case is for our used-car sales advisors,” Christensen says. “They enter a registration number, and the AI pulls data from factory systems and our databases to generate a listing. It writes the ad with the right tone of voice—Audi luxury feels different than a Volkswagen Golf.”

Even more impressive? The tool also estimates optimal pricing by analyzing market dynamics and historical sales data.

But Christensen is clear: this isn’t about cutting jobs. “It’s about quality. Freeing up people’s time for more meaningful tasks. We’re not reducing FTEs—we’re raising the bar.”

Digital Adoption: Where Whatfix Fits In

Semler’s definition of transformation success isn’t just about deployment—it’s about adoption. “We talk about the J-curve,” Christensen explains. “Productivity drops right after go-live. But the faster we get our people climbing the curve again, the faster we unlock business value.”

That’s where Whatfix, a digital adoption platform, comes into play. “We’re integrating Whatfix with Semler GPT. So when users ask how to do something—like ‘create a sales order for a new car’—they’re not just shown a document. The AI starts the process for them. Eventually, agents may do the entire task.”

This “one interface to rule them all” vision is foundational to Semler’s user experience strategy. From booking time off to checking lunch menus, the enterprise interface is being simplified and reimagined through AI.

Data Readiness and Integration: Not Just a Checkbox

With AI, everything hinges on data readiness—and Christensen knows it.

“GDPR forced us to start cleaning customer data back in 2018,” he says. “Since then, every automation project has pushed us to mature our data governance.”

Even so, some use cases—especially customer-facing AI—are still out of reach. “We have high internal usage, like call-center assistants. But until data quality improves, exposing these tools externally isn’t feasible.”

To unify its systems, Semler built an integration platform in Azure. Over 200 integrations—ranging from OEM factory systems to tire partners—run through this layer. It’s not a traditional enterprise service bus, but rather a loosely coupled microservices model. “It gives us full control, auditability, and scalability,” Christensen says.

Industry Matters

Why Microsoft? The availability of a complete platform—ERP, cloud, AI, Power Platform, and Office 365—played a role, but Christensen says the ISV offering was the clincher.

“We needed a full-scale automotive solution,” he notes. “When we found out Anetta was building that on Dynamics, and that we already used Microsoft heavily, it made sense. That said, CE and Finance and Operations aren’t fully integrated. It’s not quite plug-and-play.”

Semler’s also helping shape the Anetta solution, providing requirements and helping the ISV meet Volkswagen certification standards. “It’s a co-build, not just an implementation,” Christensen says.

Looking Ahead: From AI to In-Car Commerce

Christensen sees the future filled with agentic AI, embedded services, and predictive analytics.

“We’re starting to support in-car commerce—apps people can buy directly from their car’s interface. That has to connect back to our ERP,” he explains. “We’re also investing in predictive inventory management. When you hold a car, you’re tying up a lot of capital. Forecasting demand more precisely will be crucial.”

As compute power increases and models evolve, Christensen expects more business decisions to be AI-assisted. But first? “Still a lot of data governance to do,” he admits with a smile.

What this means for ERP Insiders

ERP is now an ecosystem, not just a system. Semler’s transformation illustrates a broader market shift: ERP is no longer a monolith. It’s a foundation that’s only valuable when paired with cloud-native integration, AI augmentation, and continuous user enablement. Microsoft’s platform strategy—combining Dynamics 365 with Azure, Power Platform, and copilots—lets companies design modular, adaptive ecosystems. ERP leaders should not only focus on core functionality, but also on how AI agents, digital assistants, and self-healing data architectures amplify value across the entire process landscape.

AI is real, but readiness is everything. Semler GPT shows that even mid-sized companies can build custom AI assistants if they have the right cloud infrastructure, data models, and culture of experimentation. But most ERP customers are still in “data denial”—overestimating the cleanliness and usability of their information. Tech leaders must prioritize metadata enrichment, master data consolidation, and data governance policies now, or risk failing to operationalize AI even when tools like Whatfix or Microsoft Copilot become turnkey.

Digital adoption platforms could be the missing link. The biggest ROI blocker for ERP investments isn’t architecture—it’s behavior. Semler’s pairing of Whatfix with AI assistants provides a compelling blueprint for how to accelerate user adoption and shorten the post-go-live productivity dip. By embedding training, guidance, and automated workflows directly into the user interface, companies can shift from “train the user” to “empower the user.” For Microsoft Dynamics customers especially, combining Whatfix’s contextual guidance with Azure-native AI could be a game-changer for long-term ERP success.

The post From Mainframe to Microsoft: Semler’s Epic ERP Overhaul to Drive a Data-Powered, AI-Enabled Automotive Empire appeared first on ERP Today.

During SAP Sapphire 2025 in Orlando, Christensen spoke with ERP Today’s Mark Vigoroso on why in an enterprise world where 20 or more instances are not uncommon, Jabil stands out with successfully running a majority of its operations on just two SAP instances across its 135 global sites.

“We’re consolidating even further,” Christensen noted. “And that simplicity is a strategic asset—it’s what gives us the ability to respond to tariffs, chip shortages, or pandemics in real time.”

That ability to respond swiftly and intelligently underpins Jabil’s definition of resilience. SAP, acting as the company’s single system of record for supply chain data, enables real-time analytics and scenario modeling across operations. During the COVID-19 pandemic and subsequent supply chain turbulence, this data backbone allowed Jabil to make instant adjustments and reconfigure supply models—without waiting 12 hours for an analyst to re-run reports.

“It may sound simple, but having the right data at the right time changed how we survived disruption,” Christensen said. “That’s what resilience looks like.”

Listen in to learn more.

The post Chase Christensen on Why Jabil’s Relationship with SAP is More Than a Legacy appeared first on ERP Today.

The Dynamic Duo: AI and IoT

The study found that 29% of manufacturers are already witnessing artificial intelligence and machine learning (AI/ML) integrated into their ERP systems, with the Internet of Things (IoT) integration following closely at 19%. Moreover, nearly 30% and 20% of these businesses see AI and IoT being baked into ERPs specifically for efficiency gains.

SYSPRO describes AI not as a job-stealing robot but as a tireless, insightful co-pilot that can help monitor workflows, flag anomalies before they become disasters, and automate complex decision-making processes. The power provided by AI helps organizations move from reactive firefighting to proactive problem-solving. Utilizing these technologies enhances data analytics, optimizes maintenance schedules, and drastically minimizes downtime.

The Supporting Cast of ERP Innovations

While AI and IoT might be grabbing the spotlight, other crucial ERP advancements are quietly revolutionizing complex manufacturing, the study shows:

• Real-time data analytics (16% adoption): The ability to tap into real-time operational data provides the visibility needed to sidestep disruptions and make informed decisions quickly. For instance, if there is a sudden spike in demand for a particular product, an organization can view that rise via its ERP dashboard. It can then immediately adjust production schedules, check raw material availability, and coordinate with logistics in real time, preventing stockouts and capitalizing on the opportunity.
• Cloud-based ERP solutions (13% adoption): Cloud ERPs offer the scalability to grow with the business, enhanced security, seamless data integration from various sources, and easier adoption of advanced technologies like AI.
• Mobile accessibility and remote management (13% adoption): The factory floor and the entire supply chain are no longer tethered to a desktop. ERP functionality accessible via mobile devices empowers everyone from quality inspectors to on-the-go sales teams who need instant inventory updates.
• Enhanced cybersecurity features (10% adoption): With legacy systems being replaced, and data becoming more centralized, robust cybersecurity isn’t just an IT concern; it’s a business continuity imperative. This is underscored by the fact that over 50% of industry experts in some regions view cybersecurity as a critical concern.

The Smart Factory and The Human Element

These evolving ERP capabilities are the building blocks of the smart factory — a highly connected, intelligent, and responsive manufacturing environment. Future-focused factories seamlessly integrate Industrial IoT (IIoT), AI, digital twin simulations, and, at their core, modernized ERP systems. This integration enables businesses to prevent disruptions before they happen and continuously optimize operations.

However, the path to achieving this goal isn’t always smooth. The report highlights some very real barriers:

• High upfront costs (cited by 25% of respondents)
• Resistance to change (22%)
• Lack of technical expertise (19%)
• Challenges with integrating new tech with existing systems (12%)
• Technical difficulties with complex integrations (43%)

These figures represent real-world headaches for operations managers, IT departments, and ERP professionals. Overcoming them requires technological savvy and a focus on the human side of change. This includes clear communication, robust training, and showcasing how these tools empower employees to do their jobs better, faster, and with less frustration.

What This Means for ERP Insiders

Embrace AI & IoT as your efficiency power-ups. ERP professionals are pivotal in deploying these technologies. SYSPRO, for instance, leverages its ERP to integrate with IoT devices for real-time data and machine-to-machine communication, driving tangible gains like predictive maintenance and optimized production. ERP professionals’ role is to translate this potential into reality on the shop floor to create truly digital manufacturing facilities.

Champion data and cloud for agility and scalability. Real-time analytics and cloud ERP enable proactive decision-making and scalable infrastructure. ERP professionals should guide this transition. For example, SYSPRO customer Merle Norman Cosmetics saved $6 million in inventory costs through real-time data, and Aspire Pharmaceuticals achieved 98% inventory accuracy. Moving to platforms like SYSPRO Cloud ERP also paves the way for easier adoption of AI, which is often “built into the heart of such solutions.

Drive modernization and fortify security strategically. While high upfront costs and complex integration are significant hurdles to becoming a smart factory, the strategic need is undeniable. With over 50% of industry experts in some regions citing cybersecurity as a critical concern, ERP professionals must prioritize secure, robust systems. Your expertise is crucial in navigating these challenges, advocating for the necessary investments, and ensuring the ERP backbone is future-proof and resilient against emerging threats.

The post AI, IoT and Smart Factories: The Game-Changers for Complex Manufacturing appeared first on ERP Today.

Thomas Saueressig, SAP Board Member for Product Engineering, opened the keynote by reminding the crowd that “the pace of change has never been this fast—and yet it will never be this slow again.” He emphasized that transformation today is the foundation for tomorrow’s resilience. “We shipped, we delivered, but we cannot stop here,” he stated, citing customers’ demand for “faster time-to-value, innovation cycles, and cost control.”

But this keynote was different. Less monologue, more dialogue. Throughout, live audience polling was used to surface concerns, with one striking result: 40% of the world’s GDP is now touched by customers using Rise with SAP. SAP Sapphire 2025 showcased a confident, customer-aligned SAP—one that understands its own complexity and is willing to rewire itself alongside its users. “The best is yet to come,” promised SAP’s new Chief Customer Officer. But for enterprise leaders, the time is now. Transform not because it’s trendy—but because today’s decisions, like SAP says, “will shape tomorrow’s resilience.”

From Legacy to Lift-Off: Mercedes-Benz, Mars, Phoenix Global

Mercedes-Benz, a symbol of precision engineering and innovation, shared how it’s tackling complexity head-on. With over 10,000 enterprise applications—1,200 of them SAP-related—CIO Cathey Lehman turned to Rise with SAP to rationalize and modernize the company’s digital core. “We grouped and tackled systems using the TIME method—transform, invest, migrate, eliminate,” she explained. More than just cloud migration, this strategy underpins Mercedes’ AI ambition, from engineering (via GitHub Copilot) to a natural-language interface for shop-floor problem solving.

“We’re leveraging AI across our entire value chain,” Lehman emphasized. “We’ve deployed our internal ChatGPT-like solution, and we’re excited to expand with SAP’s Joule and Business AI stack.”

At Phoenix Global, a metals and mining company, the transformation story was existential. After explosive growth led them into bankruptcy, new CIO Jeff Salentros spearheaded a radical reboot: eight sites replatformed in 8 months using SAP Public Cloud ERP. “We ripped out everything—paper and pen, fragmented systems—and replaced it with best-practice SAP,” said Salentros. “We’ve already returned millions through better equipment maintenance, utilization, and embedded AI.” It’s a textbook example of cloud ERP enabling not just operational agility, but financial recovery.

Mars Inc. highlighted the scaling power of SAP’s three-tier ERP strategy. The confectionery giant runs flagship brands like M\&M’s and Snickers—but it’s their newer acquisitions (True Fruit, Kind Snacks, Nature’s Bakery) that demanded a flexible ERP backbone. CIO Bill discussed how Mars deploys SAP Public Cloud for agile startups, a Rise instance for retail, and a customized S/4HANA template for its core operations. “It allows small businesses to plug in fast and scale,” he said. VP Praveen Muthuraj added, “With model-driven architecture and embedded analytics, we’ve seen huge productivity gains—especially from Joule and real-time automation.”

The Age of Agentic ERP: SAP’s Response to AI Uncertainty

Amid enthusiasm for AI, the audience revealed a common concern: data remains the biggest barrier to value realization. SAP responded with a clear direction—business-ready AI, embedded natively, governed responsibly.

With the SAP AI Foundation and Joule, SAP aims to democratize AI across finance, HR, procurement, and operations. Embedded copilots will become ubiquitous, from quality issue detection on factory floors to onboarding via natural language prompts. “This isn’t just AI—it’s agentic AI,” said Thomas, referring to SAP’s vision of interconnected, autonomous agents coordinating tasks, governance, and outcomes across the enterprise.

SAP also unveiled a new partnership with AWS, offering a “dedicated AI co-innovation fund” to accelerate industry-specific AI applications built on SAP BTP using AWS models and infrastructure. This move signals SAP’s commitment to unlocking verticalized, customer-defined AI without the technical sprawl or cost typically associated with custom builds.

Complexity: The Silent Killer of Productivity

A striking revelation came during a poll about enterprise application growth. In 2000, the average $10B company ran just 10 core applications. In 2025? Over 600. The cloud has enabled rapid adoption—but at the cost of fragmentation.

Christian Klein’s message was clear: “More technology doesn’t equal better business outcomes. In fact, global productivity growth has declined—despite SaaS explosion.” From 1995–2005, productivity grew 2.6%. From 2005–2025? Just 1.5%. SAP’s proposed antidote: an integrated, harmonized enterprise foundation, powered by Business Technology Platform (BTP), unified data models, and embedded AI.

Saueressig reinforced the point with use cases:

• BHP created $500M in value by using Signavio to orchestrate process redesign and shared services reinvention.
• Nestlé reclaimed 105M work hours by leveraging SAP Enable Now across 200+ applications.
• First Abu Dhabi Bank reduced its application landscape by 25%—streamlining cost and complexity.

What this means for ERP Insiders

Reinvent your core with fit-to-suite, not fit-to-standard. SAP’s evolution of Rise with SAP—from “fit to standard” to “fit to suite”—is more than marketing lingo. It reflects a new model of cloud ERP implementation: one that embraces tailored lifecycle orchestration, custom dashboards, and embedded AI for transformation readiness. CIOs should evaluate SAP’s new transformation prep services and explore toolchains that cut project costs by 30%—critical at a time when many SAP S/4HANA programs still run in the $100M+ range. For example, Mercedes-Benz’s use of AI-guided migration is a leading model worth emulating.

Use AI as a business lever, not a side project. SAP’s embedded Joule copilot and BTP-based agentic AI framework are designed to operationalize AI at scale, from procurement to HR. But successful adoption depends on unified data models and strong governance. Mars’ model-driven architecture and tiered ERP rollout show how to scale AI across M&A-heavy portfolios. Tech leaders should build AI competency centers and partner with SAP on use-case co-creation—particularly via the new AWS/SAP AI fund. Start with low-lift, high-impact scenarios like maintenance scheduling or finance forecasting to prove value.

Tame application sprawl—focus on integrated outcomes. The statistic that productivity has dropped despite a 60x increase in application count is a wake-up call. Instead of expanding toolsets, CIOs should consolidate workflows around unified platforms. SAP’s BTP, Signavio, and Business Data Cloud (BDC) provide foundational capabilities to align business processes, enable reuse, and simplify integration. Start by auditing your application portfolio and building a business capability map to drive rationalization. As Phoenix Global’s turnaround showed, even a complete rip-and-replace can be profitable if guided by simplicity and standardization.

The post SAP Sapphire 2025 Customer Keynote: “Bring Out Your Best” and Reinvent the Future of Enterprise ERP appeared first on ERP Today.

In a revealing, freewheeling interview with ERP Today, Kask peeled back the curtain on how SAP is building, scaling, and operationalizing AI at enterprise scale—not just as a technology trend, but as a competitive moat. “Even I have trouble keeping track of all the announcements and use cases,” he admitted with a laugh. “But make no mistake—this has been years in the making.”

In a landscape flooded with AI hype, SAP’s strategy stands out for its depth, rigor, and customer-first pragmatism. As Kask summed it up: “You want assets that are hard to replicate, and an organization that can exploit them. That’s how you lead—not just this year, but for the next ten.”

Building a Platform, Not Just a Product

Kask’s 13-year journey with SAP began in cloud transformation and matured through the company’s AI evolution, particularly since joining SAP’s machine learning and AI unit eight years ago. Today, he reports directly under CEO Christian Klein as part of a growth area that behaves more like a startup-within-a-giant.

SAP’s approach to AI is intentionally pluralistic, avoiding the common trap of model monoculture. “We realized early that no ERP company is going to sink $200 million into training foundational models at the pace hyperscalers do,” Kask explained. “These models commoditize fast, and performance improves every few weeks. So our strategy is to partner broadly with curated models—OpenAI, Google Gemini, AWS Nova, Meta, Mistral, NVIDIA, even niche ERP-specialized models like Zora.”

But SAP doesn’t just “plug and play” with LLMs. The company layers a sophisticated AI foundation atop its Business Technology Platform (BTP), using tools like retrieval augmented generation (RAG), knowledge graphs, output validation, and a new “Prompt Optimizer” developed with a Silicon Valley startup. This optimizer automatically rewrites prompts when switching models—cutting what used to be weeks of effort down to near zero.

“It’s behind-the-scenes magic,” said Kask, “but it’s the kind of infrastructure that allows us to deliver AI that’s not just impressive in the lab, but reliable and explainable in a real-world enterprise.”

Embedded, Ethical, and Explainable

For all its technical firepower, SAP’s AI strategy begins with ethics. “We design for human empowerment, not displacement,” said Kask, referencing SAP’s published AI Ethics Policy—one of only six companies to earn a perfect score in the World Benchmarking Alliance’s ethics evaluation.

This philosophy translates into every product decision. Before AI takes an action in a system, it requires human verification. Outputs are transparent and traceable, showing what data was used, where it was pulled from, and what the system “thought” step-by-step. “Think of our agents like very fast interns,” Kask quipped. “They’re helpful, but you still want to double-check their work.”

Even SAP’s go-to-market approach prioritizes controlled experimentation. Early adopter programs—like the rollout of “Joule” to thousands of internal and partner consultants—enable rigorous feedback loops before mass deployment. And yes, Kask said, adoption is accelerating. “It reminds me of the early days of cloud. There’s a learning curve for legal, compliance, and security teams. But once the first use case lands, the floodgates open.”

Joule, Agentic AI, and the Rise of the Autonomous ERP

Nowhere is this more evident than in Joule, SAP’s AI assistant, which recently surpassed 1,600 “skills” and is moving from task automation toward what Kask calls “native agenticness.”

“Most people think of agents as standalone bots you have to manage. With Joule, it’s different. The system itself becomes the agent,” he said. “If you ask it to ‘give a spot award to my five top-performing employees and send a personalized email,’ it can plan and execute that multi-step process autonomously, because those skills are already natively embedded.”

That’s a far cry from a glorified chatbot—and it’s underpinned by some serious architectural muscle. SAP has constructed a proprietary knowledge graph across its massive ERP landscape—452,000 ABAP tables and over 7 million fields—giving context that generic LLMs can’t hope to replicate. “When you extract ERP data into hyperscaler data lakes, you lose context,” said Kask. “You can try to rebuild it, but you’ll never match the depth we have.”

This knowledge graph now enables foundation models on tabular data—distinct from LLMs—to predict regressions, match invoices, and improve accuracy on narrow AI tasks. It’s a clear example of SAP’s strategy: use general-purpose models where appropriate, but rely on proprietary assets for true differentiation.

Commercializing AI, Carefully

With AI capabilities embedded into its product suite—and often activated via subscription—SAP is seeing strong commercial traction. “Christian [Klein] has said that 40–50% of new deals now have AI attached,” Kask noted. “There’s a commercial model, and yes, the models can be expensive to run. But customers see the value.”

SAP now mandates AI discovery workshops post-sale and tracks adoption closely. “Our success metric is not just building it, but getting it live. That’s why we published the AI feature catalog. That’s why we have dashboards. It’s all about real use.”

Still, the company isn’t inflating its numbers for Wall Street. “Some vendors are touting their AI revenue, but we’re skeptical. There’s a lot of fuzzy math—direct vs. indirect. We’re playing the long game.”

Owning the Integration Layer

As the AI arms race heats up, so too does the question of ecosystem positioning. Where does SAP fit in a world where hyperscalers, competitors like ServiceNow, and even niche ERP players are all building agents and automation?

“We’re not trying to be everything,” Kask clarified. “But we are laser-focused on integration. Our agents don’t just wrap around processes—they live inside them. With tools like Signavio, LeanIX, and WalkMe, we can see, map, and optimize entire process flows across applications.”

That includes embedding AI into transformation tools like enterprise architecture (via LeanIX) and UI-level interactions (via WalkMe). “We want to own the transformation stack. Not just the database. Not just the UI. The intelligence in between.”

What this means for ERP Insiders

AI adoption is the new differentiator—but requires intentional design. CIOs and COOs should treat AI adoption not as a standalone innovation track but as a core KPI. SAP’s Joule, for example, has demonstrated measurable time savings—up to 1.5 hours per day per consultant. By embedding AI in business processes via tools like BTP, enterprises can reduce friction, accelerate time-to-value, and gain strategic advantage. Begin with AI discovery workshops, leverage SAP’s AI feature catalog, and use internal pilot programs to refine before scaling.

Proprietary context beats generic models—invest in knowledge graphs. One of SAP’s most defensible innovations is its domain-specific knowledge graph. For SAP customers, this means far lower hallucination risk, more accurate agent outputs, and better integration between structured and unstructured data. Tech leaders should evaluate vendors on their ability to preserve context—especially for agent-based use cases—and consider building their own knowledge layers on top of vendor platforms to enable AI-powered autonomy with precision.

Ethics, transparency, and governance will define winners. AI success isn’t just about speed or scale—it’s about trust. SAP’s top-tier ethics score from the World Benchmarking Alliance underscores a crucial shift: regulatory scrutiny is coming, and enterprises that can demonstrate auditable, human-in-the-loop processes will be favored. ERP buyers should demand full transparency from vendors: where models run, what data they access, how decisions are made, and what governance layers exist. Design for explainability from day one.

The post From SAP Sapphire 2025: Sean Kask, Chief AI Strategy Officer, Opens SAP’s AI Playbook, Covers Agentic Intelligence, Strategic Differentiation, and the Race to Real Adoption appeared first on ERP Today.

“We needed a platform that could handle global scale, localization, and compliance right out of the box,” said Christensen. SAP provided that foundation early on, enabling Jabil to achieve SOX compliance while supporting lean, highly standardized operations. Over time, SAP’s role has expanded, powering everything from supply chain management to finance and regulatory compliance.

Today, Jabil runs the majority of its operations on just two SAP instances across 135 global sites. That’s an anomaly in the enterprise world, where 20 or more instances are not uncommon. “We’re consolidating even further,” Christensen noted. “And that simplicity is a strategic asset—it’s what gives us the ability to respond to tariffs, chip shortages, or pandemics in real time.”

That ability to respond swiftly and intelligently underpins Jabil’s definition of resilience. SAP, acting as the company’s single system of record for supply chain data, enables real-time analytics and scenario modeling across operations. During the COVID-19 pandemic and subsequent supply chain turbulence, this data backbone allowed Jabil to make instant adjustments and reconfigure supply models—without waiting 12 hours for an analyst to re-run reports.

“It may sound simple, but having the right data at the right time changed how we survived disruption,” Christensen said. “That’s what resilience looks like.”

Jabil’s move from ECC to S/4HANA is another example of its pragmatic innovation. Initially, the company piloted a Greenfield implementation. But after assessing organizational impact, they pivoted to a Brownfield approach. That decision, supported by SAP MaxAttention and advisory services, enabled Jabil to migrate 250 accounts to SAP S/4HANA within 18 months—at enterprise scale.

SAP’s ongoing innovation in AI has caught Christensen’s attention as well. Jabil was an early adopter of AI and machine learning, using them to improve forecasting and automate processes through RPA and NLP. Now, with the rise of generative and agentic AI, Jabil is evaluating SAP Joule and other emerging tools—but with a healthy dose of skepticism.

“We exist in a hybrid environment—on-premise, cloud, Rise with SAP—and we’re not going to rewrite everything overnight. We need to understand how tools like Joule complement our current stack and where the ROI really is,” he said.

That demand for value realization is a recurring theme. Christensen emphasized the importance of holding partners accountable—not just for delivery, but for outcomes. “I pay SAP a lot,” he said, half-joking. “I want net-new value from what I’m already paying, not just more licenses. That means tangible ROI from the tools we’ve already bought.”

This pragmatic mindset extends to Jabil’s entire innovation strategy. “We don’t invest in the shiniest object,” Christensen said. “We invest in what moves a metric. If we can’t see a business case in a few weeks, we shut it down.” That fail-fast, scale-fast mentality allows Jabil to stay competitive without becoming chaotic.

Jabil also leverages SAP Business Technology Platform (BTP), SAP Integration Suite, and Signavio to drive business architecture maturity, connect legacy systems, and manage compliance across diverse regulatory environments. They’ve prioritized integration layers, document management, and GTM alignment tools to future-proof their SAP investment.

That investment is also about people. As AI agents evolve, Christensen sees the opportunity not as replacing jobs but as augmenting employees—especially in manufacturing and supply chain roles. “Yes, we’re rebalancing the workforce,” he said. “But it’s about removing the menial tasks so employees can do higher-value work. That’s the real power of AI.”

He also believes that workforce transformation will be driven by generation shifts. “More digital natives are entering the workforce, and they expect systems to work like their phones. We have to design for that.”

Ultimately, Jabil’s vision is one of controlled transformation—moving quickly, but never recklessly. “We have a North Star,” Christensen concluded. “And every technology decision—whether it’s SAP, AWS, or GenAI—is about getting us closer to that vision without losing what makes us operationally excellent.”

What this means for ERP Insiders

Prioritize simplicity in global ERP strategy. Jabil runs its global operations with just two SAP instances across 135 sites. For ERP leaders, that’s a compelling argument for consolidation and standardization. By minimizing ERP sprawl, organizations can unlock agility, reduce risk, and improve response times during disruption. SAP customers should evaluate the feasibility of single-instance strategies using SAP S/4HANA, Integration Suite, and BTP to centralize operations.

Embed real-time decision support in supply chain operations. Christensen highlighted that Jabil’s ability to re-run supply models in minutes was critical to their pandemic and tariff resilience. SAP customers should focus on embedding real-time analytics using SAP HANA Cloud and SAP Analytics Cloud to enable instant scenario modeling. Resilience is about responsiveness—and that starts with trustworthy, accessible data.

Invest in AI use cases that augment, not replace. Jabil’s approach to GenAI is rooted in augmentation—freeing up supply chain professionals and analysts to focus on what matters most. SAP customers can replicate this with Joule and SAP AI Core, targeting use cases like invoice reconciliation, contract analysis, and demand forecasting. When AI removes low-value tasks, humans can focus on strategic impact.

The post From SAP Sapphire 2025: How SAP Helps Jabil Achieve Resilience at the Speed of Industry appeared first on ERP Today.

The company received the “Rising Star” designation in the 2025 ISG Provider Lens ServiceNow Ecosystem Partners report for Europe, underscoring its growing expertise. Another pivotal development is the March 2025 inauguration of its Center of Excellence for ServiceNow Agentic AI. Inetum is among the initial ten partners chosen by ServiceNow for Agentic AI development, co-creating solutions like “CI Smart Recommendations,” an add-on that leverages ServiceNow’s GenAI applications to promote self-healing IT and autonomous operations.

While these achievements directly enhance ServiceNow’s capabilities, the underlying technological shifts and strategic focuses carry clear parallels and learning points for ERP professionals and the systems they manage.

Inetum’s advancements within the ServiceNow sphere are a significant marker for the direction of enterprise technology. For ERP sector professionals, these developments underscore the accelerating integration of intelligent, proactive, and increasingly autonomous capabilities. Adapting to and leveraging these changes will drive future innovation and efficiency in ERP-managed operations.

What This Means for ERP Insiders

Advanced AI integration is becoming standard for enterprise platforms. Inetum’s focused investment in Agentic AI for ServiceNow indicates a broader trend: sophisticated AI is transitioning from an auxiliary feature to an integral component of enterprise software. This suggests a future beyond current analytics or basic automation for ERP systems. The expectation will be that AI agents are capable of predictive analysis and proactive intervention in core processes such as inventory management, production scheduling, or financial reconciliation. ERP professionals should anticipate AI that identifies issues and recommends or even initiates solutions based on continuous learning. This necessitates strategically evaluating how AI can be embedded to redefine operational efficiency within ERP environments.

Self-healing and autonomous operations are extending to ERP domains. The concepts of self-healing IT and autonomous operations, central to Inetum’s new AI offering, directly apply to ERP functionalities. This could manifest as systems that autonomously detect and resolve discrepancies in period-end financial closing processes, flagging only critical exceptions for human review. Similarly, supply chain modules could gain the ability to autonomously adjust logistics based on real-time disruption data, learning from events to mitigate future risks. This evolution does not point to replacing ERP personnel, but to augmenting their roles, enabling a shift from reactive problem-solving to strategic oversight and process optimization.

Evolving partner ecosystems and the value of specialized AI solutions. The collaboration between Inetum and ServiceNow to develop targeted AI solutions like CI Smart Recommendations highlights the increasing importance of specialized expertise in the evolving technology ecosystem. While general AI tools provide a foundation, maximum value in the enterprise space, particularly for complex ERP systems, will be derived from AI solutions tailored to specific business functions and industry verticals. ERP professionals should, therefore, identify partners and solutions that combine AI proficiency with deep knowledge of their specific ERP platform and operational intricacies. As stated by Hemant Lamba, CEO of Inetum Solutions, their focus is on developing AI solutions that can support the future of business operations — a future that integrally involves ERP systems.

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SAP and Google Cloud are working across every layer of enterprise technology—data integration, AI agents, infrastructure, and security—to help customers reduce project risk, accelerate innovation, and tap into the power of their existing SAP systems. This isn’t AI for AI’s sake. This is AI for outcomes.

At the core of this partnership is a shared focus on generative AI and agent-based architectures. SAP’s Joule is now enhanced with Google Cloud’s Gemini models via the SAP Generative AI Hub on SAP BTP. These AI agents can now act across SAP applications with intelligence and autonomy—providing everything from invoice resolution and marketing content generation to natural language customer service.

Google Agentspace further empowers this vision, offering a unified interface for users to access enterprise agents and SAP data from wherever they work. Whether it’s a CRM, IT ticketing tool, or data analytics suite, employees can now invoke AI with full SAP context. Agent2Agent (A2A) protocols allow SAP and Vertex AI agents to talk to each other—cutting out brittle, manual integrations and replacing them with standards-based intelligence orchestration.

Companies like AMD are already seeing results. Using Vertex AI and the Cortex Framework, AMD built finance and customer operations chatbots that fetch real-time SAP data and respond in natural language—reducing service time and accelerating forecasting insights.

For decades, SAP data has been siloed, locked behind complex integrations and analytics workarounds. Now, BigQuery and SAP Business Data Cloud are changing that. With prebuilt connections and models from Google Cloud’s Cortex Framework, customers can activate their SAP data in real time for ML, analytics, and operational workflows.

Brazilian paper giant Suzano is a standout example. Using Cortex and gen AI, the company created a natural language interface that allows employees to query SAP data via simple questions—cutting data retrieval time by 90% and democratizing enterprise insights across teams.

But AI means nothing if it’s not supported by the right infrastructure and security. That’s why Google Cloud has rolled out new SAP-optimized VM families like M4 and C4D, offering 127% performance gains at 36% lower TCO. With single-instance 99.95% uptime SLAs, even the most demanding S/4HANA environments now run reliably and securely under RISE with SAP.

Security is equally robust. Google Unified Security and Assured Workloads provide multilayered defense for SAP workloads, supporting ITAR and public-sector compliance mandates. These tools offer real-time monitoring, access control, and threat mitigation built into the cloud fabric—enabling SAP customers to operate with resilience and confidence.

What this means for ERP Insiders

Activate your AI strategy with agents, not experiments. Enterprise leaders should prioritize AI initiatives that are embedded into business workflows—like Gemini-powered SAP Joule agents or Google Agentspace integrations. AMD’s chatbot success shows that AI, when paired with real-time SAP data, can enhance operations without requiring a total replatform. Start with finance, service, or procurement to see fast wins.

Make your SAP data actionable now. Instead of warehousing data for dashboards, consider using Cortex and BigQuery to make SAP data active, connected, and ready for ML. As Suzano proved, giving teams self-service access to SAP insights via natural language can transform decision-making and accelerate ROI across the board.

Future-proof your ERP infrastructure for scale and security. Don’t wait for legacy systems to fail before upgrading. Google Cloud’s new SAP-optimized infrastructure ensures better performance and lower costs, with built-in security and compliance. For RISE with SAP customers, this means peace of mind with always-on uptime, ITAR-ready workloads, and real-time observability.

The post From SAP Sapphire 2025: How SAP and Google Cloud Are Accelerating Real-World Impact from AI appeared first on ERP Today.

A Big Opportunity for SMBs

According to Sage, this development is a direct response to the evolving needs of SMBs. The company’s “Small Business, Big Opportunity” report indicates that 85% of SMBs now view technology as critical to operational success. The upgraded Sage 50 aims to meet this demand by offering:

• Faster reporting via natural language AI searches
• AI-powered data extraction to automate purchase transactions and reduce errors
• Enhanced security features, including AI-driven fraud detection

Access to these new cloud-connected features, including Sage Copilot, will be managed through the unified Sage account login, promising a more secure and seamless user experience.

“Sage 50 has been the backbone of small business accounting for decades, and these new enhancements ensure it will remain a trusted tool for years to come,” said Neal Watkins, EVP, Accounting & HR, Sage. “We know many of our customers rely on it, and we’re committed to making it even better by integrating AI and automation to save them time, reduce manual work, and improve cash flow.”

Reaping Benefits with AI

The AI-powered Sage Copilot will proactively monitor financial data, offering actionable recommendations. For SMB users, this translates into tangible benefits like:

• Generating custom reports instantly
• Identifying trends
• Spotting anomalies
• Reducing administrative overhead

Commenting on the practical implications of this enhanced solution, David Harvey, Co-Founder of Seabass Vinyl and an early adopter, said: “We’re really excited about what Sage Copilot can do, especially in saving time on admin that takes us away from bigger priorities. Having those proactive insights will be a huge help as we scale.”

What This Means for ERP Insiders

Sage is doubling down on its focus on UK-based SMBs. The AI integration in Sage 50 augments a familiar system that UK-based businesses use. Key use cases directly address SMB pain points: automating tedious purchase data entry, simplifying report generation (a common bottleneck), and bolstering security without requiring deep IT expertise. For ERP consultants serving this segment, it highlights a trend of embedding AI to solve particular, practical challenges rather than offering broad, undefined AI capabilities. This approach eases adoption for traditionally less tech-forward SMBs.

AI democratization and SMB tech reliance. AI is no longer an enterprise-only play. Sage’s move exemplifies the democratization of AI, making sophisticated tools accessible within existing, trusted software. For ERP professionals, this means even smaller clients will increasingly expect AI-driven efficiencies in any new or upgraded system. The market demands intelligent automation that delivers clear ROI, particularly regarding time savings and error reduction.

With Sage 50, users are evolving with a known quantity. This approach minimizes disruption and leverages existing customer trust. This strategy suggests that for established software vendors, incrementally adding AI value to core products can be more successful than a rip-and-replace approach, especially when dealing with change-averse SMBs. The focus should be on how AI assists and augments human capabilities, making processes faster and decisions smarter, thus freeing up valuable owner/operator time for strategic tasks rather than administrative churn.

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