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.

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.

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.

The post Inetum Earns ISG “Rising Star,” Launches ServiceNow Agentic AI Center 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.

The post Sage 50’s AI-Powered Copilot to Boost UK SMB Efficiency appeared first on ERP Today.

The new Joule is powered by SAP’s AI Foundation and is designed to live inside workflows, not outside them. That means finance users can request margin forecasts, HR leaders can identify attrition risk, and supply chain managers can simulate disruption scenarios – all within their existing SAP UI, using conversational prompts.

This isn’t a point solution. Joule is integrated into core SAP analytics and apps, enriched by the SAP Graph, and governed through LeanIX. It understands context, permissions, and process state—a leap forward from generic chatbots.

Joule’s impact is already visible. A global consumer goods company is using Joule to automate 60% of its HR service requests. A European auto parts supplier has cut time-to-resolve for customer disputes in SAP S/4HANA by 40%. And SAP itself has deployed over 100 Joule use cases internally, generating measurable cost savings and productivity improvements.

What this means for ERP Insiders

Shift from process automation to decision co-piloting. With Joule embedded in every SAP app, enterprises can move beyond workflow automation and into intelligent co-piloting. Joule understands business rules, adapts to user behavior, and surfaces recommendations in real time. This supports faster, more confident decisions—especially in cross-functional ERP environments where latency kills momentum.

Eliminate friction in daily operations. Joule’s omnipresence means users no longer need to toggle between systems or rely on technical teams for insights. For example, a procurement manager using Ariba can use Joule to summarize supplier risk, generate RFQs, and initiate approvals—all within a single pane of glass. This embedded intelligence reduces cognitive load and accelerates time-to-outcome.

Operationalize AI at scale through embedded governance. Joule is not just smart—it’s secure. Its actions are governed through SAP LeanIX, ensuring agent activity is visible, auditable, and aligned with enterprise goals. As SAP expands Joule agents across functions, ERP leaders gain a federated, controlled way to scale generative AI without introducing risk or fragmentation.

The post From SAP Sapphire 2025: Joule Everywhere – How SAP Is Making Business AI Omnipresent and Proactive appeared first on ERP Today.

At the center of this transformation is a shift in how ISVs, resellers, and enterprises interact. Google’s latest enhancements to its Marketplace—announced by Dai Vu, Managing Director of Google Cloud Marketplace and ISV GTM Initiatives—highlight three major changes: a new variable revenue share model for partners, streamlined commit drawdown through channel partners, and a customer incentive program to drive new workload adoption.

One of the most transformative changes is Google Cloud’s shift to a variable revenue share model. Rather than a flat cut, the Marketplace now adjusts fees based on the nature of the deal. For example, large private offers of $10M or more now incur only a 1.5% revenue share, allowing partners to retain 98.5% of total contract value. Even smaller deals—under $1M—are charged just 3%, which still significantly undercuts many competing platforms.

This move is already resonating with partners. Shaun Clowes, CPO at Confluent, noted that the update better aligns with their growth strategy and helps monetize demand more effectively across deal sizes. The economic flexibility empowers ISVs to scale across a wide range of customer segments while maintaining profitability.

For enterprise buyers locked into cloud commitments, being able to draw down those commitments against software purchases is a major purchasing incentive. Google Cloud has now made that simpler. As of June 9, 2025, qualifying Marketplace purchases made via Channel Private Offers (MCPOs) will result in 100% commit drawdown tied to the final negotiated price.

This policy makes Google Cloud’s Marketplace a more strategic procurement path—not only for customers with cloud minimums to meet but also for the channel partners who can now maintain the customer relationship, recognize topline revenue, and offer tailored services.

Momentum is clear. Between 2023 and 2024, the value of third-party software resold through Google Cloud Marketplace’s channel partners grew by 170%, proving that this model is gaining traction across the ecosystem.

With the general availability of the Marketplace Customer Credit Program (MCCP), Google Cloud is giving customers another reason to explore the Marketplace. This program offers up to 3% in Google Cloud credits for eligible first-time software purchases, which can then be applied toward Google Cloud’s own services. It’s a clever incentive: customers benefit from cost offsets, partners win new business faster, and Google secures deeper cloud engagement.

This is particularly significant in the AI space, where customers often need to test and deploy new agents in low-friction, cost-effective ways. Google Cloud’s new AI Agent Marketplace—an emerging category within the Marketplace—provides an open door to experiment with enterprise-ready AI solutions backed by infrastructure-grade support.

What this means for ERP Insiders

Enterprise ERP buyers should rethink marketplace strategy. For Oracle Fusion customers navigating multi-cloud and hybrid environments, Google Cloud Marketplace offers a compelling opportunity to centralize ISV procurement. The ability to draw down Google Cloud commitments while purchasing pre-integrated ERP tools or AI extensions through the Marketplace allows IT and procurement teams to improve budget utilization and reduce friction. For ERP programs that rely on third-party planning, automation, or analytics tools, leveraging this model can streamline sourcing and integration.

ERP vendors must embrace the economics of scale. For ERP-adjacent ISVs, Google’s variable revenue share model represents a powerful growth lever. By retaining up to 98.5% of revenue on high-value deals and still benefiting from the discoverability of a global cloud Marketplace, solution providers can reinvest in innovation, customer support, and AI capabilities that enhance Oracle Fusion environments. Vendors that optimize Marketplace strategy will gain a competitive edge in cost and reach.

AI adoption in ERP requires accessible channels. As AI agents begin augmenting finance, HR, and supply chain processes, ERP leaders must create safe, scalable paths to experimentation. Google Cloud’s AI Agent Marketplace—combined with MCCP credits—offers a low-risk entry point for Oracle customers seeking to evaluate AI copilots or autonomous agents. This infrastructure enables test-and-learn strategies that won’t disrupt core ERP systems while accelerating innovation at the edges.

The post Marketplace Momentum: How Google Cloud is Rewiring the Economics of Enterprise Software appeared first on ERP Today.

According to Inetum, this restructuring will bring the company closer to its clients, better respond to regional nuances, and turbocharge the execution of its two core business lines: Inetum Solutions, led by Hemant Lamba, and Inetum Consulting, led by Emmanuelle Payan.

François Fleutiaux Appointed to Head EUROMED

The newly formed EUROMED hub significantly consolidates Inetum’s regional presence, bringing together France, Luxembourg, Belgium, Morocco, and Tunisia.

The region will be helmed by François Fleutiaux, who has joined Inetum and has experience in leadership roles at Orange Business France, T-Systems International, IBM, Unisys, and Fujitsu. Inetum indicated that his track record in driving growth and leading major transformations with a customer-centric approach signals a clear intent to energize this key region, which is home to many businesses reliant on robust SAP landscapes.

Inetum Expands Kathy Quashie’s Role

The “Growing Markets” hub, encompassing the United Kingdom, Ireland, Switzerland, and Eastern Europe, will be led by Kathy Quashie.

This expands Quashie’s role as CEO of Growing Markets for the Inetum Group. She was previously at the helm of Inetum’s UK and Ireland markets, and her expanded role underscores the company’s ambition in these territories that represent significant markets for SAP adoption and transformation.

Manuel Garcia Del Valle Carlos Roca to Continue Leading LATAM Ops

According to Inetum, the established Iberia-LATAM zone, already a model of regional synergy, will continue under the region’s current CEO, Manuel Garcia Del Valle Carlos Roca. This continuity highlights the success of the company’s integrated approach across Spain, Portugal, Mexico, Peru, Colombia, and Brazil.

All three regional leaders will report directly to Jacques Pommeraud, Chairman and CEO of the Inetum group, and will be integral members of the Group Executive Committee.

Building on a Successful Model

Commenting on the changes, Jacques Pommeraud, Chairman and CEO of Inetum, stated, “This simplification of our organization builds on the proven success of our Iberia-LATAM model, which has demonstrated how markets sharing cultural and economic ties can generate significant synergies.”

He added that grouping operations into these three strategic areas will create more powerful entities capable of accelerating innovation and optimizing Inetum’s presence across its markets.

What This Means for ERP Insiders

With this new structure, Inetum is seeking to enhance service delivery. ERP users should note that this structural change from a partner like Inetum aims to maximize its local footprint and promote the cross-pollination of best practices. These are vital elements when undertaking complex ERP projects or seeking ongoing support and innovation from partners like SAP, which already has a strong presence in these regions.

A renewed regional focus signals more substantial synergies. For ERP professionals, these changes at Inetum highlight a strategic intent to become more synergistic across all its locations, which can directly impact the quality and relevance of the services you receive. Expect tailored approaches that better understand the specific challenges and opportunities within each geographic market where your ERP system operates.

Greater potential for leveraging shared expertise. Inetum’s emphasis on strengthening regional synergies also suggests potentially strengthened shared resources across borders, which could translate into more efficient project delivery and innovative solutions. For example, the move could result in even more competitive service models for clients navigating the complexities of digital transformation with SAP S/4HANA, cloud migrations, or other ERP initiatives.

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Smarter AI for the Shop Floor and Beyond

Epicor Prism introduces conversational AI to traditionally manual environments like the shop floor, warehouse, and sales desk. Built as a suite of industry-specific digital agents, it allows employees to interact with their ERP systems using natural language commands. Instead of manually navigating complex interfaces, users can ask for a list of overdue quotes, insights on part availability, or recommended suppliers and receive immediate, actionable responses.

Andy Young, VP Systems and Processes at Olympus Group, noted the potential impact of this technology on his operations. “One of the most important metrics for us is on-time delivery,” he said. “I really think Epicor Prism can increase our responsiveness to customers and get a typical eight-week delivery time down to four weeks. There’s probably opportunity for a 20% gain in the operation.” This highlights a key use case: reducing lead times and improving customer satisfaction through more intelligent, responsive systems.

Meanwhile, Epicor Grow AI aims to enhance data quality and scalability by integrating ERP, third-party, and legacy data into predictive models. This data backbone powers tools like Item Advisor, which automatically suggests complementary products during the order process—potentially increasing basket sizes and reducing abandoned carts. The platform’s focus on data quality is critical, as poor data remains a top barrier to effective AI adoption across industries.

Decarbonization as a Core Business Metric

With global pressure mounting on companies to reduce carbon emissions, Epicor also introduced the Carbon Cost Rollup—a patent-pending tool designed to measure and manage the carbon footprint of products from raw material to final assembly. This feature is integrated into the Epicor Kinetic ERP system and borrows from traditional cost accounting methods to assign a “carbon cost” at every stage of production.

As Kerrie Jordan, Group VP at Epicor, put it, the tool is meant to elevate emissions data to the same level of business scrutiny as financial costs. This approach could provide a more transparent way for manufacturers to meet ESG targets and comply with increasingly stringent environmental regulations. The Carbon Cost Rollup also benefits from Epicor’s 2024 integration with Climatiq’s carbon footprint APIs, further enhancing its ability to capture real-time sustainability metrics.

What This Means for ERP Insiders

AI is Becoming a Critical Operational Layer. Predictive AI is no longer a futuristic add-on—it’s becoming an essential part of day-to-day operations. Epicor’s Prism and Grow AI demonstrate how conversational and predictive tools can reduce manual workloads and accelerate response times without requiring data scientists on staff. Companies should assess their current ERP environments to identify high-friction areas where these types of tools could drive immediate efficiency gains.

Sustainability is Now a Core KPI. For manufacturers, tracking carbon costs at the bill of materials level is a game-changer. This approach moves sustainability from marketing material to the core of operational decision-making. For CIOs and CTOs, the question is no longer whether to measure carbon, but how accurately and at what granularity. Companies that can calculate their carbon impact in real-time are likely to have a strategic advantage as ESG reporting requirements tighten globally.

Usability Will Define the Next Wave of ERP Winners. Embedding advanced capabilities like generative AI and carbon accounting directly into ERP workflows addresses a critical barrier to user adoption. If your ERP strategy relies on disconnected, bolt-on solutions, it may be time to reconsider. The most impactful technologies are those that enhance user productivity without disrupting established workflows, ensuring faster ROI and higher overall adoption rates.

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“Winning Gold three years in a row is a tremendous honor—and a reflection of our team’s relentless innovation and focus on customer success,” said Rick Berger, CEO of Rootstock Software. “This Gold Stevie Award is also a tribute to the results our customers have achieved,” added Berger.

ERP As Digital Nervous System

At the heart of Rootstock’s platform is what it calls the “Signal Chain”—a connected framework across demand, supply, and production capacity. It’s a digital nervous system for manufacturers, enabling them to forecast demand, simulate sourcing changes, and fine-tune production with speed and clarity. In an era of trade tension, supply chain disruption, and economic whiplash, that kind of intelligence isn’t just nice to have—it’s survival gear.

Award judges and industry analysts alike praised Rootstock for its rapid release cycles, tight customer feedback loops, and embedded AI. “Rootstock’s financial and transactional enhancements equip finance and operations teams with precise tools to optimize decision-making in complex manufacturing environments,” one judge noted.

With global manufacturing on track to reach $16.6 trillion in 2025 (World Bank and Statista data) and digital transformation spend expected to top $3.4 trillion by 2026 (International Data Corporation), companies are under pressure to modernize fast. Rootstock’s momentum suggests it’s not just keeping up—it’s helping lead the charge.

What This Means for ERP Insiders

Modernization is no longer optional: The triple Gold win underscores a broader shift: legacy ERP systems are increasingly seen as liabilities. Rootstock’s continued recognition reflects a market shift towards AI-native, cloud-first architectures that minimize technical debt and accelerate deployment timelines. That said, the prevailing direction isn’t necessarily full cloud migration for everyone. The most forward-looking organizations are adopting situationally adaptive hybrid models—balancing public cloud, private cloud, and on-prem infrastructure to meet performance, regulatory, and business continuity needs. ERP leaders still managing fully on-prem or heavily customized systems should reevaluate whether their architectures can support dynamic forecasting, scenario planning, or intelligent automation—all of which are quickly becoming essential capabilities.

AI: from hype to business muscle: Rootstock’s customers are translating AI from buzzword to bottom-line results—specifically through predictive AI used in forecasting and inventory simulation. These capabilities power intelligent workflows that support real-time decision-making across production and supply chain functions. In a world where businesses must respond within hours—not weeks—this form of operational AI is becoming the backbone of agility. According to a Rootstock customer case study shared in 2025, a mid-market electronics manufacturer achieved a 40% reduction in demand planning time and a 15% boost in on-time delivery by leveraging Rootstock’s predictive AI tools to flag sourcing risks before they triggered delays.

Velocity is the new differentiator: Rootstock’s focus on customer success isn’t just anecdotal; it’s operationalized. The company has built an ERP solution that allows manufacturers to pivot rapidly in response to tariffs, labor fluctuations, or global disruptions. For ERP decision-makers, the lesson is clear: speed, adaptability, and user empowerment are today’s true differentiators. Rootstock’s modular, cloud-native design enables faster implementation and continuous configuration—qualities that leading manufacturers now consider essential to staying competitive in a volatile market. Companies embracing this kind of composable, business-led approach are seeing measurable gains in deployment speed and cost efficiency—not in theory, but in practice.

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