The hardest part of buying enterprise software isn’t finding it—discovery is basically solved. You can find thousands of enterprise software options in an afternoon. The hard part is everything that happens between finding the right solution and actually having access to it.
Who owns the procurement motion? How does pricing get negotiated? Who handles the contract? What about tax, invoicing, and payment? Which team tracks approvals? And once it’s signed, how does it fit into existing contracts and renewal cycles?
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Most of these previously mentioned challenges occur in e-mail chains, spreadsheets, and conversations that no one fully documents. Seventy-three percent of B2B buyers actively avoid suppliers who send irrelevant outreach—they’ve already done their research by the time they engage. But the internal process of actually completing a purchase remains as manual as it was a decade ago. Research, shortlist, evaluate, and then hand it off to a process that moves at a completely different speed.
This is especially true for organizations with existing SAP investments. Expanding a software landscape that’s already complex—adding new capabilities, aligning contracts, managing co-term timing across multiple products—adds layers of coordination that can slow even straightforward decisions to a crawl. Every new solution that doesn’t co-term with an existing contract means another renewal date to track, another negotiation cycle to manage, and another piece of the landscape that runs on its own timeline.
SAP Store exists to help remove those layers and barriers. For SAP customers, it’s the single place to discover, trial, and purchase both SAP and partner solutions—over 3,600 of them—within an environment that’s already connected to their existing SAP landscape. When a customer modifies an existing contract through SAP Store, new purchases automatically co-term with the original order. Pricing and discounts, if applicable, are inherited from the previous contract. There are no separate renewal cycles to manage, no renegotiations from scratch.
The buying process itself is also built to help remove the common points of friction. Automated entitlement checks confirm compatibility before a purchase is completed. Pre-verified product dependencies prevent deployment issues after the fact. For customers that want to move quickly, many solutions offer a “Buy Now” path that goes from selection to provisioned access in under 15 minutes. No forms to fill out, no calls to schedule.
The Danish wholesaler Lemvigh‑Müller has deployed artificial intelligence to automate one of the most time‑consuming tasks in procurement: processing supplier order confirmations. The solution consists of multiple AI agents, each responsible for a clearly defined task, orchestrated into a single automated workflow built on SAP Business AI. The outcomes are faster processing, improved data quality, and more accurate delivery information for customers.
When suppliers send order confirmations as PDF files, even minor discrepancies in price, quantity, or delivery dates can trigger significant manual effort within procurement. For Lemvigh‑Müller, one of Denmark’s largest wholesalers within steel, plumbing, heating and electrical products, this has long been a familiar challenge, consuming substantial time and resources.
The company has now tackled the very point where earlier automation initiatives often stalled. With a new solution based on several specialized AI agents, developed on SAP technology and implemented in close collaboration with NTT DATA Business Solutions, supplier PDF order confirmations can now be read, interpreted, compared, and processed automatically—directly against SAP systems.
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“We have previously tried both RPA and traditional automation approaches without really achieving the desired effect. The key difference this time is that we broke the task down into multiple independent AI agents, each responsible for a specific part of the process. Together, they now handle what previously required manual review,” says Frederik Aakerlund, IT director at Lemvigh‑Müller.
10 weeks from idea to AI agents in production
The project originated with an e-mail from Jess Frederiksen, an AI‑savvy project manager in Lemvigh‑Müller’s Market and Procurement organization. After successfully matching an order confirmation with a purchase order using ChatGPT as an experiment, he approached the IT director to explore whether this could be turned into a fully integrated system solution.
From the initial tests to production deployment, the entire project took just 10 weeks. According to Lemvigh‑Müller, this short implementation timeline was critical in allowing the solution to demonstrate tangible business value quickly and build internal support.
“This was not a long-running project. In 10 weeks, we moved from idea to AI agents in production, already delivering measurable value to our procurement officers,” Aakerlund says.
Over time, Lemvigh‑Müller expects the solution to free up resources equivalent to three to four full-time employees. These resources will instead be redeployed to higher-value activities, including handling the most complex and exception‑driven orders.
“The objective is not to reduce headcount, but to use our expertise more effectively. The AI agents take care of routine tasks, enabling procurement officers to focus on cases where their experience genuinely matters,” Aakerlund adds.
More than 100,000 order confirmations automated
Each year, Lemvigh‑Müller sends approximately 175,000 purchase orders to more than 2,000 suppliers. While part of this volume is handled in a structured manner via EDI, around 60% of supplier order confirmations are still received as unstructured documents.
With the coordinated AI agents in place, the company can now automatically identify delays, quantity changes, and price discrepancies—and respond significantly faster.
“Previously, when order confirmations were handled manually, it could take hours or even days before changes were reflected across the organization. Today, the AI agents update the data almost immediately, allowing customers to receive a much more accurate picture of deliveries far sooner,” says Klaus Heinemann, head of SAP ERP at Lemvigh‑Müller, who led the development together with the project team. “In addition, we now identify price discrepancies before the final invoice is issued, saving time both for us and for our suppliers.”
Multiple AI agents orchestrated in a single workflow
The solution is built around three cooperating AI agents, each with a clearly defined role in the process. One agent handles incoming e-mails and attachments, a second extracts and structures data from PDF documents, and a third compares the extracted information against purchase orders in SAP to determine whether there is a match or a deviation.
As a result, complex and unstructured supplier data can be processed in a unified, automated workflow without requiring procurement officers to open and manually review lengthy PDF files.
“What makes this solution robust is the interaction between the agents. Each agent is highly specialized, but they are orchestrated in a way that ensures the process flows seamlessly from start to finish,” Heinemann explains.
Three AI agents working together at Lemvigh‑Müller
Lemvigh‑Müller’s solution is built around three specialized AI agents, each responsible for a clearly defined task within the procurement process. Together, they form a single, end‑to‑end, automated workflow:
1. The e-mail agent receives and sorts incoming e-mails from suppliers. The agent identifies relevant order confirmations and attached documents and routes them to the next step in the process.
2. The data extraction agent extracts key information such as prices, quantities, and delivery dates from PDF documents and structures the data so it can be compared directly with purchase orders in SAP.
3. The matching agent compares the extracted data with existing purchase orders in SAP and determines whether there is a match or a deviation. In case of a match, the process continues automatically, while deviations are flagged for further handling.
During the project, the importance of master data quality also became increasingly clear.
“In areas such as Incoterms and other master data, we identified improvements that need to be addressed. This has been an important learning not just for this initiative, but for our broader work with AI,” he says.
While it is still too early to measure the full impact on customer experience, error rates, or claims, expectations are that faster and more precise handling of supplier confirmations will, over time, lead to fewer surprises and significantly improved delivery transparency. Internally, the solution has been met with strong interest and curiosity among employees.
“Procurement officers clearly recognize the value of being relieved from the most tedious routine work. This has sparked a constructive dialogue about how technology can best support their day‑to‑day responsibilities,” Heinemann says.
The interaction between the three AI agents makes it possible to automate a task that previously required manual review of unstructured documents.
Business AI with a clear business outcome
According to Lemvigh‑Müller, the investment is expected to deliver a return within a relatively short timeframe.
“We are talking about quarters rather than years when it comes to ROI. That is why it was essential for us to get the solution into production quickly and focus on processes with a clear and measurable impact,” Aakerlund says.
For SAP, the project serves as a concrete example of how artificial intelligence can be embedded directly into core business processes rather than remaining a disconnected experiment.
“Many companies talk about AI agents primarily in terms of automation. Lemvigh‑Müller demonstrates that the real challenge—and the real opportunity—lies in coordination,” says David Pontoppidan, head of AI at SAP for the Nordics and Baltics. “It is the orchestration of three specialized agents directly within the core process that makes this solution robust. This is also where many multi‑agent initiatives fail, not due to limitations of individual agents but because of insufficient coordination. Lemvigh‑Müller has succeeded by anchoring the solution in its SAP landscape, where data, business rules, and governance frameworks are already firmly established.”
He continues: “Innovation is not about company size. Lemvigh‑Müller shows that a Danish organization with short decision paths and a pragmatic approach to technology can move faster than many large global enterprises that are still in the planning stage. Ten weeks from idea to production is far from the norm, but perhaps it should be.”
Designed for operations and scalability
The solution was implemented in close collaboration with NTT DATA Business Solutions, which was responsible for making the solution production‑ready and fully integrated into Lemvigh‑Müller’s SAP landscape.
“By distributing responsibilities across multiple AI agents, Lemvigh‑Müller has been able to automate a complex process without losing transparency or control. This has enabled a fast and secure transition from pilot to production and ensures a more robust solution that can easily be expanded as new requirements emerge,” says Kristian Dahl, SAP UX manager at NTT DATA Business Solutions.
According to Dahl, the modular, agent‑based architecture was a key enabler in moving efficiently from proof of concept to live operation.
First step in a broader AI agent strategy
Initially, the AI agents have been deployed for selected supplier inboxes and business areas. However, Lemvigh‑Müller already sees significant potential in applying the same agent‑based approach across additional administrative processes.
“This is the first AI agent solution we have put into production. The experience has given us the confidence to consider similar approaches across other areas, including invoice processing and order management,” Aakerlund concludes.
Ellen Vig Nelausen is a Nordic Integrated Communications Expert at SAP.
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The push for sovereign AI data centers in Europe (and elsewhere) reflects a shift in how IT infrastructure is perceived by enterprise customers, policy makers, and politicians. Because of the growing importance of business AI capability, compute capacity is no longer seen as “just” IT plumbing—it is strategic infrastructure, akin to energy or telecommunications.
AI infrastructure as strategic asset
Although infrastructure ownership is just one element of digital sovereignty strategy, European politicians and policymakers have argued that without domestic data centers, Europe risks dependence on U.S. and Chinese providers for critical AI capabilities.
This concern is echoed by some industry leaders—particularly those in finance and regulated sectors—who increasingly view AI infrastructure as a foundation of economic security. Specifically, they argue that sovereign data centers enable companies to comply with stringent European regulations on data protection and AI governance. They say that locally operated infrastructure ensures that data remains under European jurisdiction, reducing exposure to foreign legal regimes and enhancing trust among customers and regulators.
Security and compliance imperatives
European leaders also frame AI infrastructure as a hedge against geopolitical risk. They argue that dependence on external providers introduces vulnerabilities, whether through legal exposure, supply chain disruptions, or political tensions.
As Christian Klein, CEO of SAP SE, noted at the SAP Sapphire Madrid event last month, many European customers operate in the public sector or other highly regulated industries. “Geopolitical risk is a growing concern,” he said. “What if sanctions suddenly block data flows across borders? Or if the latest LLMs can’t be deployed in certain regions?”
Christine Lagarde, president of the European Central Bank, also highlighted this concern in her November 2025 speech titled “The transformative power of AI: Europe’s moment to act,” noting that Europe must “avoid single points of failure” in critical areas such as data centers and compute capacity.
Proponents of sovereign AI infrastructure also argue that it can stimulate broader economic growth. Data centers often anchor the ecosystems of startups, research institutions, and industrial applications, enabling Europe to capture more value from the AI stack.
From a technical standpoint, proximity also matters. Locally sited data centers reduce latency and improve performance for AI applications, particularly those requiring real-time processing or integration with industrial systems.
But despite these perceived advantages, many European business leaders have urged policymakers to take a more moderate, nuanced approach towards sovereign data. Their concerns are not about the need for data sovereignty itself, but about how it is implemented—particularly the push to rapidly build new, domestically controlled AI data centers. They emphasize that that data residency (location) is only one element of the four standard pillars of a sovereign data strategy, which also include legal sovereignty (jurisdictional control), operational sovereignty (independent operations), and technical sovereignty (data control).
In discussions with policymakers, European business leaders from diverse sectors have been warning that reducing reliance on U.S. technology too quickly is unrealistic. This reflects a structural reality: Europe remains deeply dependent on non-European providers for cloud infrastructure, chips, and AI platforms.
Research from Swiss cloud provider Proton suggests that around 75% of publicly listed European companies rely on U.S. tech services, (primarily Microsoft and Google) for critical infrastructure, including e-mail, cloud, and software. Therefore, attempting rapid substitution risks disrupting operations without delivering viable alternatives.
Barriers and concerns
Even the most ardent proponents of sovereign AI infrastructure acknowledge that there are major practical barriers to building massive AI data centers in Europe, including energy. AI data centers are extremely power-intensive, and Europe already faces grid constraints, high electricity prices, and long permitting timelines.
Without significant investment in energy systems, some European business leaders warn that new data center projects risk delays, cost overruns, or cancellation.
Another concern is that infrastructure-focused, sovereignty-driven policies may distort markets. Critics warn that infrastructure subsidies could flow to less competitive domestic providers resulting in slower innovation and the misallocation of capital resources to politically driven projects rather than economically viable ones.
In this view, sovereignty risks becoming industrial policy for its own sake, rather than a driver of efficiency or innovation. But perhaps the most significant critique is that the focus on infrastructure may distract from a more pressing issue: AI adoption.
Europe has historically lagged in deploying digital technologies. Some business leaders, including SAP’s Klein, argue that the priority should be accelerating AI use across industries and point out that infrastructure alone will not drive productivity gains. Over-emphasis on the infrastructure component of sovereignty could slow deployment through added complexity and cost. As Klein has noted, focusing primarily on infrastructure is a mistake if it is at the expense of developing AI applications and software.
Europe, he said recently, should prioritize “code over concrete.” At the World Economic Forum in Davos earlier this year, senior executives from major European firms, including Capgemini and Ericsson, also warned against an overly protectionist approach. They argued that excluding or limiting global providers would raise prices, slow tech adoption, and reduce competitiveness.
The business view
From a business standpoint, AI is rapidly becoming a general-purpose technology, and the costs of AI infrastructure directly impacts productivity. If European AI infrastructure is more expensive, European companies risk falling behind global peers.
While data residency and the other elements of digital sovereignty are essential for some businesses operating in sensitive and highly regulated sectors, the sovereignty debate in Europe risks oversimplifying a fundamentally global industry. As Henna Virkkunen, the European Commission’s technology chief, noted: “Nobody can be competitive alone.”
Indeed, since AI development depends on globally integrated supply chains, including semiconductors, software, and talent, fully localized infrastructure may be neither feasible nor desirable.
Rather than building duplicative infrastructure to support AI development, Europe’s real competitive advantage may lie in its treasure trove of operational data—a resource that is often difficult to access because of overly restrictive regulation and data access rules, prompting growing calls for reform from business leaders across Europe.
Easing and standardizing data access rules would help European businesses tap into this resource and compete more effectively with international rivals as they move into the next phase of AI enablement—the Autonomous Enterprise.
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The EU’s Carbon Border Adjustment Mechanism (CBAM) is moving beyond a regulatory reporting exercise. From 2026 onwards, emissions embedded in imported goods carry real, measurable cost exposure. To help customers navigate it, SAP is introducing an integrated, end-to-end CBAM solution that starts with CBAM declarants, built on SAP Sustainability Footprint Management and SAP Green Ledger, and will expand to fully support operator needs.
Companies need to quantify those emissions, recognize liabilities, withstand audit scrutiny, and, ultimately, prepare to settle carbon costs through certificates linked to the EU Emissions Trading System.
In practical terms, carbon becomes a priced input, one that directly affects margins, cash flow, and sourcing decisions in a way that is comparable to other cost drivers.
Why CBAM matters now
CBAM cuts across business functions. Finance teams manage liabilities and forecast costs. Procurement teams need emissions data from suppliers and must incorporate it into sourcing decisions. Trade and compliance teams ensure imports are correctly classified and reported.
No single function can manage this in isolation. The financial implications depend on operational data, and operational decisions increasingly depend on carbon cost exposure.
The regulation initially applies to imports of iron and steel, aluminum, cement, fertilizers, hydrogen, and electricity, with a threshold of more than 50 tonnes annually for declarants. While this concentrates formal obligations on larger importers, the effects extend into supply chains as companies request more detailed and verified emissions data from suppliers and adjust sourcing decisions accordingly.
From reporting to financial exposure
What changes in 2026 is not only what companies must report, but what follows from it. Imports of CBAM-covered goods into the EU create a carbon liability for authorized declarants based on their verified embedded emissions. Those liabilities accumulate throughout the year and must be reported, audited, and settled through the purchase and surrender of CBAM certificates in 2027.
This creates an ongoing compliance cycle with clear financial implications:
Emissions must be tracked and translated into certificate requirements.
Liabilities accumulate throughout the year.
Certificates must be purchased, managed, and surrendered to cover those liabilities.
For finance, this means ongoing exposure that needs active management. For procurement and supply chain teams, costs now hinge on supplier emissions data.
An integrated approach to CBAM
Decarbonize your value chain with carbon accounting software from SAP
Many organizations are currently managing CBAM across multiple systems, spreadsheets, and manual processes. That approach becomes difficult to sustain under audit and as volumes increase.
SAP’s approach brings together the key elements of CBAM management into a connected process: data collection and mapping, emissions and cost calculation, analytics, carbon and financial accounting of liabilities, certificate asset management, and declaration generation.
This new approach allows companies to move away from fragmented workflows toward an integrated solution tied to core business processes.
Coming soon: End-to-end CBAM data capture and calculation with SAP Sustainability Footprint Management
SAP Sustainability Footprint Management will provide the operational backbone for CBAM by helping to establish a reliable data foundation. At its core will be customs data, such as import records and CN code classification, sourced from SAP Global Trade Services and other trade systems. Without that layer, companies struggle to identify where CBAM applies.
Building on this foundation, SAP Sustainability Footprint Management will help centralize CBAM-relevant ERP, trade, and supplier data in one place; ingest supplier emissions data via Excel uploads with automated interpretation; and calculate embedded emissions, certificate requirements, and estimated CBAM costs. A dedicated CBAM dashboard will allow organizations to analyze emissions and cost exposure, while built-in reporting capabilities support the generation of CBAM reports ready for submission to EU authorities.
Available today: Financial control of CBAM exposure with SAP Green Ledger
A critical differentiator in CBAM readiness is the ability to connect carbon data with financial processes. Today, with SAP Green Ledger, companies can track the number of certificates required, valuate them as financial liabilities, continually revaluate based on price changes, and post financial impacts to the appropriate accounts. This is the level of traceability finance teams and auditors expect, in line with the International Accounting Standards.
This integration enables organizations to:
Recognize, valuate, and periodically revaluate CBAM liabilities.
Track certificate holdings and their valuation (coming soon).
Support audit-ready reporting and verification.
Forecast and plan for cash impacts (coming soon).
Break down and manage costs on a product level (coming soon).
Most organizations still treat operational data and financial impact as separate. These capabilities can bring them together.
Beyond compliance: enabling better decisions
While CBAM is often framed as a compliance burden, it also provides an opportunity to improve decision-making. When carbon costs are visible and integrated into business processes, companies can see exactly where exposure sits and where action will make the biggest impact.
With better data, organizations can:
Identify high-cost emission hotspots in their supply chains.
Evaluate supplier choices based on emissions and cost trade-offs.
Improve forecasting and budgeting of carbon-related costs.
Reduce reliance on conservative and costly default values by using actual data.
This does not remove the cost, but it can make it easier to manage and, in some cases, reduce.
What to focus on now
As CBAM has entered its definitive phase, the immediate priority is building a reliable data foundation. That includes accurate customs data and clear mapping of where CBAM applies. Supplier engagement is another practical constraint. Collecting verified emissions data often requires structured outreach and follow-up. Tools such as SAP Sustainability Data Exchange can support with supplier communication and data collection, but the effort remains organizational as much as technical.
From there, organizations can assess their CBAM exposure, ensure the necessary data flows are in place, and plan their solution architecture to optimize total cost of ownership, automation, and integration into business functions. It continues with ensuring that emissions calculations are traceable and auditable. That influences behavior; carbon now drives planning, which no team can ignore.
At the same time, companies need to define how CBAM data flows into finance. Linking emissions, liabilities and certificates to financial systems early helps avoid rework and reduces audit risk.
What’s next
CBAM is a broader shift in how environmental impact is reflected in business performance. Carbon is tracked, priced, and managed alongside other cost drivers.
Organizations that treat CBAM as a periodic reporting task will likely remain reactive. Those that integrate it into financial and operational decision-making will be better position to manage its impact.
Customers expect brands to know them, anticipate their needs, and engage them with relevance across every channel and touchpoint. The challenge isn’t agreeing on the vision. The challenge is closing the gap between that vision and systematic, scalable execution.
For many SAP Commerce Cloud and SAP Engagement Cloud customers, this gap shows up in familiar ways: recommendation engines that surface generic results because behavioral data is not connected, e-mail campaigns timed by calendar rather than by individual habit, loyalty programs that reward transactions rather than relationships, and personalization rules that require significant manual effort to maintain at scale.
The ambition is there; the infrastructure to fulfill it, however, is often partial. Clean data is siloed, AI capabilities are underutilized, and the organizational discipline to run ongoing experimentation does not yet exist.
True hyper-personalization is not a feature you switch on. It is a capability you build systematically across three interdependent layers: data, decisioning, and delivery.
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Data is the foundation. Hyper-personalization requires unified, consent-aware, real-time customer profiles consolidated across commerce transactions, engagement history, browsing behavior, service interactions, and loyalty activity. Without this foundation, even the most sophisticated AI models are operating on incomplete signals.
Decisioning is where AI translates those signals into action—the next best product to surface, the right offer to present, or the optimal moment to reach out. This layer requires not just model accuracy but governance, knowing when to trust the algorithm and when human judgment should override it.
Delivery is where the personalized experience reaches the customer, at the storefront, in the inbox, through a mobile push, or across a loyalty interaction. This layer requires orchestration across channels, consistent with the customer’s current context.
The Advanced Success Plan for SAP Customer Experience solutions helps address all three layers simultaneously, providing the expert guidance, governance frameworks, and adoption acceleration needed to move from point capabilities to an integrated operating model.
Hyper-personalization in SAP Commerce Cloud
SAP Commerce Cloud can provide the storefront execution layer for personalization at scale. The solution’s AI-assisted product recommendations capability enables organizations to show the most relevant products to each visitor at the right point in their shopping journey, from trending products and related items to complimentary products that support cross-sell and upsell motions. This can go beyond manual merchandising rules; it can respond dynamically to real-time behavioral signals, helping to improve conversion performance and drive product discovery at a scale no merchandising team could replicate manually.
Yet many SAP Commerce Cloud customers have not yet activated the full depth of these capabilities. The blockers are predictable: data quality gaps that limit recommendation model performance, integration complexity between the commerce layer and upstream profile data, and an absence of the experimentation discipline needed to tune and improve models over time.
The Advanced Success Plan for SAP Customer Experience solutions can bring targeted guidance to help address these barriers. Data readiness assessments can establish the quality baselines and integration patterns required to feed reliable signals into SAP Commerce Cloud’s personalization engine. Adoption accelerators help teams operationalize experimentation, defining hypotheses, running A/B tests, and translating results into durable configuration changes. The outcome is a storefront that can continuously learn and improve, rather than one frozen at the point of initial configuration.
Hyper-personalization in SAP Engagement Cloud
SAP Engagement Cloud, powered by SAP Emarsys, can extend personalization beyond the storefront and into the full lifecycle of the customer relationship. This is where SAP Commerce Cloud’s transactional signals combine with engagement history to help power cross-channel personalization that is individual rather than segment-based.
The solution’s AI-assisted send time optimization capability is a direct example of this philosophy in practice. Rather than sending campaigns on a fixed schedule, the capability can analyze each contact’s behavioral patterns—independently of time zone, language, or region—and deliver messages at the precise time each individual is most likely to engage. This is not personalization as a concept; it is personalization as an automated, scalable operational process.
Paired with the SAP Emarsys, AI-assisted campaign translator capability and omnichannel orchestration, SAP Engagement Cloud enables marketing teams to move from building campaigns to orchestrating journeys where the system is continuously learning which signals should trigger which interactions and adapting those interactions based on what drives response.
The native integration between SAP Commerce Cloud and SAP Engagement Cloud is a critical accelerator here. By unifying commerce behavior and engagement data, organizations can drive increases in conversion rate, purchase frequency, and average order value in ways that neither system could achieve independently. The Advanced Success Plan for SAP Customer Experience solutions helps customers realize this joint value by aligning integration architecture, data governance, and adoption milestones across both products within a single, coordinated engagement model.
How the Advanced Success Plan enables continuous improvement
Hyper-personalization projects are often treated as one-time implementations. The Advanced Success Plan for SAP Customer Experience solutions is designed to make them repeatable, continuously improving programs. This means:
Outcome-based governance: Co-defining the KPIs that matter, such as conversion rate lift, repeat purchase rate, engagement open rates, and average order value, and building work streams aligned to move them measurably.
Prescriptive adoption patterns: Structured playbooks for activating AI-assisted recommendations, send time optimization, and next-best action logic, with clear milestones and measurable gates.
Continuous enablement: Role-based coaching for the teams responsible for data, product ownership, and campaign operations, closing skills gaps that otherwise cause personalization programs to plateau or regress.
Proactive telemetry: Regular adoption checks that surface underperforming configurations before they impact business outcomes, and AI-guided best practices that inform ongoing tuning.
Making the business case concrete
For SAP Commerce Cloud customers, the value of operationalized hyper-personalization can be seen in storefront metrics: higher conversion from AI-surfaced recommendations, increased average order value through intelligent cross-sell, and improved product discovery that reduces bounce and exit rates.
For SAP Engagement Cloud customers, the value can be seen in engagement quality: open rates and click-through rates that reflect individual relevance rather than list-wide broadcast, improved campaign ROI through AI-optimized delivery, and loyalty program engagement that reflects relationship depth rather than transaction volume.
Across both, the compounding effect of unified data and orchestrated decisioning is what transforms hyper-personalization from a POC into a sustained growth mechanism, one that gets measurably better over time.
Payal Sachdev is product manager for the Advanced Success Plan for SAP Customer Experience. Tara Tracey is global product owner for the Advanced Success Plan for SAP Customer Experience.
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As cost pressures intensify, procurement leaders must find new ways to deliver savings, manage risk, and accelerate transformation.
Over the past several years, procurement has steadily expanded its influence inside the enterprise. As supply chains faced unprecedented disruption, procurement leaders became trusted advisors to the C-suite on resilience, risk management, and sustainability. Their visibility increased and so did the expectations placed upon them.
Now, the playbook is being rewritten once again.
Research from the 2026 Economist Enterprise Report titled Procurement at a crossroads: from optimism to realism, sponsored by SAP, finds that financial performance has reemerged as the primary benchmark of procurement’s success. Drawing on a global survey of 2,648 C-suite executives, the report found that 54% cite cost control as procurement’s greatest contribution to the business, up from 43% just one year earlier. The findings point to a function that is increasingly stretched, yet positioned to deliver measurable business outcomes—if it can navigate a difficult balancing act.
Cost control returns to center stage
The shift is not surprising given the environment. Persistent inflation, tariff uncertainty, and continued investment in supply chain resilience have pushed cost management back to the top of the executive agenda. At the same time, companies are investing in dual sourcing, nearshoring, and inventory buffering to reduce exposure—strategies that strengthen resilience but often raise costs. Procurement is expected to offset those increases elsewhere.
Cost savings can be sustainable with AI-powered and integrated sourcing, contracting, and supplier management applications
What makes this moment particularly challenging is that procurement’s broader responsibilities have not diminished. Teams are still expected to manage geopolitical risk, advance sustainability, and support digital transformation. The mandate has expanded significantly, often without a corresponding increase in capacity, tools, or operating model support. Delivering savings, limiting cost increases, and managing input costs while fulfilling a growing strategic role is the defining tension facing procurement leaders today.
AI is becoming procurement’s digital imperative
Technology, and AI in particular, is increasingly seen as the key to resolving tension. In the Economist Enterprise study, 60% of executives identified digital transformation as procurement’s top strategic priority over the next 12 to 18 months, up sharply from 38% in 2025. More than half (56%) identified AI as the primary driver of that transformation.
The emergence of agentic AI is accelerating expectations further. More than half of executives are planning to implement or evaluate agentic AI capabilities within the next 12 to 18 months. Unlike earlier generations of AI that focused primarily on generating insights, agentic AI introduces the ability to execute workflows—from guided buying experiences to automated purchase order creation—enabling procurement to move beyond recommendations and drive actions.
Even so, executive expectations remain grounded. Only 9% of survey respondents want AI to lead most procurement decisions within three years. Procurement’s highest-value work continues to rely on human judgment, strong supplier relationships, and the ability to navigate complex trade-offs. AI plays a critical role in strengthening these capabilities, but it does not replace them.
Realizing that potential, however, requires the right foundation. Connected data, clear governance, and close collaboration across procurement, finance, IT, and operations are prerequisites for generating AI outputs that are reliable and accountable.
Category management takes on greater importance
As procurement balances cost pressures with broader business priorities, category management is emerging as a critical discipline. The report found that category and demand management are expected to receive the second highest level of digital investment among procurement disciplines over the next three years, trailing only spend and performance analytics.
This reflects the growing complexity of procurement decisions. Category leaders are no longer simply awarding projects to the lowest-cost supplier. They are expected to weigh cost, risk, sustainability, and supplier performance simultaneously—a level of complexity that demands better analytics and faster insight-to-action capabilities.
That level of nuance can strengthen procurement’s impact, but it can also slow execution. More sophisticated category strategies require better data, sharper analytics, and faster insight-to-action capabilities. The report found that category strategy has become the third most common source of process delays, behind only contracting and sourcing.
Success increasingly depends not on collecting more data, but on turning data into confident decisions quickly. Organizations that close that gap will be better positioned to execute strategy, not simply develop it.
Procurement’s strategic value is being tested
Perhaps the most striking finding in the report is a growing confidence gap. While nearly three-quarters of executives still believe procurement collaborates effectively across the organization, that figure dropped from 90% in 2025 to 74% in 2026. Confidence in procurement’s role in shaping digital transformation strategy also declined meaningfully over the same period.
These numbers do not signal a retreat from procurement’s strategic importance. Rather, they reflect a broader shift in how enterprise decisions are being evaluated. As AI democratizes access to data across the organization, more stakeholders have the information to question decisions and demand clearer evidence of value.
Procurement leaders are now expected to control costs, manage risk, strengthen resilience, and help guide AI adoption, often simultaneously and without additional resources. The question is no longer whether procurement belongs at the leadership table. It is whether procurement can consistently deliver the value expected of it across an expanding and increasingly complex set of priorities.
Procurement’s next chapter
The Economist Enterprise findings paint a picture of a function at a pivotal moment. Cost savings has returned as the primary mandate, yet procurement is still expected to manage risk, protect supply continuity, and lead digital transformation.
Meeting those expectations will require more than layering AI onto existing processes. It demands connected data foundations that make AI outputs trustworthy, visibility across suppliers and spending, and technology that enables teams to move from reactive decision-making to proactive intervention.
The leaders who will define procurement’s next chapter are those who can turn AI, data, and connected processes into faster decisions, stronger resilience, and measurable business impact.
To learn more, join the upcoming Economist Enterprise–hosted webinar, “Leading the firm: The future of procurement,” on June 25, 2026, which will explore how leaders can accelerate AI adoption, prove digital value, and strengthen supply chain resilience.
Gordon Donovan is vice president of Research for Procurement and External Workforce at SAP.
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The SAP Experience Center brought the “new SAP” to life at SAP Sapphire. It guided visitors through the story of a major sporting event—from early planning to game day—and ended with a special souvenir.
Andreas Wendel is very pleased with the outcome: a total of 11,200 visitors explored the SAP Experience Center at SAP Sapphire Orlando and Madrid. The self-contained exhibit drew customers, partners, SAP employees, media representatives, and analysts alike. Across the two identical centers, visitors also joined 123 guided tours.
“The rush of visitors was so great that, in Orlando, the line at times wrapped all the way around the center, which covers roughly 1,000 square meters,” says Wendel, head of Innovation Experience Services at SAP.
Get an impression of the SAP Experience Center at this year’s SAP Sapphire
So what was inside the oversized box in the middle of the show floor? What were visitors willing to wait more than an hour to experience?
Sports create an emotional connection
“This year, our task was to bring the Autonomous Enterprise to life,” Wendel says. “It’s a highly technical topic, and we talk a lot about artificial intelligence, agents, and Joule Assistants.” The team wanted to make tangible what CEO Christian Klein and other members of the Executive Board of SAP SE introduced in the keynote and what was demonstrated in sessions.
Planning began six months before SAP Sapphire, supported by experts from Strategy, Development, and Product Marketing. Over time, more partners, customers, and service providers joined the effort. Wendel estimates that close to 100 people contributed to the concept.
As the narrative thread, the team chose a major sporting event and the theme “From Competition to Collaboration”—a timely fit with the world’s largest soccer tournament taking place across the United States, Mexico, and Canada this year. “With so many technology discussions at SAP Sapphire, sports is a topic that resonates with people emotionally,” Wendel says. “We used a sports event to show how SAP solutions help plan and deliver an event of that scale.”
“For spectators, it’s an experience. But for a mega-event to run smoothly, all equipment and technologies around a stadium must work,” he adds. “We showed how Autonomous Asset Management helps ensure the infrastructure performs on the day of the event.”
A players’ tunnel, pipelines, and a robodog
Let’s take a tour of the SAP Experience Center with Wendel. We enter through a players’ tunnel and arrive in a skybox overlooking an imagined stadium for a major international soccer tournament. The first stop, “Plan the Game,” focuses on the big picture and shows how SAP brings AI, data, and applications together to orchestrate every aspect of a major sporting event.
Wendel explains how SAP solutions support the planning phase: “We show how customers can use our finance and planning solutions well ahead of the event. Agents and Joule Assistants help identify developments early and take action to stay within budget.”
His colleague Pranav Avadhanula, solution advisor for Finance and AI, demonstrates this with a real-world scenario. On a large screen, visitors see how Joule Agents can identify the best providers for the event’s security concept in Mexico and simulate different scenarios—including currency fluctuations between the Mexican peso and the U.S. dollar.
The next station, “Build the Stage,” highlights the work that happens behind the scenes before fans cheer. Modernizing a stadium requires precise planning, budget discipline, and seamless execution. SAP helps orchestrate everything—from staffing and travel to procurement—enabling the venue to be ready on time and on budget, supported by Autonomous Spend, Autonomous HCM, and Autonomous Project Delivery.
Another room focuses on applications that are invisible to visitors—but critical. One scenario in particular stands out and was likely the most frequently filmed by visitors: a dog-shaped robot from partner Boston Dynamics moving along a series of pipelines, automatically detecting leaks with sensors. Once identified and analyzed, the system triggers a digital repair order for the maintenance staff responsible.
“What resonates strongly is that we don’t just show digital solutions,” Wendel says. “We also demonstrate how embodied AI and robotics can support operations in the future—ideally through customer use cases. These physical elements make SAP solutions tangible and help reduce complexity.”
Another popular highlight is the “Hall of Fame,” where key customers are honored with their own trophies. “In Orlando, we had a tour with a customer. When employees saw their trophy, they cheered and took photos like at a Champions League final. That really showed how much detail went into the experience—it was simply incredible.”
More than just a jersey
The visit concludes in the fan shop. Under the theme “Monetize the Moment,” it demonstrates how organizers can generate revenue through merchandise. Visitors scan their SAP Sapphire badge and order a personalized jersey in one of two colors.
They then watch as a machine printed the jerseys with their chosen name and number. A humanoid robot from partner Aimbo Robotics sorts the finished items onto shelves. Despite high demand, jerseys are ready for pickup about two hours later.
The twist: the jerseys include an NFC chip. “If you tap your phone to it, you can access all SAP Experience Center content again,” Wendel explains. “So it’s not just a jersey—it extends the experience beyond the event.”
Wendel emphasizes that while the SAP Experience Center was built for SAP Sapphire, its elements are reused at other events or in one of the numerous permanent SAP Experience Centers. Parts of the setup are also stored for reuse. “Sustainability is very important to us,” he says.
Hard to top
The many months of preparation and the long evenings in the exhibition hall in the run-up to SAP Sapphire clearly paid off. Asked about the feedback, Wendel concludes: “Our concept makes SAP’s full portfolio and industry strength tangible. This year, many people told us: ‘Last year was already great, but you managed to top it.’ And that’s not easy.”
Experience SAP innovation firsthand
SAP Experience Centers bring innovation to life through real business scenarios, interactive showcases, and industry-specific storytelling. Across 31 locations worldwide, SAP connects applications, data, and AI to help turn complex business challenges into tangible solutions.
At a recent gathering of SAP innovators, a powerful message emerged from one of the world’s aerospace leaders: the sky is not the limit anymore, but space itself. Innovation is not a destination; it’s an endless journey.
Few companies embody that philosophy better than Airbus.
Innovation is not a department
Simplify complex operations, manage risk, and meet customer demand with SAP
“We are living at a remarkable crossroads in history. For decades, the sky was simply a place we traveled through. Today, it has become a testing ground for the future of humanity,” said Nicolas Jourdan, senior strategist at Airbus SAS. He was speaking at the TAC Insights conference for SAP Energy and Utilities in Toulouse, the operational headquarters of the company.
At Airbus, the mission goes far beyond manufacturing aircraft. It’s about designing systems that connect cultures, advance technology, protect the planet, and extend humanity’s reach into space.
“For us, innovation is not a department. It’s a way of thinking. It means asking ‘What if?’ when others say something is impossible,” said Jourdan. “It’s very simple. Innovation is about creating value for someone, somewhere, at a moment in time—and sustaining it over time.”
While this may sound simple, it requires challenging the status quo. It means embracing cultural change, taking calculated risks, and accepting failure as part of learning.
Legacy of breakthroughs
In 1970, Airbus entered an aviation market dominated by giants like Boeing, McDonnell Douglas, and Lockheed. They didn’t compete by being similar, but by being fundamentally different. The company has consistently challenged conventional thinking in aviation.
At a time when experts believed twin-engine aircraft couldn’t safely cross oceans, Airbus proved them wrong with the A300 revolution, forever changing long-haul aviation.
When most aircraft required a three-person crew, Airbus redesigned the cockpit to automate the flight engineer’s role. Despite resistance, the two-pilot cockpit became the global standard.
Replacing analog dials with digital displays transformed how pilots interact with aircraft; glass cockpit innovation made flying safer and more intuitive.
Airbus introduced digital flight controls, replacing mechanical systems with computers. Fly-by-wire technology increased safety and enabled flight envelope protection and more efficient operations. What once looked like a video game controller is now industry standard.
One of Airbus’s most impactful innovations is cross-crew qualification, meaning pilots can transition between aircraft models—from the A319 to the A350—with minimal additional training. This reduces costs for airlines and improves operational flexibility.
“Innovation isn’t always flashy. It’s mostly about making complex systems simpler and more human-friendly,” Jourdan reminded his audience.
Running the factory
Airbus builds big sections such as the fuselage, the wings, and the tail in different places. The sections are then shipped to one factory for assembly and testing in the Airbus Beluga, an oversized cargo aircraft developed especially to transport large components between production sites across Europe. Altogether, this process can take up to 12 months, especially for wide body aircraft.
The company uses SAP ERP systems, including SAP S/4HANA, to manage core business functions. It also uses SAP Manufacturing Execution directly on the factory floor and assembly lines, as well as SAP Integrated Business Planning to plan production, manage supply chain complexity, and optimize resource usage.
“SAP and Airbus have a long-term partnership,” Jourdan said. “Without SAP, our systems would not be as efficient as they are. We’re in continuous development.”
Future scenarios
When it comes to pioneering new horizons, Airbus doesn’t rely solely on internal expertise but regularly explores unconventional approaches with external thinkers. These exercises help identify blind spots, validate strategy and understand societal and environmental shifts
To maintain both an inside and an outside-in perspective, Airbus created Skywise, an aircraft data analysis engine platform which acts as a digital brain, connecting aircraft, operations, and maintenance systems. A data platform for airlines and aircraft operations, it collects vast amounts of data into one system. It then performs predictive maintenance increasingly supported by AI to detect patterns and predict failures before they happen in order to prevent delays, failures, and expensive repairs.
Airbus’s future strategy is built on three transformational pillars:
Decarbonization: The aerospace industry faces mounting pressure to reduce emissions. Airbus is tackling this head-on by exploring hydrogen-powered aircraft, sustainable aviation fuels, blended wing body designs, and fully electric propulsion concepts. Their goal is to launch the world’s first zero-emission commercial aircraft.
Digital transformation: To enable fully connected ecosystems, Airbus is developing satellite-based connectivity networks, smart cabin and cargo systems,. and real-time operational data platforms. This enables better decision-making, reduced costs, and improved passenger experiences.
Automation and autonomy projects: Projects like DragonFly are pushing the boundaries of pilot assistance and automation. Future capabilities include automatic emergency landing, weather-independent operations, and advanced navigation systems. The goal is not to replace pilots, but to enhance safety and efficiency.
Beyond Earth
From orbit to deep space, Airbus is helping shape humanity’s next frontier. The company plays a key role in searching for life on Mars together with the European Space Agency using the ExoMars rover. It also collaborates with the European Service Module for NASA’s Artemis program missions and is helping to develop satellite systems enabling global communication and climate monitoring.
Often, new ideas are met with skepticism, cultural resistance can slow adoption, and mistakes are inevitable. Airbus embraces this reality and considers it part of the process.
“The biggest challenges of our time—climate change, global connectivity, and space exploration—cannot be solved by one company or even one industry. Decarbonization alone depends on energy providers, governments, infrastructure developers, and airlines and manufacturers. It’s a shared responsibility,” Jourdan concluded.
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Enterprise software marketplaces have fundamentally changed how software gets bought and sold. What used to require months of vendor outreach, in-person meetings, and parallel e-mail negotiations can now start—and often end—inside a single platform.
Discover, try, and buy solutions from SAP and partners
But here’s where the marketplace model runs into its limits: most enterprise deals aren’t straightforward enough for a standard checkout button.
Negotiated pricing. Custom contract terms. Procurement reviews. Regional tax requirements. Bank transfer requirements. Delayed start dates. Sixty-nine percent of B2B buyers would complete transactions of $500,000 or more without in-person interaction, but those same high-value deals involve complex approval workflows, payment terms, and stakeholder sign-offs that a flat “Buy Now” experience simply can’t handle. When a deal doesn’t fit the standard flow, it typically gets pushed outside the platform entirely—back into e-mail threads, separate negotiations, and disconnected systems that no one has full visibility into.
That’s the problem private offers on SAP Store help solve.
Instead of forcing complex deals out of the platform, customers can request a private offer directly through SAP Store, negotiate terms with the partner, and close the transaction inside the same environment where they found the solution. The deal stays connected, trackable, and consistent—from discovery to signature.
When talking about travel and transportation, there is only one thing a business should focus on: the end-to-end customer journey. Excellence in experience is what to strive for from the very first point of interaction to the destination.
Travelers nowadays have very strict requirements. From booking a ticket to arriving at a destination, they expect fast, convenient, and prompt assistance when they face issues along the way. No matter how perfectly a system is designed to meet needs, there will always be situations that can’t be avoided. Delays, confusing booking systems, long customer service wait times, and much more create frustration for travelers.
AI is reshaping how the travel and transportation industry is doing business. It delivers more avenues to provide customer care aside from the typical communication channels such as e-mail, short messaging services, and social media. AI provides smarter, faster, and more personalized customer experiences, leading to happier customers and therefore growth in revenue for the business. AI is no longer optional, it is now becoming a necessity.
Get an analyst’s perspective on the business impact of success plans from SAP Services and Support
Beyond tickets and timetables: how AI orchestrates the customer journey
Previously, travelers preferred travel agents over booking apps, relied on printed tickets, and valued personal service and human interaction. However, mobile apps for bookings, check-ins, and payments are now widely used. Travelers also expect real-time updates and personalized recommendations that provide seamless, end-to-end experiences.
SAP delivers an ecosystem that can provide the tools needed to meet these expectations. Using SAP Service Cloud, organizations can manage cases, complaints, and information requests efficiently. AI can respond within seconds, unlike traditional customer service processes that rely on manual handling of support tickets. AI-powered chatbots can also manage a high volume of customer conversations simultaneously. Here is an example integration strategy:
Intelligent selling services for SAP Commerce Cloud
Intelligent selling services for SAP Commerce Cloud are AI-powered services that leverage machine learning and artificial intelligence to help deliver personalized customer experiences and optimize booking strategies. These services help analyze customer booking patterns, provide contextual data across customer touchpoints, and offer recommendations that can lead to increases in revenue.
Travel accelerator
The travel accelerator for the SAP Commerce solution is an industry-specific solution designed to enable travel companies to deliver omnichannel digital traveler engagement through SAP Commerce Cloud. For customers that already have an existing SAP Commerce Cloud solution, they can use the travel accelerator to help tailor it for travel business demand. It can provide real-time information to offer personalized customer experiences and reinforce customer loyalty.
Loyalty management program through integration
Organizations may need a system to reward customers for coming back, like earning points, perks, or special treatment when you repeatedly book with the same travel company. For this, an integration to a loyalty management program, either SAP Customer Loyalty Management or a third-party solution, can be used.
The way forward
The Advanced Success Plan version for SAP Customer Experience solutions can help you achieve your business goals. As a starting point, we can create a service engagement plan that provides a tailored approach to meeting your KPIs. During this phase, we also deliver sessions to help you set up SAP Sales Cloud, SAP Service Cloud, and SAP Commerce Cloud while working to ensure that travel and transportation industry best practices are followed.
With AI capabilities available across every solution, you can now categorize your customer base based on travel behaviors and patterns, as well as perform sentiment analysis on customer reviews and support tickets. The Advanced Success Plan can serve as a strategic partner in helping achieve AI objectives. Our experts, backed by deep industry knowledge, can provide guidance on the most effective path forward.
To deliver services that are aligned with each customer’s specific goals, we have organized our offerings into four phases: implementation, pre-go-live, post-go-live, and continuous improvement.
Implementation
During the implementation phase, our focus is on providing adoption guidance to help set up the solutions, from front-end applications to back-end systems. We work alongside the team to establish core capabilities needed for a successful implementation and to help ensure the solution is aligned with business requirements.
This includes, but is not limited to, application user management, key user extensibility, the SAP CX AI Toolkit, integrations, security considerations, and other essential platform capabilities. Our goal is to help build a solid foundation that supports scalability, maintainability, and future growth while enabling teams to get the most value from the platform.
Pre-go-live
In the pre-go-live phase, our focus is to validate and safeguard the solutions that have been built throughout the implementation. The goal is to make sure systems are configured correctly, performing as expected, and ready at go-live.
This includes conducting detailed reviews of business configuration settings, evaluating system performance, validating integrations, reviewing security and user access setups, and assessing analytics and reporting capabilities. We also help identify potential risks, gaps, or areas for optimization before launch, working to ensure issues are addressed proactively.
In addition, we work with teams to confirm readiness across key functional and technical areas, helping ensure that testing has been completed successfully, critical business scenarios have been validated, and the solution is aligned with operational requirements. Performing an adoption checkpoint during this phase helps reduce risk, improve system stability, and support a smoother go-live experience.
Post-go-live
During the post-go-live phase, we work closely with the team to help ensure that recommendations and best practices identified throughout the implementation have been properly configured and are delivering the intended results.
As users begin working in the production environment, new questions, opportunities for optimization, and minor challenges often emerge. During this stage, we provide continued guidance and support to help address those items, whether they are related to business processes, system configuration, integrations, extensibility, analytics, or overall solution adoption.
Our functional and technical experts remain available to review issues, provide recommendations, and help navigate any areas that require additional attention. We also help identify opportunities for further improvements and knowledge transfer, working to ensure the organization is well-positioned to maintain, enhance, and scale the solution over time.
Continuous improvement
Finally, as part of the continuous improvement phase, we help stakeholders remain informed about new innovations and enhancements introduced through SAP release cycles. By staying up-to-date with the latest capabilities, the team can continue to maximize the value of the solutions and drive ongoing business success.
Tara Tracey is global product owner of the Advanced Success Plan at SAP. Geoffrey Arado is product manager for SAP Customer Experience.
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