The goal is clear for Royal Greenland and its more than 40 plants and factories along the coast of Greenland and Atlantic Canada: a more standardized, cloud‑based landscape with significantly lower complexity, and a technological foundation that can support future AI initiatives.

Headquartered in Nuuk and 100% owned by the Government of Greenland, Royal Greenland is modernizing its SAP platform and moving from on premise to cloud ERP in order to future‑proof core processes and unlock embedded AI across its SAP business applications.

“We are moving from our existing setup to SAP Cloud ERP and SAP Business Data Cloud because we want access to the capabilities you can consume on a cloud platform,” said Lars Bo Hassinggaard, CIO at Royal Greenland for more than 25 years.

The company brings high‑quality wild‑caught fish and shellfish from the North Atlantic and Arctic Ocean to consumers worldwide. It has been running SAP since 1998 but is now embarking on its most significant transition to date: migrating SAP ERP Central Component to SAP Cloud ERP while simultaneously elevating its business intelligence (BI) landscape into SAP Business Data Cloud and later transforming BI into SAP Datasphere.

The project follows the structured RISE with SAP framework, which consolidates platform transformation, operations, and the innovation cycle into one contract.

Lean, selective data transition: 90% fewer data to move

As part of the migration, Royal Greenland is reducing its data volume significantly using the “Lean Selective Data Transition” method.

“We are keeping 10 years of data and cleaning up, so we avoid outdated company codes and historical data that no longer create value,” Hassinggaard explained. “We’ve achieved a 90% reduction in what needs to be stored and migrated. The method combines data analysis, scoping, and standardized mapping objects in a guided process, ensuring that Royal Greenland only carries forward what is truly necessary, making the financials of the transformation more predictable and avoiding unnecessary complexity.”

Technology first, innovation next

Go‑live is planned for March 1, 2027. The year 2026 is dedicated to the platform lift itself. From 2027, Royal Greenland will begin building business‑driven improvements on top of the standardized core—for example, new user interfaces and process optimization using small AI agents within finance and administration.

“Royal Greenland and SAP have worked together since 1998, and we look forward to getting started on the technical part of the platform uplift this January,” Hassinggaard shared. “We’re keeping the transformation as simple as possible for now and will use 2027 to activate the benefits, such as improved data analysis, better user experience, and more efficient work processes.”

Royal Greenland is following a classic waterfall approach and has already established a “golden shell” as the basis for further configuration and retrofitting.

SAP is responsible for implementing the cloud solution, which will run on Microsoft Azure, initially in Sweden, with the option to move later to a Danish data center. External advisor Spektra Analytics has supported contract validation.

From in‑house experiments to standardized, “consumed” AI

Although Royal Greenland has already successfully experimented with its own AI solutions, including vision‑based projects in production, the strategic direction ahead is to leverage embedded, standardized AI data products from SAP and models built on the SAP Business Data Cloud and its semantic data layer.

“We are a company that prefers to tap into existing AI solutions rather than invent them ourselves,” Hassinggaard said. “It’s far more efficient for us. There is no reason for us to spend resources reinventing what SAP already provides. The initial focus will be on process optimization within administrative functions such as finance—small AI agents that can streamline daily work.”

Advice to others: Allocate more time, and understand your method

Hassinggaard is clear that the RISE with SAP contract, methodology, and preparation work require time and organizational maturity. His advice to other companies facing a similar cloud ERP decision: “Do it thoroughly—and allocate more time than you think. Study the methodology, pricing, and contracts. And bring a competent advisor on board.”

Ellen Vig Nelausen is an integrated communications expert for SAP Regional Communications.

The automotive industry has always been a bellwether for technological change. From mass production to lean manufacturing, from embedded software to connected vehicles, each wave of innovation has reshaped not just cars but entire ecosystems. Today, artificial intelligence is doing the same—quietly, decisively, and at scale. While much of the public conversation around AI in automotive focuses on autonomous driving or in-car experiences, the real transformation is unfolding behind the scenes, in how vehicles are designed, launched, serviced, and sustained over their lifecycle.

According to industry estimates, auto executives expect AI to boost product value by 22% and digital service value by 37% within three years. As vehicle portfolios expand—electric, hybrid, software-defined, and increasingly customized—the operational complexity for automakers and suppliers has risen sharply. Nowhere is this more evident than in service parts management and new product introduction (NPI).

Service parts planners sit at the intersection of engineering, supply chain, manufacturing, and customer service. Their task is deceptively simple: ensure the right parts are available at the right time and place across a vehicle’s lifecycle. In reality, they grapple with fragmented data, limited inventory visibility, unpredictable demand signals, and compressed timelines—especially as new models and components are introduced at unprecedented speed. High data quality, tight orchestration across systems, and rapid decision-making are no longer nice to have, they are business-critical.

This is where customer-specific AI becomes transformative. Instead of treating NPI as a linear, manual, and reactive process, AI agents can fundamentally reimagine how service parts planning is executed. By embedding AI directly into the planning workflow, service parts planners are supported—not replaced—by intelligent systems that operate with full contextual awareness. These AI agents can monitor real-time data across inventories, supplier readiness, historical demand patterns, external risk factors, and engineering changes, as well as orchestrate the NPI process end to end.

In practice, this means planners move from firefighting to foresight. AI agents can automate sequential NPI steps, flag potential bottlenecks before they materialize, and dynamically adjust plans as conditions change. A single, unified dashboard provides transparency across the entire process, while built-in what-if simulations allow planners to test scenarios—supplier delays, demand spikes, geopolitical disruptions—before decisions are locked in. Crucially, humans remain firmly in control. AI augments judgment, improves speed, and enhances confidence, rather than operating in a silo.

Platforms like SAP Business Technology Platform (SAP BTP), combined with Joule and the agent builder capability in Joule Studio, can enable this multi-agent approach at enterprise scale. By integrating AI seamlessly with core business processes, automakers can ensure that intelligence flows across functions, rather than being trapped in silos. The result is not just automation, but orchestration—where systems, data, and people work in concert.

The impact is tangible. Automakers can significantly reduce planning cycle times and improve time-to-market for new products. Planning risk is lowered through continuous what-if analysis that incorporates both internal and external variables. Service readiness improves, ensuring that customers experience continuity and reliability even as product complexity increases. At an ecosystem level, this translates into greater resilience, lower costs, and higher customer satisfaction.

More broadly, this use case points to a shift in how we should think about customer-specific AI in automotive. The future will not be defined solely by smarter vehicles, but by smarter enterprises—where AI agents support decision-making across the value chain, from product inception to end-of-life service. In an industry under pressure to innovate faster, operate leaner, and remain sustainable, AI-driven operations are fast becoming a competitive necessity. The automotive ecosystem is evolving. Those who embrace AI not just as a technology but as a new operating model will be best positioned to lead it.

Sindhu Gangadharan is head of Customer Innovation Services and managing director for SAP Labs India.

Meet your new process companion! Joule with SAP Signavio solutions is now generally available, helping users, analyze, and manage business processes using natural language.

Joule is an AI solution that turns siloed data and tasks into intelligent, connected workflows that help improve decisions, speed up end-to-end processes, and create a unified AI experience across SAP and non-SAP systems. With AI agents for all core functions, powered by SAP business process expertise, an AI strategy scales faster and wider.

In this context, the unique value of combining Joule with SAP Signavio is the powerful combination of deep process context from SAP Signavio and orchestration across SAP applications, including but not limited to SAP S/4HANA, SAP Business Technology Platform (SAP BTP), and SAP SuccessFactors solutions.

After months of successful collaboration with customers in the SAP Early Adopter Care program, this launch marks a major step toward delivering a conversational experience, making it easier than ever to explore, understand, manage, and transform processes with SAP Signavio solutions.

But how does this work in practice? Let’s look at an example.

Joule in action

Imagine accessing SAP Signavio Process Collaboration Hub, an organization’s single source of truth for process alignment, in order to understand more about a particular process, order-to-cash. What once might have taken hours of investigation can now happen in minutes through a simple conversation.

Asking Joule, “Who is the process owner of the order-to-cash process?” prompts Joule to suggest the process that most closely matches the query, then retrieve the owner information from the process diagram attributes. 

Following up with “Provide me with a description of the process flow” means Joule skills convert the process visual into a clear process description. You can dive deeper into the process as well, perhaps by comparing the difference in process execution in different regions. Just ask, and Joule skills provide a textual summary that highlights the key differences between the two process models.

Joule offers a connected user experience across SAP and non-SAP systems, allowing employees to ask questions and interact with Joule from anywhere. In other words, while working in SAP Signavio, users can interact with data and capabilities from other systems, or while in other systems, users can access SAP Signavio capabilities.

Simple and seamless

This connectivity and seamless access is designed to simplify day-to-day tasks in multiple ways, and Joule with SAP Signavio offers skills across three use cases: informational, navigational, and transactional. Plus, additional analytical capabilities are planned for future releases. As a summary, these use cases—or interaction patterns—comprise the following:

• Informational: Joule acts as an intelligent assistant, helping users understand how to perform specific tasks or generating a textual comparison between processes. For example, ask Joule: “What’s the difference between draft and published process models?” or “How can I set up a dashboard?”
• Navigational: Joule simplifies content navigation across SAP Signavio solutions and guides users through the SAP Signavio Process Collaboration Hub to access various assets such as process and journey models, and value accelerators. For example, prompt Joule: “Open the Order-to-Cash process model published for EMEA” or “Find accelerators for the Financial Process”
• Transactional: Joule enables users to perform actions conversationally, such as creating and deleting assets within the SAP Signavio Process Transformation Suite, including processes, journey models, and dictionary items. For example, tell Joule: “Create a new dictionary term and link it to the Returns process.” or “Delete the journey model called Sales Process.”

Unlocking value with agentic AI

Right now, Joule works across SAP applications as a process companion, meaning that SAP Signavio process context and intelligence is accessible to the user across all Joule-compatible applications, including, among others, SAP S/4HANA, SAP SuccessFactors solutions, and SAP BTP. But this is just the beginning.

SAP is developing Joule Agents embedded into every business function and accessed with role-based assistants, which use SAP’s process expertise to automate complex workflows and deliver AI value at scale. Joule Agents for SAP Signavio solutions can help accelerate content discovery and process analysis, create value cases, and enhance user onboarding.

The age of AI brings an expectation of immediate insights and context-based support when and where you need it, and Joule with SAP Signavio solutions means process navigation and execution is no exception.

For clearer decision-making, seamless integration, and enhanced automation, visit the Joule capabilities page to learn how to activate Joule and get your own conversation started.

Lucas de Boer is Global Marketing program lead for SAP Signavio.

As we enter 2026, volatility and uncertainty have accelerated rather than eased, which puts additional pressure on global supply chains. At the same time, we are hearing from so many of our customers that technology is no longer just part of the supply chain story, but the solution to some of its toughest challenges. From geopolitical uncertainty to rising customer expectations, supply chain leaders are facing mounting pressure to deliver resilience, agility, and sustainability. The good news is that innovations like agentic AI and advanced analytics are no longer theoretical; they’re transforming workflows today, at scale.

The past few years have taught us that disruption is the new normal. Whether it’s global conflicts, raw material shortages, or sudden demand spikes, supply chains need to pivot faster than ever. That’s why this year, the conversation isn’t about incremental improvements—it’s about reimagining processes with intelligent technologies that anticipate, adapt, and act autonomously.

From complexity to clarity: how agentic AI changes the game

Agentic AI is reshaping supply chains, and we’re already seeing real value in practice:

• Supplier onboarding in hours, not weeks: Companies can drive substantial efficiencies by collaborating more deeply with their suppliers, such as material or logistics providers. AI agents autonomously validate supplier credentials, check compliance, and integrate them into your network, cutting onboarding time by up to 50%.
• Predictive maintenance and service that prevents downtime: Instead of reacting to failures, AI agents monitor equipment health and trigger proactive service, reducing unplanned outages by 30%.
• Autonomous disruption handling: When short-term disruptions or opportunities arise to demand or supply levels, AI agents evaluate events and alerts, model scenarios, and drive action while keeping humans in the loop. If critical inventory needs to be shifted for example, agents place orders automatically, optimizing stock levels and reducing lead times by 25%.

These aren’t distant possibilities—they’re real scenarios already piloted by SAP Supply Chain customers. AI isn’t replacing people; its amplifying human decision-making, freeing teams to focus on strategy rather than firefighting.

Why this matters: analyst rankings tell the story

SAP solutions underpin strategies that earned recognition in major 2025 analyst reports, including:

• IDC MarketScape for Multi-Enterprise Supply Chain Commerce Networks*: SAP was named a Leader for enabling real-time collaboration and orchestration across global ecosystems with SAP Business Network.
• IDC MarketScape for AI-Enabled Enterprise Asset Management Applications**: SAP was positioned as a Leader for innovations like predictive maintenance and agentic AI through Joule.
• Gartner Magic Quadrant for Cloud ERP for Product-Centric Enterprises***: SAP was recognized as a Leader for integrating planning, manufacturing, and logistics with advanced analytics and AI.

These accolades aren’t just badges of honor. They validate the trust our customers and partners place in SAP and the impact we deliver together. They also reinforce a critical truth: supply chain excellence is now a boardroom priority.

Sustainability: from obligation to advantage

Sustainability isn’t just a compliance checkbox; it’s a competitive edge. More than 25% of global emissions are already taxed or regulated by trading systems. Circularity and carbon accountability have become core KPIs for supply chain leaders because responsible practices deliver measurable benefits. Meeting environmental, social, and governance (ESG) standards lowers regulatory and reputational risk, while optimizing logistics for lower emissions often translates into fewer miles traveled and reduced fuel costs. At the same time, customers and investors increasingly favor brands with transparent sustainability metrics, making it a powerful differentiator in the market.

SAP solutions help companies measure emissions, enable ESG compliance, and embed sustainability data deep into operational decision-making for procurement, logistics, dispatching, and planning. This turns sustainability into a lever for growth rather than a reporting exercise. In fact, companies recognized in Gartner’s rankings often cite sustainability as a driver of resilience and profitability. When businesses can prove carbon accountability and circularity, they’re not just meeting regulations, they’re building trust and unlocking new market opportunities.

Looking ahead: our 2026 roadmaps

In 2026, our priorities center on enabling supply chains that are more intelligent, more connected, and more resilient. We are deepening our investment in agentic AI to support end-to-end value streams such as integrated business planning, sales and operations execution, digital manufacturing, and logistics execution. The goal is to bring AI directly into processes where decisions are made so planning becomes more predictive and execution becomes more automated. Over time, organizations will entirely redesign workflows and decision-making processes for the true step-change in agentic AI.

We are also advancing our capabilities in supply chain orchestration. As global supply chains operate increasingly across networks, companies need a coordinated layer that unifies planning, procurement, manufacturing, and logistics with partner ecosystems. This year, we will continue strengthening how our solutions identify risks in the n-tier network of complex supply chains by synchronizing data, prescribing decisions and actions across the enterprise and the broader network, and helping customers manage disruptions end‑to‑end with greater speed and clarity.

Finally, we remain focused on data excellence. Reliable, harmonized data is essential for AI-driven decisions and for orchestrating the supply chain. In 2026, we are continuing to enhance master data consistency, improve network-wide data quality, and support AI‑ready data models that help ensure our customers can trust and operationalize their insights at scale.

Together, these areas form the backbone of the innovations we are delivering this year, with a clear aim of helping customers move from reactive operations to intelligent, proactive orchestration. But technology alone isn’t enough. The real magic happens when we collaborate with our customers and our partners, turning complexity into opportunity.

The takeaway: 2026 is about action at scale

The supply chain landscape is evolving faster than ever. Agentic AI, sustainability, and intelligent automation aren’t optional, but essential. Companies that embrace these technologies to truly evolve how they operate and take even complex decisions will lead in resilience, efficiency, and responsibility. Those that hesitate risk falling behind in a world where adaptability is the ultimate competitive advantage.

Don’t wait for disruption to force your hand. Build the capabilities now that will carry you through uncertainty and position you for growth. Learn more about SAP’s AI-powered solutions here.

Dominik Metzger is president and chief product officer of SAP Supply Chain Management.

*IDC MarketScape: Worldwide Multi-Enterprise Supply Chain Commerce Network 2025 Vendor Assessment, November 2025, IDC #US53010225
**IDC MarketScape: Worldwide AI-Enabled Asset-Intensive Enterprise Asset Management Applications 2025–2026 Vendor Assessment, December 2025, IDC ID # US52977525
***IDC Magic Quadrant for Cloud ERP for Product-Centric Enterprises, October 2025, IDC ID# G00826212

Sustainability rarely took center stage at Davos this year. Instead, it quietly delivered by playing an implicit and influential role in most conversations throughout the week.

The major topics of geopolitical risk, artificial intelligence, and economic uncertainty consistently circled back to environmental exposure and long-term resilience, pointing to a broader shift: sustainability is becoming less of a separate agenda item and more an underlying consideration in enterprise risk and strategy.

For leaders looking to shape the next phase of business, two major and consequential themes emerged.

1. AI is a sustainability enabler with responsibilities

Artificial intelligence was central to many Davos discussions this year, including those touching on sustainability. The focus was less on experimentation and more on how AI is already influencing operational and strategic decisions.

In several sessions, leaders pointed to practical applications where AI, combined with sustainability and operational data, is helping organizations to reduce waste, improve resource efficiency, and better anticipate environmental risks.

At the same time, there was no lack of recognition that AI brings new challenges. Its growing energy and water requirements, along with questions around governance, transparency, and equity, featured prominently in discussions. Leaders emphasized the fact that AI’s sustainability value depends heavily on how well it is integrated into existing business systems and decision-making processes, rather than deployed as a standalone technology. This was also underscored by broader analysis showing that emerging regulatory frameworks are struggling to keep pace with AI’s environmental footprint and governance needs. 

For many organizations, the focus shifted towards how responsible AI can support sustainability objectives while remaining aligned with enterprise governance and financial oversight.

2. Water is key to societal and economic stability

One of the most prominent sustainability topics at Davos 2026 was water. Across both formal and informal sessions, leaders discussed water and ocean health as a foundational element to stable societies, economies, and business continuity.

Much of the conversation focused on the growing gap between economic dependence on water and the level of investment dedicated to protecting and managing water systems. With a significant share of global GDP expected to be exposed to high water stress in the coming decades, participants highlighted the operational and financial implications for supply chains, production facilities, and communities. According to the World Economic Forum, 31% of global GDP could be located in regions of high water stress by 2050, underscoring the urgency of rethinking water investment and risk. 

To this end, new collaborative initiatives were announced during the week, including efforts aimed at integrating water considerations more directly into corporate strategies and strengthening ocean stewardship across industries. For example:

• Early-stage innovators were selected at Davos to boost water resilience across infrastructure, industry, and agriculture systems. 
• Public-private collaboration initiatives were launched to accelerate water finance and investment ahead of the 2026 UN Water Conference. 
• Research and alliance work was directed at bridging the €6.5 trillion global water infrastructure gap, and commitments were made to mobilize private capital and improve water resilience strategies. 

These discussions signaled a move away from viewing water solely through a sustainability reporting lens and toward understanding it as a material risk and resilience issue for businesses.

What can business leaders take away?

While AI and water dominated the headlines at this annual meeting, sustainability quietly permeated most strategy meetings, with three takeaways arising as directional signals for leaders looking to build resilience into their business:

Sustainability is increasingly understood as financial risk

One of the clearest signals from Davos was the extent to which sustainability risks are now discussed in financial terms.

The World Economic Forum’s Global Risks Report 2026, released shortly before the meeting, reinforced this view by ranking environmental risks (including extreme weather and biodiversity loss) and critical changes to Earth systems among the most severe long-term global threats. The same report also highlighted that adverse outcomes from artificial intelligence are rising sharply in long-horizon risk rankings, reflecting growing concern about both technological and environmental disruption. 

While geopolitical and economic issues dominated short-term attention at the annual meeting, environmental risks were consistently framed as persistent factors shaping long-term planning and resilience strategies.

Furthermore, the role of the CFO is also evolving to meet sustainability requirements, including reporting non-financial KPIs, managing plastic and carbon taxes, steering the business, and aligning business decisions with carbon and environmental cost trade-offs. SAP’s carbon accounting and management solutions can provide the capabilities needed to address CFO sustainability priorities.

As SAP Chief Sustainability & Commercial Officer Sophia Mendelsohn noted during the week, “Sustainability remains firmly planted in both the Davos agenda and the minds of the CEO and CFO. The reality of climate change persists—both its risks and opportunities, and they are already showing up on the balance sheet.“

For many executives, this framing reflects how sustainability considerations are increasingly influencing investment decisions, insurance strategies, and assessments of long-term enterprise value.

The focus is shifting from ambition to execution

Davos discussions also underscored a growing emphasis on execution. While sustainability remains firmly planted in the C-suite agenda, many leaders acknowledged a gap between ambition and implementation.

Despite years of commitments and target-setting, fewer than one in five companies have implemented climate adaptation and mitigation measures at scale. This is a persistent action gap that helps explain why sustainability strategies are now evaluated more closely through the lens of financial feasibility, operational readiness, and data credibility.

In an environment where sustainability investments compete with other priorities, including AI and digital infrastructure, leaders emphasized the need for clear business cases and measurable outcomes. Sustainability initiatives that can demonstrate value creation and risk reduction are more likely to secure long-term support.

Integration decides whether sustainability insights lead to action

Data availability is no longer the primary challenge for most organizations. The tools to measure emissions, water use, climate exposure, and supplier impacts are widely accessible. What remains difficult is turning that information into decisions.

Across Davos, there was broad agreement that sustainability data needs to be integrated into core business systems for planning, procurement, asset management, and finance. When sustainability information sits outside these systems, it tends to inform reporting rather than operational or strategic action. When it is embedded, it can support more forward-looking decisions around resilience, investment, and supply chain design.

This shift toward integration reflects a broader understanding that sustainability efforts are most effective when they are aligned with how the business already operates.

SAP’s ERP-centric, AI-enabled approach connects business and sustainability data to help give full visibility across a company’s value chain, enabling it to align business objectives with sustainability priorities across areas like material choice, efficient transport and distribution, improved asset performance, and reduced carbon impact.

Davos 2026 clearly reflected a maturing phase of the sustainability conversation, one that is less about visibility and increasingly about how organizations can confidently prepare for the decade ahead.

For business leaders shaping sustainability strategies, there is a pressing need to make plans financially grounded, operationally integrated, and supported by reliable data.

Enterprise systems play an important role in this transition. When sustainability information is connected across business functions, leaders gain clearer insight into risk and opportunity, supporting more resilient and informed decision-making.

Monica Molesag is global head of Sustainability Communications at SAP.