AI is quickly evolving from a set of powerful tools to a central component of the competitive enterprise. Specialized models, AI agents, and AI-native architecture will ensure that AI continues to embed itself into the very core of enterprise operations—with potentially powerful benefits.

To navigate AI’s evolution, organizations need to understand that it’s no longer just a question of “What can AI do?” but “How do we set our organization up for success with AI? How do we build for it? What problems do I solve with which models? How do we govern it?”

Looking ahead to five critical themes that will define enterprise AI in 2026, these present both opportunities and challenges for organizations. Let’s dive in.

1. New categories of AI foundation models unlock enterprise value

Advances in generative AI stem from breakthroughs in “foundation models,” massive neural networks trained on vast amounts of data that can be adapted to a wide range of tasks.

Large language models (LLMs) were the first wave of foundation models at scale. General-purpose LLMs, trained on the equivalent of all the text on the internet, opened the door to many value-adding use cases, including summarizing documents, writing code, and powering applications like ChatGPT and Claude. Over the last few years, we have already seen the foundation model approach applied to other domains, such as video creation and voice.

In 2026, specialized foundation models optimized for specific data types and domains will power the high-value enterprise AI use cases. Video generation models have already shown that models grounded in real-world physics data can reason about scenes and physical dynamics. Emerging world models demonstrate that simulating the physical world unlocks new possibilities in simulation, synthetic training data, and digital twins. Vision-language-action models demonstrate that robot-specific foundation models can generalize to new tasks and environments, enabling the transformation of web-scale knowledge into real-world actions in logistics and manufacturing.

In the enterprise domain, a similar shift is underway for structured data found in databases and transactional business software. While LLMs are impressive across many enterprise use cases, they cannot handle tasks like numerical predictions, such as inferring a delivery date or supplier risk score. However, work on relational foundation models shows that training on structured datasets—for example, data in tables, rather than generic text or images from the internet—can deliver high predictive accuracy without the tedious feature engineering and training required in classical machine learning. This means organizations can deploy predictive models in days, not months. Recent launches of relational foundation models, such as SAP-RPT-1, Kumo, and DistilLabs, highlight how new models can directly support use cases like forecasting, anomaly detection, and optimization across ERP, finance, manufacturing, and supply chain scenarios.

In 2026, these specialized models are expected to scale to deliver superior performance and economics for structured business tasks, surpassing general-purpose LLMs and state-of-the-art machine learning algorithms. These models will emerge as the workhorses behind high-value enterprise tasks.

2. Software evolves toward AI-native architecture

AI has seen various approaches create value over the decades, from the first rules-based expert systems to probabilistic deep learning and the recent explosion in generative AI. In 2026, organizations will shift from enhancing existing AI applications and processes to AI-native architectures, which will fully realize the promise of modern AI.

AI-native architecture adds a continuously learning, agentic intelligence layer on top of deterministic systems, enabling applications to become intent-driven, context-aware, and self-improving rather than being statically coded around fixed workflows. Agentic systems will still only be as good as the context layer they can reliably retrieve and ground on. Here, organizations should invest in truly comprehensive, semantically rich knowledge graphs that provide a scalable source of context, making AI-native software dependable and self-improving.

Enterprise applications will increasingly be built natively around AI capabilities, featuring user experiences designed for multi-model, natural language interaction; AI agents reasoning through complex processes; and a foundation managing foundation models, services, and a knowledge graph capturing semantically rich business data. AI-native architecture also enables more employees to create apps—such as smaller, ad-hoc productivity applications—in a matter of minutes without straining IT. 

AI-native architecture builds on, and even requires, established SaaS principles and investments in modern cloud applications. The technical term for combining probabilistic, adaptive AI models with deterministic systems of record is called neurosymbolic AI. It brings together AI’s best capabilities to adapt with reliable, governable, and deterministic processes. Next-gen applications will not just have AI bolted on; they’ll be built around AI at their core. This means combining reasoning, business rules, and data to deliver insights and automation seamlessly. Imagine ERP systems that proactively flag anomalies, recommend actions, and even execute workflows autonomously—all while staying aligned with company policies and regulations.

3. Agentic governance becomes mission-critical

Over the past two to three years, generative AI has introduced a wave of value-added use cases. These use cases were largely based on users sending a prompt to a model, receiving a response, and then interacting with the model again.

Last year saw the start of the next wave of innovation: AI agents capable of planning and iteratively reasoning through multi-step tasks, including selecting tools, self-reflecting on progress, and collaborating with other AI agents. These advanced AI agents promise to tackle complex business processes that were previously immune to automation, such as analyzing myriad documents, records, and policies to resolve a dispute or book a trip.

However, the proliferation of AI agents, many of which handle critical tasks and sensitive data, demands the development of new capabilities. Agentic governance will emerge as a critical capability as organizations deploy hundreds of specialized AI agents. The “agent sprawl” challenge will mirror previous shadow IT crises, but with higher stakes given agents’ autonomous decision-making capabilities.

Forward-thinking enterprises will establish comprehensive governance frameworks addressing five dimensions: agent lifecycle management (version control, testing protocols, deployment approval, retirement procedures); observability and auditability (agent inventory, logging, reasoning paths, and action traces); policy enforcement (embedding business rules, regulatory constraints, and ethical guidelines into agent execution); human-agent collaboration models (defining autonomy boundaries, approval requirements, and escalation pathways); and performance monitoring (tracking accuracy, efficiency, cost, and business impact).

The organizational shift will prove profound—from viewing AI as an independent tool to managing agents as digital coworkers requiring onboarding, performance reviews, and continuous improvement. HR and IT functions will collaborate on “digital workforce management” as organizations treat agentic governance as seriously as they do traditional workforce oversight.

4. Intent-driven ERP and generative UI emerge as a new user experience

Consumers are becoming increasingly familiar with computer interactions requiring prompts in natural language, voice, and even images and gestures. At the same time, generative AI’s ability to create text, graphs, code, and HTML on the fly is improving rapidly. In parallel, AI agents enable users to simply express their intentions, allowing the agent to determine how to work toward achieving that goal.

These advancements open the door to varied and entirely new modalities for users to work with enterprise software, as well as “no-app ERP” experiences. For example, to book a customer visit, a worker typically needs to open an analytics application to review the account, look in the CRM system to retrieve the customer’s address, and then navigate to another application to book travel, among other tasks. 

In 2026, we will see “gen UI” experiences increasingly surface via digital assistants, relieving users from the need to navigate between multiple applications and perform manual tasks. With time, AI will allow the user to simply express the intent: “Prepare a trip to my customer with the most leads.” From here, an AI agent will plan out the steps and required systems, interacting with the user to confirm travel details while dynamically generating analytical graphs and briefing material in the window. As AI agents develop stronger calculation and prediction tools, users will be able to “speak to their data” more naturally, with agents making data-based decisions in the background. To be clear, interactions with agents will extend far beyond a chat box; organizations will enjoy rich visualizations, complete workflows, and the ability to build hyper-personalized apps with just a few commands.

The user interface will not disappear. No-app ERP experiences and autonomous agents require the same foundational substrate that humans rely on for their daily work: structured workflows, security, governance, and business logic defined in business applications. The difference is that agents consume these primitives programmatically at scale, not only through a GUI, and humans can interact with these agents via natural language without ever needing to open the application.

These capabilities will usher in a new paradigm for human-AI collaboration and productivity in the workplace. Personalized experiences and adaptive workflows across applications and data sources will lower adoption barriers. This ability to focus solely on achieving a user’s intention, regardless of the interaction modality and underlying systems, will drive return on investment (ROI) in AI and enterprise software.

5. Deglobalization drives sovereign AI offerings

AI sparked debates about digital sovereignty among nations due to AI’s potential impact on everything from scientific discovery and national security to economic productivity and even culture. Events in geopolitics, such as supply chain disruptions caused by tariffs and war, have only intensified the urgency that many nations and organizations feel to become digitally sovereign.

Digital sovereignty has two broad definitions. First, digital sovereignty is an information security designation governing data storage and access, such as U.S. FedRAMP and German VSA, required to process sensitive governmental data in a “sovereign cloud.” Second, and more broadly, sovereignty refers to the provenance of physical assets, intellectual property, legal jurisdiction, and services along the cloud stack. For example, does an application utilize an AI model created in Europe, the U.S., or China, and is the data center geographically isolated? 

The high stakes, geopolitical uncertainty, and complexity of “sovereign AI” will lead enterprises to increasingly demand AI and cloud solutions that are simultaneously cutting-edge, flexible, and fully sovereign. This intensifies the shift from globalized one-size-fits-all cloud to regionally compliant, AI-powered enterprise platforms. At the same time, governments will continue to refine their national AI strategies to invest in areas along the stack where they can compete and create value.

Executing on the 2026 AI themes

In 2026, AI is poised to move from a supporting tool to a fundamental pillar of the enterprise. This shift is driven by a convergence of defining trends—including increasingly capable agents, generative UI, and AI-native architecture—that push AI from the application layer and into the very core of business operations.

Organizations that thrive will be those that recognize this shift and build an enterprise that is purpose-built for AI: establishing robust governance to manage a new, collaborative workforce of humans and AI agents; embracing gen UI to lower adoption barriers and an intent-driven user experience that helps employees interact naturally; seeking out specialized foundation models that are precisely tuned for enterprise use cases to drive business value; and, finally, building applications natively around AI that combine reasoning, business rules, and data, delivering proactive insights and automation.

However, in 2026, organizations will still need high-quality, connected data. Data siloes severely limit the effectiveness of AI. As mentioned, AI-native architecture requires established investments in modern cloud applications that harmonize data across the entire business—because unified data means AI’s outcomes are more accurate and relevant.

Jonathan von Rueden is chief AI officer at SAP SE.
Walter Sun is senior vice president and global head of AI for SAP Business AI at SAP.
Sean Kask is vice president and head of AI Strategy for SAP Business AI at SAP.

Embedded AI streamlines planning, operations, fulfillment and commerce to help retailers scale with speed, resilience and loyalty

NEW YORK — SAP SE (NYSE: SAP) today announced a new generation of AI-enhanced retail innovations at NRF 2026: Retail’s Big Show.

SAP continues to infuse AI into the DNA of every part of its retail solutions, reinforcing its suite-first strategy and helping retailers operate with greater intelligence, resilience and trust while delivering better experiences for customers everywhere.

“Retailers face a landscape where AI is no longer optional,” said Balaji Balasubramanian, President and Chief Product Officer for Customer Experience and Consumer Industries, SAP SE. “SAP provides one closed-loop, AI-enhanced retail operating system that ties planning, execution and engagement together. We put data and AI at the heart of retail, delivering speed, personalization and growth across every channel and segment.”

AI that turns retail data into actionable intelligence

The Retail Intelligence solution in SAP Business Data Cloud provides accurate demand and inventory planning, leveraging retailers’ data from across SAP software and third-party systems to drive profitable growth through actionable, real-time insights. Purpose-built for retailers and direct-to-consumer businesses, it will be generally available in the first half of 2026.

Harmonizing real-time data from sales, inventory, customers and suppliers, Retail Intelligence uses AI-generated simulations so planners can anticipate outcomes and optimize inventory. This improves forecast accuracy, reduces manual planning effort, lowers inventory costs and raises service levels. All this drives more seamless omnichannel engagements, which strengthen customer loyalty and enable growth without adding complexity for retailers.

“Retailers are seeking built-in, embedded AI solutions to help balance daily operations, future planning and agility to manage a dynamic market,” said Ananda Chakravarty, Vice President of IDC Retail Insights. “What sets SAP apart is the holistic nature of its approach, offering an agentic operating system that works in the background, connects data and orchestrates agents. SAP makes it an easy lift for retailers to achieve enterprise-wide intelligence, avoiding the complexity of many point solutions.”

AI that streamlines modern retail operations

Retailers must make fast, confident decisions across assortments, pricing and planning. To meet that need, SAP announced new AI-assisted assortment management capabilities, allowing planners to create, modify or retire assortments using natural language through the Joule copilot. This reduces the bottleneck on expert users, enabling faster responses to market shifts and freeing time for higher-value merchandising decisions.

SAP also introduced omnichannel sales promotions in sales orders, integrating the SAP Omnichannel Promotion Pricing solution with the SAP S/4HANA Cloud Public Edition, retail, fashion and vertical business solution. This enables advanced promotions such as bonus buys to be applied consistently across diverse channels, enabling a single source of truth for pricing and promotions in store and online, so retailers can deliver a consistent experience.

In addition, SAP is delivering deeper merchandising, segmentation and manufacturing support in the solution, tailored to fashion wholesalers and manufacturers. These enhancements provide the data and process foundation needed for AI-assisted fashion operations across the business.

AI that drives better customer engagement

As shopping journeys increasingly begin with AI assistants rather than storefronts or search engines, retailers need new ways to be present wherever buying decisions are made. SAP helps retailers connect products, pricing, inventory and promotions directly to AI-enabled discovery and shopping experiences, unlocking agentic commerce with its new storefront MCP server, part of the SAP Commerce Cloud solution.

Retailers can now make their storefronts intelligible to AI, driving shopping experiences not only on their storefronts but also on platforms such as ChatGPT. This creates a truly channel-less commerce experience, one where engagement, discovery and transaction happen more seamlessly across human and AI-assisted touch points.

AI that builds customer loyalty

As customer expectations rise and fulfillment networks grow more complex, retailers need confidence that every order will be delivered as promised, using AI solutions that provide proactive visibility and guidance to help keep operations running smoothly and at scale. And as brand visibility shifts in the age of agentic commerce, reliable and consistent shopping experiences are more important than ever to drive sustained customer loyalty and trust.

SAP announced Order Reliability Agent as part of the SAP Order Management Services bundle, planned for release in the second quarter of 2026. The new agent proactively identifies and resolves potential order issues, helping associates answer common questions about order status, stock availability and fulfillment risks before they impact customers.

By combining agentic autonomy with human oversight where judgment matters, these innovations from SAP drive insightful planning and improve operational efficiency, both enhancing the customer experience and driving profitable growth.

Visit the SAP News Center. Get SAP news via LinkedIn and Bluesky.

Media contact:
Mallory Kuno, +1 (425) 239-9362, mallory.kuno@sap.com, ET
SAP Press Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.  Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of SAP’s 2024 Annual Report on Form 20-F.
© 2026 SAP SE. All rights reserved.
SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE in Germany and other countries. Please see https://www.sap.com/copyright for additional trademark information and notices.

NEWTOWN SQUARE —  SAP SE (NYSE: SAP) today announced the appointment of David Robinson as president of SAP North America. In this role, Robinson will oversee the company’s North America market units and lead sales operations across the broader Americas region. He will focus on driving customer success, accelerating business transformation, and helping organizations realize the full value of their SAP solutions.

“David’s deep understanding of our North American markets and strategic vision will accelerate SAP’s momentum in this geography as we continue to empower businesses with AI embedded in mission critical applications and powered by unified data to drive real business outcomes,” said Jan Gilg, Global President of Customer Success & Americas and member of the Extended Board of SAP SE. “With his appointment, we are bringing special focus and extra leadership capacity to SAP’s most important growth market.”

Robinson has 22 years of SAP experience and proven leadership across multiple business functions. Most recently serving as president and chief revenue officer for Cloud ERP and acting managing director for SAP U.S. Public Services, he has been instrumental in driving SAP’s and customers’ cloud transformation strategies. His SAP career includes leadership roles as senior vice president for RISE with SAP, global vice president and managing director, COO for Customer Success, and regional vice president for business finance in North America. Earlier in his career, he served as chief innovation officer for public services and led industry advisory, value advisory, and product engineering teams at SAP Labs.

Visit the SAP News Center. Get SAP news via LinkedIn and Bluesky.

Media Contact:
Victoria Dixon, +1 (703) 288-6020, victoria.dixon@sap.com, ET
SAP Press Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.  Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of SAP’s 2024 Annual Report on Form 20-F.
© 2026 SAP SE. All rights reserved.
SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE in Germany and other countries. Please see https://www.sap.com/copyright for additional trademark information and notices.

For decades, BSH Hausgeräte GmbH has been a quiet force in kitchens worldwide, with brands like Bosch, Siemens, and Gaggenau in its portfolio. Now, the company is rewriting its own recipe—not for food, but for finance. In partnership with SAP, BSH is transforming its IT landscape to a cloud-first foundation, aiming to free employees from manual tasks and put insights at the center of decision-making.

In an interview, BSH Head of Governance, Methods, and Systems Heiko Schletz explained how the company is reshaping finance and why its move to the cloud is a critical ingredient to a successful AI-enhanced future.

Technology follows vision

Represented in more than 50 countries, BSH manufactures home appliances in 39 factories worldwide. Schletz’s team oversees group controlling and is responsible for ensuring that financial data flows smoothly from its core systems, such as ERP, all the way up to the consolidated group level. His team manages how financial data is structured and integrated across all global entities, ensuring it can be used effectively for company-wide reporting and decision-making.

BSH is working to bring accounting and controlling together into one integrated process, supported by real-time data and analytics. One principle is guiding this transformation: technology follows vision, not the other way round. As part of its transformation journey, BSH is embracing change by testing new technologies to support its vision.

To simplify reporting efforts, for example, BSH is currently piloting SAP Datasphere, SAP’s next-generation data management platform that can unify and govern all SAP data and seamlessly connect with third-party data.

A recent use case automatically connected accounting balances, controlling P&L data and market metrics in SAP Datasphere and delivering consolidated reports without spreadsheets and manual effort. “This shows where the journey is going—joining sources, bringing them together,” Schletz says.

Breaking down silos to empower AI

BSH’s long-term goal in the financial area is to get rid of silos between accounting, controlling, and treasury. Schletz envisions a parallel ledger architecture that supports both—legal entity and consolidated group views—enabling advanced analytics such as value-driver trees. By moving to SAP S/4HANA Cloud Private Edition, integrated with SAP Datasphere and SAP Analytics Cloud, BSH aims to create a single source of truth for finance spanning from subsidiary ledgers to group-level consolidation.

Schletz is convinced that with a cloud-based, synchronized toolset, his finance team can deliver the latest figures for decision-making faster and with less manual consolidation. “SAP’s AI evolution is running in the direction we also want to go,” Schletz explains. “The technology meets our vision and that’s why it’s a perfect fit.”

The company has relied on SAP solutions for decades, starting with SAP R/3 and now running SAP S/4HANA, SAP Business Warehouse, and SAP Analytics Cloud. The next milestone is cloud migration: RISE with SAP. “In the next two years, we go into the cloud,” Schletz says. “We want a synchronized toolset that gives us a holistic view.”

To get the most out of analytics and AI functionalities, BSH is currently consolidating and simplifying its comprehensive business application landscape. The company’s target is to move from six separate ERP solutions to one global SAP S/4HANA environment that covers all subsidiaries and geographies.

How to prepare an SAP S/4HANA transformation

Schletz’s advice for other organizations exploring the RISE with SAP journey is to start with a clear vision. “If you don’t begin with a concept that combines accounting and controlling, don’t start with SAP S/4HANA,” he says, noting that a finance transformation is not an isolated IT project—it requires alignment across logistics, sales, and customer service. “The SAP S/4HANA conversion is a cross-functional adventure,” he adds.

BSH’s journey is ongoing, but the direction is set. Cloud migration via RISE with SAP, integrated data, and a finance function designed for insight rather than manual effort. “We want the machine to do what it does best, so people can focus on creating value,” Schletz concludes.

SAP has announced a final five months transition period for the usage rights of its Compatibility Packs for SAP S/4HANA on premise, moving the expiration date from December 31, 2025, to the end of May 2026.

Compatibility Packs provide temporary usage rights, allowing certain classical SAP ERP functionalities to operate within SAP S/4HANA, aiming to ease the migration and maintain business continuity for customers moving from SAP ERP to SAP S/4HANA.

For most of the Compatibility Packs, the usage rights end on December 31, 2025, which has been extensively communicated to customers, partners, and user groups and is documented in SAP Note 2269324.

To counter for the fact that despite the extensive communication several customers still need some more time to manage this transition, SAP is offering this final transition period in an effort to provide customers with greater choice and flexibility.

Accompanying this extension, SAP will offer tailored programs for customers that are moving to the respective SAP cloud solutions that replace the compatibility pack functionalities. We encourage affected customers to contact their SAP representative.

Stefan Steinle is EVP and head of Customer Support & Cloud Lifecycle Management at SAP.

Founded in 1995, Howdens Joinery has become one of the UK’s premier kitchen and joinery suppliers, producing over 4.5 million kitchen cabinets annually and distributing more than 44 million pieces through its extensive supply chain network.  

As the business expanded, so did the complexity of its operations and the expectations of its customers. The existing manufacturing development team, focused on small-scale factory applications, found it increasingly difficult to keep up with the pace. The data was often locked in silos or other systems. To address this, Howdens set out to automate and collect data from multiple points across its supply chain. 

Considering off-the-shelf solutions that could be tailored to its needs, Howdens Joinery needed a solution that would continue to evolve with the company. Through a detailed assessment of several manufacturing execution systems (MES), Howdens Joinery decided to replace all outdated manufacturing execution systems with the SAP Digital Manufacturing solution, making it the heartbeat of its production processes with the help of a featured partner, Eng. 

Reinventing kitchens with an innovative and customer-centric process 

The kitchen has evolved from a simple cooking space into the heart of the home. Knowing this, Howdens Joinery has adapted its offerings to meet the changing needs of its customers. “The kitchen market has changed a lot over the years,” says David Peacock, IS Manufacturing System technical lead at Howdens Joinery. “We don’t sell a kitchen; we provide a living space, the central part of their homes.” 

Howdens expanded its range beyond the standard kitchen colors and styles. This approach enables customers to experiment with various colors and styles before making a final decision. “It’s almost like a trial run,” Peacock explains. “We can see if a new color is worth adding to our main range. If it’s popular, we can roll it out on a larger scale.” 

This strategy not only helps customers find the perfect kitchen but also provides Howdens with valuable feedback on what works best. To support this expanded offering, the company invested in a new factory and upgraded paint lines. These improvements enhanced production capacity and equipped the team with new skills and expertise. 

Traditionally, the company made a stock model, but now customers can visit depots and order kitchens in any color and style they want. “We have a fast turnaround, with manufacturing and shipping taking just five days,” Peacock says. “To make this possible, we updated our entire order strategy and implemented the new system in less than 12 months.” 

By embracing innovation and listening to customer needs, Howdens Joinery has successfully transformed its business to stay ahead in a competitive market, making it easier than ever for customers to get the kitchen they truly want. 

“Having our own homegrown MES provided us a clear view of what needed to be produced on each production line,” he says. “In real time, operators could start or stop orders and receive confirmations. And we continued to add more features and functionalities to our MES.”

Reducing order production lead time from 21 days to 14 days 

Howdens Joinery faced two major challenges as it transformed its approach to kitchen manufacturing. The company sells the individual pieces of a kitchen, such as cabinet doors or shelves, that are ordered separately. 

Highlighting that the company is sales order-driven, Peacock further adds, “When you convert the sales orders into production orders, you get a sort of production order per piece. Tracking this is easier said than done.” Each piece follows a specific route through the factory, depending on its shape and the machinery it needs to pass through. Since the company isn’t selling finished panels that are simply waiting on a shelf, tracking each part and keeping everything together was a great challenge. 

Another major hurdle was managing the concept of process lots. Because of the specific routing required for different components, orders often needed to be split and sent down two separate production routes. These production orders would then be grouped into SFCs (shop floor controls), but this sometimes made the process more complicated rather than simpler. 

“We are potentially in a one-for-one relationship with the production order, so the SFC number became a bit redundant,” Peacock explains. The complexity increased when multiple orders were launched simultaneously. He adds: “We might be launching different production orders at a time, but we did not want in [SAP Digital Manufacturing] the guys on the shop floor to press start 40 times.” This led the company to create a mechanism for efficiently grouping orders, allowing, for example, all orders of a certain color to be processed together on the same production line. 

“When you purchase [SAP Digital Manufacturing], you’re not just buying manufacturing, but you’re buying the ability to build a manufacturing landscape. So you can do your own customizations,” he adds. 

With SAP Digital Manufacturing, Howdens Joinery enhanced operational efficiency and achieved a supporting mechanism to support both make-to-stock and make-to-order production models. 

Continuous improvement as a key driver for the future of manufacturing 

Howdens Joinery is leveraging diverse technologies in production systems. Particularly as a company expanding its manufacturing capabilities, this requires the integration of IT and operational technology, as well as seamless communication with machinery and the automation of production workflows—such as custom SAP Business Technology Platform (SAP BTP) processes and production connectors.  

With this integration, Howdens Joinery achieved direct communication with various types of machinery, thereby enhancing production efficiency and reducing the need for manual intervention. 

“With SAP Digital Manufacturing, we gained operational excellence in our supply chain processes, leading to more efficient planning and an enormous increase in production. We reduced order production lead time from 21 days to 14 days in 2023 to 2024, contributing to faster customer fulfillment,” Peacock says.

Moreover, Howdens achieved a 99.98% service level from primary sites to depots in 2024, demonstrating near-perfect product availability. “We will continue this journey of continuous improvement to deliver the best products for our customers,” he says. 

The innovative manufacturer plans to replace its legacy MES systems with a fully digital manufacturing solution, ensuring streamlined and efficient operations. With robust data quality and a flexible approach to integrating new technologies, Howdens Joinery is planning to integrate AI into its manufacturing processes as the next step. Its proactive approach to utilizing new technology for operational excellence is a great industry example for the broader manufacturing community.  

To learn more about Howdens Joinery’s transformation story, check out the full customer story here. 

Oyku Ilgar is part of SAP Supply Chain Management Thought Leadership & Awareness.

Most organizations see the potential of AI but struggle to turn that ambition into measurable, enterprise-scale results. Fragmented processes, limited AI expertise, and inconsistent data readiness often make it difficult to move beyond isolated experiments.

This is where SAP and the SAP partner ecosystem make a decisive difference.

Together, we help customers translate AI strategies into meaningful outcomes by pairing partner industry expertise with SAP Business AI, which brings hundreds of purpose-built, domain-rich capabilities embedded across SAP applications. These capabilities help automate processes, elevate decision-making, and enhance employee productivity across the enterprise.

SAP Business Technology Platform (SAP BTP) amplifies this foundation by giving customers the ability to integrate, extend, and build AI-powered solutions in a scalable and secure environment.

Across industries, SAP and our partners are helping customers unlock real value from AI. The examples below show how organizations are already achieving tangible impact today.

Driving efficiency with AI-powered process automation

Manual, repetitive processes remain one of the biggest barriers to operational excellence. The SAP partner ecosystem plays a critical role in helping customers uncover these inefficiencies and redesign them with AI-driven automation.

For frozen-food manufacturer FRoSTA, SAP partners sovanta AG, and Amista identified invoice processing as a major bottleneck. By orchestrating the workflow using SAP Build Process Automation and extracting, interpreting, and validating data through SAP Document AI, the partners were able to automate the process end to end. Invoices that once required several minutes of manual effort now flow through the system in under a minute, with roughly 60 percent fully automated. Employees can redirect their attention to higher-value work, such as resolving exceptions and collaborating with suppliers.

This is the power of pairing partner expertise with SAP Business AI and SAP BTP solutions: Organizations quickly shift from isolated task automation to connected, intelligent workflows that scale across departments and regions. What begins as a single use case becomes the foundation for a broader automation strategy—accelerating processes, reducing manual effort, and tightening the connection between data, people, and decisions.

Accelerating innovation by making AI accessible to every team

As demand for AI grows, many organizations face a familiar hurdle: the scarcity of specialized AI talent. Partners in the SAP ecosystem help close this gap by combining their industry knowledge with tools in SAP Business AI and SAP BTP that make it easier for teams across the business to experiment, prototype, and deploy AI solutions at speed.

A strong example comes from Aspen Pumps, which partnered with NTT DATA to modernize routine operational tasks. Using low-code capabilities from SAP Build to design and orchestrate workflows and SAP AI Core to power AI models, the team rapidly developed a series of automation bots—12 in total. These now streamline activities such as invoice validation, order routing, and even interpreting CAD drawings to accelerate quote creation. Many proof-of-concept initiatives were completed in under a week, demonstrating how accessible innovation becomes when intelligent capabilities are built directly into the tools teams already use.

By lowering the barriers to experimentation, SAP and partners help organizations innovate faster and more confidently. Teams can explore new ideas, test them safely, and scale what works—without waiting for scarce technical resources or lengthy development cycles. Innovation becomes a daily practice, not a specialized activity reserved for a few.

Building a future-ready foundation with scalable, extensible architecture

As AI becomes more deeply integrated into business operations, leaders are prioritizing platforms that will scale with them, not constrain them. This is where SAP partners help customers design architectures that can evolve with changing market needs while preserving the stability of their core systems.

Steel manufacturer Al Ghurair Iron and Steel (AGIS) offers a powerful example. Working with Deloitte, the company reimagined its production planning process using SAP Business AI embedded in SAP S/4HANA Cloud, private edition, combined with the integration and extension capabilities of SAP BTP. A planning cycle that once required 15 minutes of manual coordination now takes less than five. The solution has been replicated across multiple locations, and more than 400 calculations are now automated, giving teams more time to analyze results and optimize operations rather than manage spreadsheets.

When SAP Business AI and SAP BTP come together with partner expertise, companies gain a foundation they can rely on as their AI ambitions grow. They can scale new capabilities across plants, regions, or business units; extend processes without disrupting mission-critical systems; and seamlessly connect SAP and non-SAP environments into a cohesive, intelligent landscape.

Turning AI potential into business transformation

These stories demonstrate what becomes possible when customers, SAP, and our partners work together: faster processing, smarter decisions, empowered employees, and architectures built for long-term agility and growth.

With the combined strength of the SAP partner ecosystem, the domain-rich intelligence of SAP Business AI, and the extensibility of SAP BTP, organizations can move beyond pilots and embed AI where it matters most: in the daily processes and decisions that run their businesses.

Learn more about what’s possible for your business with SAP Business AI at sap.com/ai.

In a global economy shaped by geopolitical fragmentation, macroeconomic strain, and the rapid rise of artificial intelligence, the role of the chief financial officer (CFO) has never played a more pivotal part in guiding strategy amid disruption.

Economist Impact’s new report, “Beyond the balance sheet: The new CFO mandate,” sponsored by SAP, reveals how CFOs are shifting from stewards of financial accuracy to architects of business resilience, digital innovation, and long-term value. Based on input of 480 CFOs globally, the report highlights widening responsibilities, rising risk pressures, and an urgent need to adopt AI with both speed and discipline.

To lead effectively through volatility, today’s CFO agenda demands operational agility, intelligent automation, and a reimagined approach to workforce development. Here’s how today’s finance leaders are adapting.

The expanding CFO mandate

Gone are the days when CFOs focused solely on financial planning and reporting. Today, their influence extends far beyond traditional finance boundaries. Nearly 90% of CFOs report they are more involved in digital transformation and risk management than three years ago. Two-thirds are actively shaping sustainability and ESG strategies.

This evolution reflects a broader truth. CFOs are now central to decisions that impact customers, products, and talent. They are expected to anticipate disruption, mitigate risk, and enable agility—all while safeguarding profitability.

Macroeconomic, geopolitical, and technological shifts are pushing CFOs deeper into operational decision-making. As one CFO quoted in the report explained, finance leaders today must “wear multiple hats” and develop a deep understanding of business fundamentals, processes, and controls to guide transformation effectively.

With expectations rising and responsibilities converging, the next challenge is clear: aligning these expanded priorities with the capabilities required to execute them.

A sharper risk radar in an uncertain world

CFOs are on the front lines of uncertainty with increasing pressure to keep risks and costs from ballooning. In fact, more than 80% of CFOs reported that they are now more involved in risk management and compliance, with 34% significantly so.

Yet, it is not higher costs that worry CFOs most, it is unpredictability. Inflation, shifting trade rules, and increased interest rates make capital allocation more challenging, with only 37% feeling confident about meeting liquidity targets, compared with nearly 90% for revenue goals.

In response, CFOs are doubling down on what they can control. AI-enabled scenario planning is enabling faster, more sophisticated modeling, while real-time operational signals are being translated into forward-looking risk indicators. Flexibility has also become essential, from upgrading systems for adaptable production to renegotiating vendor contracts with shorter, more variable terms.

Ultimately, the mandate is clear: build organizations that can absorb shocks, respond in real time, and maintain strategic momentum despite uncertainty.

CFOs at the center of AI adoption

Digital transformation has become a core responsibility of the CFO’s role, with nearly nine in ten reporting increased involvement—much of it centered on AI. Finance leaders cite especially strong potential in compliance, where generative AI can parse complex regulations, track rule changes, and automate updates to internal systems.

But several challenges stand in the way of scaling AI’s impact:

Talent: the biggest barrier to AI acceleration

More than 60% of CFOs cited upskilling and hiring digitally fluent talent as top challenges, with fragmented systems and limited real-time data access adding further friction. As a result, CFOs are strengthening both team skills and data quality, recognizing that AI can only scale when people know how to use it and the data behind it is trusted.

The ROI paradox

CFOs must deliver quick wins from AI even though its most meaningful gains in forecasting, innovation, and growth take longer to materialize. To resolve this tension, leading CFOs are setting clear performance benchmarks, directing AI toward revenue-driving use cases, and coordinating across the business to scale capabilities that unlock sustained value.

Designing the workforce for an AI future

While AI is reshaping work, rising concerns about workforce displacement remain a real challenge for finance teams. However, nearly seven in ten CFOs see AI as a tool to augment human capability, prompting a rethink of roles, skills, and hiring decisions. Leading CFOs are redesigning early-career roles, investing in digital and analytical skills, and building blended teams that pair human judgment with AI-driven insight to strengthen the leadership pipeline.

Taken together, these shifts signal a broader evolution: finance is moving from a function rooted in historical reporting to one defined by predictive insight, real-time decision support, and enterprise-wide capability building.

CFOs who balance rapid efficiency with long-term investment in data, skills, and new ways of working will turn AI into a sustainable competitive advantage rather than a short-lived productivity boost.

Looking ahead: the new CFO playbook

Economist Impact’s research shows that the modern CFO shapes how organizations navigate risk, adopt AI, and build the workforce capabilities required for continuous transformation.

This shift demands a new playbook that unlocks capacity through automation, strengthens cross-functional alignment, builds flexibility into systems and supply chains, and reimagines finance career paths for a digital-first future. As one interviewee noted, “The modern CFO is not just the guardian of value but the architect of future value.” That future will belong to leaders who pair disciplined cost and risk management with bold investment in data, skills, and AI-driven insight.

With SAP’s financial management solutions, finance leaders can unify data, processes, and intelligence to meet the expanding demands of the role. As the expectations placed on finance continue to grow, SAP remains committed to empowering CFOs with the clarity and confidence needed to lead through uncertainty and shape a more resilient future.

Learn more about SAP financial management solutions.

David Imbert is head of Product Marketing for Finance at SAP.

With roots in ancient Greece and an Olympic history that dates to 1912, equestrian sports are steeped in tradition. Take dressage, which the Fédération Équestre Internationale (FEI) describes as the “ultimate expression of horse training and elegance,” a complex sport where human and equine athletes compete at events all over the world, evaluated by judges and spectators in an array of categories that prize beauty, grace, and tradition.

Bringing a sport like dressage into the digital age would be no small feat, but that is precisely the challenge Black Horse One undertook in 2016.

Partnering with SAP, Black Horse One CEO Daniel Göhlen and his team of 12 brought a quiet digital revolution to the paper-based, tradition-bound world of equestrian sports—introducing digital scoring systems, streamlining event operations, and facilitating fan engagement—that supported and enhanced the experience of trainers, athletes, judges, federations, event managers, and fans all over the world.

However, Black Horse One saw room for even more innovation in equestrian sports, particularly in addressing the operational challenges of equestrian event management and the untapped potential of the industry’s heavily siloed data.

Digital transformation unlocks boundless potential

With its “consistency, affordability, and proven reliability,” SAP quickly became mission-critical for Black Horse One. Building on that success, Göhlen turned to SAP Business Technology Platform (SAP BTP) to bring the company’s next vision to life—a digital event management system designed to transform how equestrian competitions are run. The new system delivers real-time, end-to-end oversight and streamlines every workflow, giving “show organizers and national federations a 360-degree software” that has cut event preparation time in half.

The industry quickly took note, and Black Horse One went from 100 equestrian shows a year in 15 countries to around 300 in 32 countries and from 50,000 unique users per month to as many as 3 million—an exponential increase in operations that the company supports with the same small team.

Further digitization of processes and information has helped Black Horse One dismantle the data silos that challenge many industries, especially one as rooted in tradition as equestrian sports. Data pours in from multiple sources: national federations maintain separate records for each horse, judges and audiences submit marks in real time, and organizers update competition systems on the fly. Every change must be reflected instantly, not only to maintain accurate results but also to meet fans’ expectations for real-time updates.

Göhlen, himself a former equestrian athlete, explains that many seasoned trainers and riders struggle to capture and pass on their hard-earned expertise and knowledge built over decades in the arena. A platform that enables real-time recording and sharing of performance data, scoring insights, and training techniques across a global, always-on network is transforming how the dressage community preserves and transmits its know-how.

And, in a sport where animal welfare is paramount, continued technological advancement offers additional layers of information and accountability when it comes to tracking and monitoring horses, which, Göhlen hopes, will continue to equate to happier, healthier equine athletes.

Leveraging AI in a world of tradition

Black Horse One continues to take a storied sport across new technological frontiers, leveraging SAP BTP to help bring artificial intelligence (AI) into its offerings. The company is already using AI to analyze performance data and biomechanical metrics, delivering personalized training and technique insights. It can even generate AI announcers when human ones aren’t available. Göhlen notes that Black Horse One is still in the early stages of exploring the “tremendous” potential of AI—using it to support and advance equestrian sport in ways that are not only exciting but also wise and effective.

Göhlen himself offers sage advice when it comes to assuaging stakeholders’ fears around digital transformation and AI in particular: “People really need to see that the technology supports them rather than replaces them.”

Real and sustainable innovation

Black Horse One’s remarkable story of leveraging technology to transform an age-old sport demonstrates that there is no company too small or industry too niche to benefit from digital transformation.

For those looking to embark on a similar journey, Göhlen has advice: first, start with the pain points, “where processes are currently inefficient or fragmented,” and then find the technology to ensure meaningful innovation. Second, Göhlen advises companies to earn and keep their customers’ trust. “In many of our mission-critical settings, if we make a mistake, we can’t undo it. So, make sure that you choose your technology wisely,” he says.

Finally, and most crucially, remember that innovation is a process, not a destination. “Never stop learning,” Göhlen says. “Each project should push you and your team to grow technically and strategically. This is how innovation stays real and sustainable.”

For the full Black Horse One episode and the on-demand Better Together: Customer Conversations series, visit here.

The full episode

Learn more about how Black Horse One brought digital transformation to the tradition-bound world of equestrian sports.

• Thought leadership podcast: Göhlen, CEO of Black Horse One, talks with Tamara McCleary, CEO of Thulium, to share his motivation and journey merging tradition with technology to transform equestrian events, improving the sport and the sporting experience for athletes and audiences and winning over even the most traditional participants.
• Practitioners’ video: Göhlen talks with me about what it took and the technologies that have resulted in a suite of applications that revolutionized the dressage world.

To access the whole series, on demand, visit here.

Do you have ideas for topics or technologies we should cover, or would you like to be a guest on the show? We want to hear from you, just e-mail us.

Timo Elliottis vice president and global innovation advocate for SAP BTP at SAP.