It’s wrap on NRF, and it is no surprise that customer engagement and artificial intelligence (AI) were top of mind for most retailers. This furthers SAP’s commitment to delivering compelling innovation that empowers our customers to deliver the best customer experience.

We are leaving the biggest retail event of the year with so much excitement for what’s to come for the SAP Customer Experience portfolio this year. Here’s a look into SAP CX innovations for 2025.

Data-Driven Loyalty Management Solution

We announced a new loyalty management solution that helps brands earn the loyalty of their customers using experiential journeys and personalized, real-time offers.

Creating loyalty is key to profitable growth; however, lasting loyalty has been illusive to many brands. According to the SAP Emarsys Customer Loyalty Index, there are diverse motivations among consumers that drive brand loyalty. Forty-percent credit their loyalty to long-standing reputations, 30 percent say brand consistency is what brings them back, and 22 percent say it’s because of a brands iconic status. Yet, despite this loyalty, only 17 percent of consumers feel “truly valued,” leaving the majority wanting more.

Helping consumers feel truly valued is no small feat. Traditional reward redemption methods focus only on customers who actively join loyalty programs, and that is no longer enough. Brands are innovating loyalty programs to create a sense of nostalgia, community, and devotion that delivers a memorable experience through personalized offers across the entire life cycle and on every channel.

The new loyalty solution from SAP aims to equip organizations with experiential journeys and personalized, real-time offers to help earn customer loyalty through integration with the SAP Commerce Cloud, SAP Service Cloud, SAP Emarsys and SAP S/4HANA Cloud Public Edition, retail, fashion, and vertical business solutions. Key features that enable this are:

• Loyalty profiles that connect every shopper with a cloud-based loyalty wallet, facilitating targeted and personalized offers, entitlements, and real-time basket analysis
• Multi-brand loyalty management, as well as shared loyalty programs with partners that centralize loyalty programs across regions and markets, enabling combined brand programs for gaining market share
• A single place for omnichannel promotion planning with real-time redemption to deliver any type of offer, digital payment, and gifting to all customers on any channel
• Loyalty journey planning that delivers experiential omnichannel journeys tailored to customer needs through personalized commerce, marketing, service, and retail interactions
• Quantifiable metrics that track promotion performance and loyalty-related liabilities, linking to financial systems to measure ROI, and enable settlements with the member and partner brands

We are currently recruiting customers for a lighthouse program, and interested customers can learn more by contacting Yaron Gur-Ari. The solution is expected to be available in the second half of 2025.

Artificial Intelligence Makes Shopping Frictionless

We are also launching an AI shopping assistant to make e-commerce search and discovery a lot easier for customers.

Search abandonment is a real challenge. According to a 2023 Google research report, retailers face more than a $2 trillion loss when shoppers cannot find what they are looking for on a retailer’s website. And to add insult to injury, search challenges also serve a huge blow to customer loyalty, with 78 percent of consumers viewing brands differently and 82 percent of consumers saying that they would avoid websites where they’ve experienced search difficulties.

With the AI shopping assistant, users can now deliver that white-glove experience to their customers online. For industrial buyers, it acts as a technical specialist — helping source specific replacement parts, comparing complex specifications, and suggesting compatible components. For retail customers, it serves as a personal shopper — understanding style preferences, recommending complementary accessories, and answering detailed product questions.

The assistant seamlessly integrates with SAP Commerce Cloud through a flexible API, allowing users to easily plug it into new or existing storefront while maintaining the brand experience. With built-in security and support for multiple languages, it is designed to deliver sophisticated product discovery at scale.

The AI shopping assistant, as part of the SAP CX AI Toolkit, is available for early access now and will be generally available in March of 2025 for SAP Commerce Cloud customers.

Effortless Payment Service Integration

We previously announced a new composable payment solution, SAP Commerce Cloud, open payment framework, that helps retailers continue to scale and remain agile as new payment options gain popularity.

Open payment framework is a no-code, low-code framework that gives retailers a low-cost, adaptive, and agile payments system that can best fit their business and customer needs without the need to build out integrations on their own. Extensible and headless, the framework ensures that the front and back ends are decoupled and operate independently, catering to a wide range of requirements across channels and allowing customers to have the freedom to pick their preferred payment methods. It covers common payment needs and end-to-end payment processes across authorization, capture, refunds, and re-authorization as well as automatic updates with security and compliance standards. Open payment framework is natively integrated with SAP Commerce Cloud.

Open payment framework is planned for general availability on January 22, 2025. Customers can sign up for SAP Early Adopter Care program here.

Intelligent Search Service Makes Product Discovery Easier

The intelligent search service is a modern, multi-tenant SaaS solution designed to deliver seamless, AI-powered search experiences for both shoppers and business users. Key benefits that empower end-to-end commerce journeys are:

• Effortless product discovery for shoppers on the storefront with natural, intuitive search capabilities, enhanced by AI-driven verbatims, flexible indexing, and intelligent scoring. Features like smart word suggestions and personalized recommendations help showcase the most relevant products, improving navigation and driving higher satisfaction.
• Search operation management with ease for business users through back-office processes that enable data-driven merchandising strategies, powered by integration with intelligent selling services. This ensures measurable impact and optimization of search experiences.

By combining modern technology with AI, the intelligent search service maximizes conversion rates and product views, delivering a natural and intuitive shopping experience. It helps retailers not only enhance customer satisfaction but also build long-term loyalty and lifetime value.

The service is planned for general availability on January 22, 2025. Customers can sign up for SAP Early Adopter Care program here.

At SAP, we are committed to empowering businesses to deliver exceptional customer experience while driving profitable growth. By leveraging connected, insightful, and adaptive technology solutions, we help our customers put their customers at the center of their operations to build loyalty, foster innovation, and unlock new opportunities for success.

To learn more about SAP CX, visit sap.com/cx.

Balaji Balasubramanian is senior vice president and global head of Commerce and Industry Cloud at SAP.

A topic that has come up many times at the World Economic Forum Annual Meeting in Davos over recent years is the increasing fragmentation of our world — within societies and between nations. But, amid this division and disagreement, there is one hope that many still share: the belief that artificial intelligence (AI) will lead to significant progress across the globe.

From my work at a company that pioneers AI in business processes, I hold this hope too: AI has the potential to stimulate growth and make companies more productive. It can make economies more resilient by helping businesses navigate disruptions, whether through global trade crises, natural disasters, or regional conflicts.

AI can also play a critical role in our ability to achieve our sustainability goals, tackle climate change, and mitigate its impact. While many recognize AI’s positive potential, the growing fragmentation of our world greatly reduces our ability to take full advantage of the opportunities AI presents.

AI can only be as good as the data it can access and work with. The more restrictions, limitations, and political borders we impose on it, the less positive impact AI can have in our countries and companies. AI can’t thrive in a fragmented world. This is what I call the AI progress challenge.

Tackling the AI Progress Challenge, Step by Step

Finding solutions to something as vast and as complex as global fragmentation requires us to divide the problem into smaller, individual challenges that are easier to overcome. How can we make AI a stronger tool for progress? How can we navigate the AI progress challenge step by step?

1. Begin at company-level

It starts on our doorsteps — at the level of the individual company. Cloud migration is an integral first step. The cloud makes data accessible for AI, systematically and comprehensively, and cloud solutions can easily — even automatically — be kept up to date with the latest AI innovations. What is more, integrated cloud software offers a standardized environment for data and processes. It makes it easier for companies to keep their data structured, clean, and coherent across the company — and consequently easier for AI applications to use.

2. Create an industrial ecosystem

The second step toward maximizing the potential of AI is to bring individual companies together in an industrial ecosystem. To become more productive, resilient, and sustainable, companies need to exchange information with suppliers — sometimes thousands of them — as well as with their clients and innovation partners. In the age of business AI, the need to build intelligent business networks is more important than ever. The more broadly and widely data can be shared between companies, the better and more impactful AI outcomes can be. The whole ecosystem profits in terms of added competitiveness and innovation power.

3. Build international frameworks

The third step is to build international frameworks that allow AI innovation to thrive in a responsible way. Governments and regulators can reduce unnecessary barriers to the exchange of data within countries and between countries. In cooperation with industry, public actors can also work towards aligning and harmonizing technological regulations wherever possible, especially between the key economic powers of North America, China, and Europe.

At the same time, we must build trust. Lack of trust is perhaps the greatest driver of global fragmentation — and the biggest obstacle to collaboration. By joining forces, international companies can agree on common rules for data usage, data privacy, and responsible, ethical AI. Such “confederations of trust” encourage more frequent data sharing.

Putting the AI Puzzle Together

The cloud, business networks, and a more harmonized global environment based on trust; each of these steps reduces fragmentation and increases federation. And, each of these steps can help the organizations involved reap much greater benefits from AI.

It’s like putting together a 10,000-piece puzzle. It’s not easy to start with and it’s not something that can be accomplished in one go, but if we begin by putting a handful of pieces into place, the big picture gradually emerges. As the degree of federation increases, progress accelerates.

It’s on us to put the AI puzzle together and reduce fragmentation, one step at a time. This is how we maximize the potential of AI — not just for some, but for many.

Christian Klein is CEO of SAP SE.

This piece originally appeared on the World Economic Forum website.

Technological innovations such as artificial intelligence (AI) are reshaping entire industries and redefining the boundaries of what is possible. These advancements significantly boost productivity and help us reach new heights as societies.

According to the McKinsey Global Institute, AI could contribute between $17.1 and $25.6 trillion to the global economy annually, including $6.1 to $7.9 trillion from generative AI use cases alone.

Yet technology alone does not guarantee success in the Intelligent Age: People remain the true catalysts of innovation and growth. As businesses navigate rapid technological change, their ability to continually adapt, build resilience, and create sustainable growth depends on how well they interlock people, organizational development, and technological advancements. Together, this triangle forms a transformation engine that drives both individual and business growth, ensuring long-term success. It also helps organizations and individuals thrive and create a sustainable future.

Putting People and Skills First

Even in this high-tech era, people remain the driving force behind innovation and growth. In the Intelligent Age, skills are the new currency — encompassing the abilities, knowledge, and expertise that empower individuals to adapt and thrive in a rapidly changing world. Therefore, to bring out the best in their people, organizations must prioritize skills.

The skills-first approach is a paradigm shift that revolutionizes how organizations handle workforce planning, hiring, performance management, job architectures, learning and development, career pathing, as well as rewards — hyper-personalized and infused with AI. Putting skills at the center transforms people practices, products, and solutions across all stages of the employee life cycle.

In doing so, organizations create a people ecosystem centered on adaptability and growth. From skill-based job descriptions and skills assessments to prioritizing skills over experience and degrees when executing skill-based hiring, organizations can transform their people practices. This extends to skill-based learning and development, enabling cross-generational and regional development, internal mobility, recognition programmes, as well as career pathing and skill mapping from an organizational perspective.

This approach ensures that organizations attract and engage the right talent, provide individuals with personalized development opportunities aligned with organizational needs, and offer competitive rewards that recognize and incentivize skill growth and application.

A skills-led people ecosystem helps employees adapt quickly, almost in real time, to changing demands. Prioritizing skills allows organizations and employees to drive innovation and achieve sustained success. Ultimately, this approach will contribute to overall economic growth by ensuring a skilled workforce and sustaining high levels of employability.

Culture as the Organizational Foundation for Innovation and Resilience

Under the constant demand to transform, along with competition and geopolitical challenges, even the most resilient organizational cultures can be stretched. In the Intelligent Age, maintaining a strong culture requires continuous strategic attention and nurturing.

Businesses must instill a culture that encourages adaptability. An adaptive culture acts as an internal compass, guiding employees on how to work together, serve customers, and remain accountable for sustainable results. It guides decision-making through shared values and priorities, emphasizing a growth mindset for continuous learning and developing individual and organizational capability. This helps organizations adapt quickly to market changes, remain competitive, and foster innovation.

Leaders play a pivotal role here. By motivating teams, providing clarity and purpose, they create a cohesive workplace that empowers individuals and aligns their actions with the broader vision. The result is a unified effort where every team member contributes to shared goals, fuelling both performance and adaptability.

When culture is deeply rooted and intentionally nurtured, it aligns strategy execution with engagement from employees, partners, customers, and shareholders — strengthening commitment across all stakeholders and delivering consistent results.

People Technology Changing the Game

Technology helps organizations implement and amplify the impact of their people strategies. By leveraging the power of mega data and AI in the people sphere, companies foster data-driven and transparent decisions, a critical prerequisite for workforce transformation and future success.

Mega data and AI help organizations predict workforce trends, identify skill gaps, and improve talent insights and mobility, leading to more efficient team setups and equal opportunities to employees. This enables superior business outcomes based on a holistic and transparent view of employee capabilities and insights — available to all relevant decision-makers.

Technological advancements also allow unprecedented levels of personalization, making hyper-personalization a key focus in the people sphere. From targeted, skill-based learning programs to individualized career paths, AI-enabled tools can tailor experiences to each person’s needs, offering clear growth opportunities and driving engagement by making employees feel valued and supported in their development.

By using technologies like AI effectively and ethically, organizations will be more adaptive going forward — enabling quick pivots to meet external demands and build resilience.

By interlocking people, organizational development, and technological advancements, businesses create the foundation to continually innovate, adapt, build resilience, and drive lasting growth. This holistic approach helps organizations and individuals thrive in the future, ultimately contributing to a better tomorrow.

As we stand on the brink of the Intelligent Age, it is vital that businesses reimagine their strategies with people at the center. Together, we can create organizations that serve as engines of innovation and resilience — ready to lead us into a people-centered, growth-focused, and sustainable future.

Let us seize this moment to ensure that the Intelligent Age is defined not only by technological progress but also by how it uplifts humanity.

Gina Vargiu-Breuer is chief people officer and labor director, as well as a member of the Executive Board of SAP SE.

This piece originally appeared on the World Economic Forum website.

Two major forces are driving rapid shifts in the modern enterprise: growing complexity, which can often feel overwhelming, and generative AI, the disruptive technology that promises to tame it.

From supply chain disruptions and shifting regulations to the struggle of attracting and retaining top talent, enterprises must navigate an ever more challenging environment. Meanwhile, AI has forever changed the game for business.

Though its potential to streamline operations and spark innovation is extraordinary, it demands more than a simple overlay on siloed, legacy systems. Realizing AI’s promise requires a fundamental shift in how people, applications, and data connect to tackle challenges and seize new opportunities.

Beyond Siloed Systems

The tension between escalating complexity and AI’s transformative power is redefining modern business. The days of relying solely on transactional systems or standalone intelligence are behind us; modern enterprises demand much more. Companies today seek an integrated business suite that unifies processes, harmonizes data, and leverages AI agents to tackle challenges and seize new opportunities.

Achieving this level of interconnection calls for a fresh approach to enterprise management — one that brings together three critical capabilities:

• End-to-end process integration that generates and relies upon trusted business data. McKinsey calls this an integrated technology operating model and says this “can help [organizations] build deeper relationships with customers, launch new business models, make processes more efficient, and make better decisions.”
• Harmonized data to fuel AI-driven insights. Data harmonization brings together all data — internal and external — so it can be managed more efficiently, analyzed, and used to guide business decision-making. Harmonizing data within an organization minimizes redundancies, improves data governance, serves as a single source of truth, and makes better use of scarce resources.
• AI that goes beyond basic automation and breaks down silos, driving real-time, cross-enterprise optimization. In other words, companies need AI that not only performs repetitive tasks but also actively analyzes data, learns from new information, and makes intelligent, actionable recommendations.

Real World Impact: BSH and MOD Pizza

By design, SAP software connects an entire organization to drive results grounded in enterprise data and in the context of business processes. This integrated approach is already delivering measurable results.

Global home appliance leader BSH is a company that already benefits from this approach, offering more than 10,000 products to 50,000 trade customers in over 50 markets. BSH achieved supply chain transparency, optimized inventory, facilitated on-time delivery, and enhanced customer experiences by synchronizing planning and execution across its extensive supply chain.

Another example is MOD Pizza. The company supports equitable opportunities and business growth by automating HR and streamlining onboarding for 1,000 new hires monthly, managing as many as 400 changes to employee data every day. Systems integration saved HR admins 15 hours per week in data entry alone.

These examples demonstrate that complexity can become a catalyst for progress — provided the right applications, data, and AI tools are in place. When these elements work in unison, the outcome is greater than the sum of its parts: a business that’s not just agile, but unstoppable.

Embracing the Next Era of Enterprise Management

We are entering a new era of enterprise management where AI agents collaborate to solve long-tail business tasks, redefining how the world does business. SAP is ready to help our customers by bringing together applications, data, and AI like never before.

Business leaders can ensure their companies not only survive but thrive by swiftly adapting to an ever-changing environment.

Thanks to AI, the systems we’ve always envisioned — where data flows freely, processes are fully connected, and decisions are backed by precise, real-time insights — are now within reach.

Jan Gilg is president and chief product officer for Cloud ERP at SAP.

This piece originally appeared on SAP BrandVoice on Forbes.

The technology space—and the business world—are changing rapidly. The race to explore and capitalize on AI’s potential is accelerating that change even more. However, businesses can only realize AI innovations if they transition from on-premise systems to the cloud to leverage the unparalleled speed and agility they offer.

SAP’s vibrant ecosystem of over 25,000 partners and SAP PartnerEdge open ecosystem members helps ensure customers are supported and thriving across the entire customer journey. These trusted partners share SAP’s vision of helping companies bring our their best and can be the catalyst to true business transformation. Partners apply their deep technical expertise and business experience to build on, sell, service, and run SAP’s leading cloud ERP and AI solutions.

Recognizing this and the need to empower partners to set the right foundation for the cloud, SAP is revamping SAP PartnerEdge—its flagship, global program to engage with partners, no matter their route to market. The program, now 100% cloud-focused, is designed to help recognize and elevate partners that are ready to support customers in the cloud-powered AI economy.

A Closer Look at the Changes Coming in 2025

Prioritizing partners that are in lockstep with SAP’s vision to drive business growth and customer value, we are focusing on the following key pillars for the SAP PartnerEdge program in 2025:

• Aligning with SAP’s cloud vision: We’ve redesigned the program with elements that support and incentivize partners to reflect SAP’s strategic cloud focus. This helps differentiate partners that are fully aligned with SAP’s direction.
• Deepening SAP expertise: Under the new framework, expertise plays an even stronger role in determining partner levels. Competencies and specializations—focused on cloud solutions from SAP—serve as benchmarks of a partner’s maturity and credibility. These also signal to customers that they can trust a partner’s expertise in areas most critical to their business.
• Championing AI adoption: To meet the AI moment, partners are further motivated to innovate on tools that can lower the bar to entry for customers to leverage AI technologies. From no-code simplicity to advanced customization, partners are encouraged to build on SAP’s embedded AI portfolio and create tailored solutions that meet our customers’ unique needs.
• Committing to customer value: Long-term success for our customers is our top priority—and it holds true weight in our partner program as well. By prioritizing solution adoption-led growth, aligning delivery practices to SAP’s cloud methodologies, and delivering measurable outcomes, partners can create lasting value throughout the customer lifecycle, ultimately propelling their partnership too.

An Approach Endorsed by Industry Experts

These changes to the SAP PartnerEdge program signal our deepened commitment to the cloud, AI innovations, and, most importantly, our customers and their success. Industry experts agree, highlighting the drivers behind this transformation and SAP’s proactive approach:

“The convergence of cloud and artificial intelligence is ushering in a new era of business innovation,” said Dave McCarthy, research vice president, Cloud and Edge Services at IDC. “This synergy is driving transformative advancements across industries.”

“SAP understands this shift and is actively taking steps to ensure its partner ecosystem is aligned and paving the path for businesses to leverage breakthrough innovations,” added Steve White, program vice president, Channels and Alliances at IDC.

Supporting Customers to Find Their Best-Fit Partner

Under our new program framework, SAP and partners will be able to experience increased synergy as they move forward focused on the cloud and AI. However, customers will see the greatest benefits. While SAP PartnerEdge is designed for partners, its goal is to ultimately create a robust ecosystem that has the experience, knowledge, and specialization to address the unique needs of all of our customers and create a blueprint for long-term success.

For businesses ready to find their best-fit partner, SAP Partner Finder can provide easy search functionality to quickly find partners that match their industry, line of business, or size. It also showcases each partner’s level, competencies, and unique qualifications, such as the GROW with SAP partner designation. 

For customers to find success in the AI-driven era—and to thrive with the pace of innovation it brings—partnerships are more crucial than ever. By combining partner expertise with the power of SAP’s robust portfolio of cloud solutions, AI technologies, and data capabilities, customers can capitalize on this exciting moment as they transform their business.

SAP encourages businesses to explore our ecosystem of partners today and take the next step towards business transformation, greater competitiveness, and growth.

Karl Fahrbach is chief partner officer at SAP.

Artificial intelligence (AI) is accelerating at an astonishing pace, quickly moving from emerging technologies to impacting how businesses run. From building AI agents to interacting with technology in ways that feel more like a natural conversation, AI technologies are poised to transform how we work.

But what exactly lies ahead? We’d like to share five key themes for AI in 2025 that undoubtedly come with challenges for businesses but also the potential to redefine what’s possible. Ready to glimpse into next year and beyond? Let’s dive in.

1.  Agentic AI: Goodbye Agent Washing, Welcome Multi-Agent Systems

AI agents are currently in their infancy. While many software vendors are releasing and labeling the first “AI agents” based on simple conversational document search, advanced AI agents that will be able to plan, reason, use tools, collaborate with humans and other agents, and iteratively reflect on progress until they achieve their objective are on the horizon. The year 2025 will see them rapidly evolve and act more autonomously. More specifically, 2025 will see AI agents deployed more readily “under the hood,” driving complex agentic workflows.

Users will interact with a copilot for their tasks, which will deploy the request and coordinate among systems of multiple expert AI agents to complete more difficult tasks. Future AI agents, or multi-agent systems (MAS), can collaborate to understand the business user, have all the context, and structure the problem to subsequently interact with these domain-specific expert AI agents — each performing specific sub-tasks that together complete a much more complex task. In the future, users will not even need to trigger an action. Instead, AI agents will proactively respond to business events such as incoming customer inquiries, supply chain disruptions, or demand surges. They will automatically prepare a decision workflow as far as they can before pinging the human user for feedback.

If we look at a five-year horizon, AI agents will simplify significant portions of workflows, even aspects that have been resistant to automation, such as exceptions in customer service, long-tail administrative tasks, and specific programming activities like coding or debugging software. AI agents will be flexible and can plan, fail, and try something else or self-correct based on reasoning. AI agents will handle and complete routine, repetitive tasks end-to-end as effectively and often even more effectively than humans, leading to increased productivity and demonstrable cost savings. Agents will be more adaptable and robust than conventional robotic process automation (RPA) for longtail and highly extensive tasks. This means figuring out the best result out of many possible outcomes, which is almost impossible to hardcode in an RPA algorithm with classical automation methods.

Adopting AI in these domains will also shift workforce dynamics, with human roles evolving to focus on anticipating uncommon scenarios, coping with ambiguity, factoring in human behavior, making strategic decisions, and driving genuine innovation — complemented, not replaced, by AI capabilities. 

In short, AI will handle mundane, high-volume tasks while the value of human judgement, creativity, and quality outcomes will increase.

2. Models: No Context, No Value

Large language models (LLMs) will continue to become a commodity for vanilla generative AI tasks, a trend that has already started. LLMs are drawing on an increasingly tapped pool of public data scraped from the internet. This will only worsen, and companies must learn to adapt their models to unique, content-rich data sources. Model improvements in the future won’t come from brute force and more data; they will come from better data quality, more context, and the refinement of underlying techniques. Companies must spend more time innovating to make better models through fine-tuning and model adaptation rather than just training larger and larger models. Neurosymbolic AI techniques, especially knowledge graph, will see a renaissance since they can provide both learning objectives for foundation models and context to significantly improve the performance of generative AI while reducing hallucinations.

We will also see a greater variety of foundation models that fulfill different purposes. Take, for example, physics-informed neural networks (PINNs), which generate outcomes based on predictions grounded in physical reality or robotics. PINNs are set to gain more importance in the job market because they will enable autonomous robots to navigate and execute tasks in the real world, from warehouses to manufacturing plants, or models trained on tabular, structured data, like SAP Foundation Model, and can handle tasks that LLMs cannot do well, like predictions of numeric values.

Models will increasingly become more multimodal, meaning an AI system can process information from various input types. AI applications will eventually evolve into “any-to-any” modality solutions capable of understanding, processing, and reasoning across text, voice, image, video, and sensor data within a single model. In addition, smaller and more specialized LLMs with scalable finetuning techniques and the ability to work on any device will become more common, a trend that may lead to hyper-personalized models for organizations or even individuals in the future.

Enterprises will shift toward strategies utilizing multiple foundation models (not to be confounded with multimodal capabilities in a single model, described above), leveraging a diverse set of AI models and techniques tailored to specific use cases. This is backed by the trend of fine-tuning small slices of models, which requires fewer resources and much less data, resulting in full model flexibility and enabling businesses to extract more value from their unique data and gain a competitive edge. Enterprise software vendors will offer or extend integrated AI model marketplaces and platforms that support seamless model deployment, management, and updating. Benchmarking and lowering model switching costs will help deploy the same use cases in heterogeneous environments. Context equals value. Knowledge graph technology has been around for 40 years and is now seeing a revival because it can overcome key LLM challenges, such as understanding complex formats, hierarchy, and relationships between business data. Knowledge graphs offer data meaning and explain the relationship between entities, significantly supercharging the abilities of LLMs. The next step in this journey will be large graph models, allowing further advancement in generative AI.

Implicit knowledge is power, and making knowledge explicit to others is a superpower.

3. Adoption: From Buzz to Business

While 2024 was all about introducing AI use cases and their value for organizations and individuals alike, 2025 will see the industry’s unprecedented adoption of AI specifically for businesses. More people will understand when and how to use AI, and the technology will mature to the point where it can deal with critical business issues such as managing multi-national complexities. Many companies will also gain practical experience working for the first time through issues like AI-specific legal and data privacy terms (compared to when companies started moving to the cloud 10 years ago), building the foundation for applying the technology to business processes.

From a technological perspective, while 2024 saw significant advancements in AI, 2025 will see companies focus on making these advancements more meaningful through seamless data integration, ultimately enhancing the accuracy and significance of AI-powered outcomes and boosting adoption. Lastly, in 2025, we might glimpse a shift in the software business model from building static software features and functions to an outcome-as-a-service model focused on achieving process objectives.

4. User Experience: AI Is Becoming the New UI

AI’s next frontier is seamlessly unifying people, data, and processes to amplify business outcomes. In 2025, we will see increased adoption of AI across the workforce as people discover the benefits of humans plus AI.

This means disrupting the classical user experience from system-led interactions to intent-based, people-led conversations with AI acting in the background. AI copilots will become the new UI for engaging with a system, making software more accessible and easier for people. AI won’t be limited to one app; it might even replace them one day. With AI, frontend, backend, browser, and apps are blurring. This is like giving your AI “arms, legs, and eyes.” While power users will still have singular, expert interfaces, most users will demand flexibility across multiple access patterns. At the same time, there will be a growing acceptance of longer inference times for high-quality answers to complex, previously unsolvable problems and actions in domains requiring deep analysis and research. Ultimately, users will recognize the trade-off between latency and complexity of tasks handled by AI.

Importantly, we will see organizations move beyond viewing AI as a collection of productivity tools and begin reimagining their workforce as a network of collaborative intelligence with AI agents and humans working to accelerate innovation within the enterprise. For example, combining human expertise in strategic thinking with AI’s strengths in large-scale analysis and pattern recognition will create new competitive advantages for companies that effectively orchestrate these hybrid intelligence networks to drive breakthrough discoveries and market opportunities. Next year will also mark the early stages of a significant shift in how humans and AI work together, with agents evolving into workflow partners, taking initial steps toward independently navigating software environments and automating routine tasks – from data analysis and report generation to schedule coordination and software testing. This will also start a longer journey toward transformed work processes and patterns, with forward-thinking organizations developing new roles, metrics, and training approaches for effective human-AI task collaboration.

5. Regulation: Innovate, Then Regulate

It’s fair to say that governments worldwide are struggling to keep pace with the rapid advancements in AI technology and to develop meaningful regulatory frameworks that set appropriate guardrails for AI without compromising innovation. The regulatory landscape will become even more fragmented, with the OECD AI Policy Observatory tracking hundreds of AI regulations under discussion worldwide. This requires evaluating model compliance with and technical interpretation of various regulatory frameworks.

In 2025, the discussion will shift from what we try to regulate from a technical standpoint to how we innovate and what we deem fundamentally human. This discussion will elevate the role of humans, contribute a much more positive perspective, and help shape a long-term vision for how we want humanity and AI to live and work together. 

In this environment, it will continue to be critical for companies developing and deploying AI technology to adhere to responsible principles around safety, security, and ethical use. This will also help set the stage for important precedents and compliance.

Executing on the Themes in 2025

Indeed, these are just a few of what we are sure will be many exciting advancements for AI in 2025. Overall, the biggest takeaway from the year ahead will be making existing breakthrough technology more meaningful. We will see AI much deeper and almost invisibly embedded in consumer and enterprise applications and witness more advancements in how vendors and organizations that use these applications embed their individual contexts and data into AI seamlessly.

Getting to the point of leveraging AI generally, however, will require businesses to take advantage of a modern cloud suite with unified data access and harmonized data models to overcome data silos and fully benefit from AI innovation that spans across the whole enterprise. This will drastically increase the accuracy and significance of AI-powered outcomes, ultimately boosting adoption, specifically in the enterprise space.

We can’t wait to see what the future holds.

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

According to the latest research from SAP and Oxford Economics, only 57% of business transformations end up being worth the time, money, and effort they require — but this can change.

Today’s business transformations are diverse, ranging from creating new products or services and entering new markets to adopting cybersecurity frameworks and transitioning to net-neutral carbon emissions. However, these transformations are neither swift nor inexpensive, and sometimes the costs can be hidden.

That is why SAP has partnered with Oxford Economics on a new and comprehensive survey of large organizations, providing an exclusive look at the current global state of business transformation.

“The Estimation Game: What Do Business Transformations Really Cost?” reveals the true cost of business transformation, with the data aimed at helping organizations maximize transformation success and take the guesswork out of transformation budgeting.

Spanning a range of industries and focusing on companies with a minimum revenue of $500 million, the report provides insights from a balanced audience of 800 respondents, including IT professionals and leaders from corporate strategy, R&D, finance, manufacturing, HR, and operations.

The paper further reveals that:

• Barely half of transformations go according to plan (51 percent)
• Fifty-eight percent of transformations end up going over budget
• The average cost of transformation efforts is €9.5 million
• Sixty-three percent of respondents face resistance from leadership regarding the value of transformation efforts
• Nearly half of the initiatives highlighted by respondents remain incomplete, and budgetary constraints pose a significant challenge

From Strategy to Execution

In broad terms, this disconnect between the confidence level of respondents and what the report data reveals about the true cost and organizational impact of transformation can be understood in the equivalent disconnect between strategy and execution.

For example, while three in five say their major transformation plan was well communicated across their organization, only 53 percent say it was clearly defined in the first place.

While most companies are employing strategic practices such as crafting mission statements, appointing dedicated leaders, and forming cross-functional teams, they can lack the final piece of the puzzle when it comes to converting strategy into action. That is where SAP comes in.

“Transformation challenges will always exist, particularly in aligning execution with strategic road maps,” Dee Houchen, head of Marketing for SAP Signavio and SAP LeanIX, shared. “As companies navigate these complexities, the path to successful transformation remains a critical focus for global businesses, which is why this research is so relevant.”

“SAP Signavio and SAP LeanIX solutions offer clarity and transparency in business transformation, helping organizations leverage enterprise analytics and process data to really turn transformation plans into action through supporting decision-making, setting timelines, and tracking progress effectively,” Houchen said. “This report is an invaluable resource for anyone wondering why their transformation efforts have slowed, what they can do differently, and how others have identified and overcome similar hurdles to their own.”

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