Global food & beverage operations run on many plants, systems, and regulations, but decisions can’t wait on disconnected data and metadata.
Doehler uses SAP Business Data Cloud to unify worldwide operational and quality data, accelerate modeling, and deliver precise insights to the business. opening the door to AI and machine learning.
Learn more about SAP Business Data Cloud 👉 https://sap.to/6056hbixK
Scaling AI value across the enterprise is hard, unless it’s built to work across teams, systems, and functions.
In this video, see how Joule simplifies AI adoption by creating a consistent experience that inspires everyday use, woven into the systems employees already use and interoperable with third-party AI. Joule also delivers ready-made AI agents for every core function, powered by built-in business process expertise, so teams can collaborate cross-functionally and break through silos.
And when you need something tailored, Joule helps speed up custom agent builds with simple tools to define business context and connect to your systems, so you can move from AI vision to real business value faster, with reliable performance at scale.
Meet the SAP S/4HANA Cloud 2602 release, new AI-enhanced innovations designed to connect applications, data, and AI so teams can run faster, work smarter, and act with greater confidence.
This update introduces finance innovations designed to work end to end, including an accounting accruals agent that automates major parts of the accrual process to help teams close faster with greater accuracy and less manual effort. As of 2026, SAP Green Ledger embeds carbon border adjustments into finance processes to support carbon liability tracking and certificate management with smart automation and compliant insights from day one.
You’ll also see enhancements for margin and profitability analysis, with improved review booklets that add comparisons and AI insights to surface optimization opportunities.
Chapters:
00:00 – Apps, data & AI on one foundation
00:23 – 2602 release overview
00:51 – AI-driven financial close (accruals agent)
01:17 – Green Ledger & carbon border adjustments (2026)
01:37 – Margin & profitability enhancements
01:56 – Joule: natural language insights
02:09 – Billing & revenue recognition updates
02:30 – Sales productivity enhancements
02:53 – Wrap-up
Learn more about financial management with SAP: https://sap.to/6054hP2XY
As enterprises move deeper into large-scale AI adoption, the conversation is shifting from experimentation to impact. Leaders are looking for outcomes they can trust, decisions that are consistent, and experiences that truly work for customers.
In 2026, AI earns its place when it is anchored in the realities of the business, shaped by enterprise data, processes, and lived customer interactions. Customer-specific AI brings intelligence directly into day-to-day operations, helping teams navigate complexity and support better decisions at scale while keeping human judgment firmly at the center. This is the shift shaping the next phase of AI adoption, moving from generic tools to intelligence that understands the business and grows stronger with every customer interaction.
1. Relevance beats raw intelligence in customer decisions
As AI becomes more central to customer-facing decisions, accuracy and relevance become non-negotiable. Generic models often lack the contextual understanding needed to interpret nuanced, exception-heavy customer scenarios. Customer-specific AI, trained on enterprise data, can recognize patterns unique to the organization—such as recurring dispute types, resolution bottlenecks, or region-specific service behaviors. According to SAP’s “Value of AI” report in collaboration with Oxford Economics, 36% of businesses say AI has already helped them address customer-related challenges, including improving customer engagement. This impact is strongest when intelligence reflects how customers actually interact with the business, rather than abstract assumptions.
2. Scaling complexity without losing control
Solve business challenges with innovations aligned with suite-first and AI-first strategies
Customer-specific AI proves most powerful where customer processes scale faster than manual intervention can keep up with. Returns, exchanges, dispute resolution, claims handling, and service exceptions span multiple systems, rules, and decision paths. AI that understands enterprise context can scale these processes without compromising consistency, governance, or accountability—enabling organizations to handle growing volumes while maintaining predictable outcomes and service quality.
3. Differentiation that compounds over time
Unlike generic AI capabilities that are broadly accessible, customer-specific AI is shaped by proprietary data, policies, and institutional knowledge. Over time, this creates intelligence that becomes deeply aligned with how the business operates—and increasingly difficult for competitors to replicate. The more the system learns from real customer interactions, the more it compounds as a durable source of differentiation.
4. Where customer-specific AI proves its value, from theory to practice
The impact of customer-specific AI is most visible in high-volume, exception-driven environments. A large European manufacturing and consumer goods organization illustrates this well through its approach to dispute, returns, and exchanges management. Operating across regions and product lines, the company faced long resolution cycles, inconsistent outcomes, and heavy manual effort. By deploying AI trained on its own historical disputes, order data, pricing rules, and resolution workflows, the organization embedded intelligence directly into its processes. Incoming claims were automatically classified, relevant documentation was surfaced, and resolution recommendations were generated based on prior outcomes and policies. Cases were routed efficiently, reducing back-and-forth and manual effort. Crucially, the system evolved with policy changes and customer behavior—augmenting human decision-making rather than replacing it. The result was a faster, more consistent, and scalable approach to managing customer disputes.
5. A cross-industry shift toward embedded intelligence
These principles extend well beyond dispute management. In manufacturing and supply chains, customer-specific AI supports fulfillment exceptions and service-level disputes. In financial services, it enables complaint handling aligned with regulatory frameworks. In healthcare, it supports decisions grounded in institutional protocols and patient journeys. In retail and services, it drives relevance by learning customer preferences, brand rules, and operational constraints. Industry observers increasingly note that AI’s next phase of growth will be driven by intelligence embedded into customer-facing processes—not stand-alone tools. According to SAP’s “Value of AI” report with Oxford Economics, the majority of businesses expect AI to become central to business processes, decision-making, and customer offerings by 2030, with only 3% saying otherwise.
In 2026, enterprises will judge AI less by novelty and more by its ability to deliver consistent customer and business outcomes. Customer-specific AI sits at the center of this shift because it weaves intelligence directly into how organizations operate and serve customers. This next stage of AI is not about removing human judgment—it is about strengthening it. By absorbing complexity and surfacing context-aware insights, customer-specific AI enables faster responses, greater consistency, and confident scaling of customer-centric decision-making. In an increasingly complex and customer-driven landscape, the true edge will belong to enterprises that invest in intelligence that genuinely understands their business.
Sindhu Gangadharan is head of Customer Innovation Services and managing director of SAP Labs India.
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Great service isn’t just faster — it’s smarter and more human.
SAP’s Scott Nelson explains how AI can help teams resolve issues and earn loyalty.
Learn how to accelerate service growth: https://sap.to/6053CrB4F
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Extended Producer Responsibility is a process that encourages companies to design more sustainable and recyclable products and manufacturing processes. It means companies are responsible for their products from the day they’re made to the when they are recycled or disposed of.
SAP Solutions can help you track this process, streamline it and properly grasp the opportunity that EPR offers.
What is extended producer responsibility (EPR)? https://sap.to/60507x0Ap
ASUG links live with SAP TechEd 2025! Hear community insights on AI, skills, and how to free up time to innovate with SAP.
In this highlight clip from SAP TechEd, ASUG connects live from Louisville to share what’s top-of-mind for the North American SAP community. You’ll hear how customers and practitioners are navigating real-world change: accelerating transformation while balancing skills, governance, and the growing role of AI.
The conversation captures the mood on the ground: less hype, more hands-on value. Speakers discuss how AI is in every conversation, the optimism (and anxiety) around changing roles, and a practical question: how do we put AI to work to make developers’ lives easier? You’ll also hear why skills and continuous learning are essential to deploy new technologies smoothly and deliver business impact, along with a look ahead at emerging areas (from UX to quantum and robotics) that will shape SAP landscapes over the next two years.
If you’re an IT leader, architect, or SAP practitioner, use this clip to brief stakeholders, focus enablement plans, and identify where ASUG community knowledge can help you move faster, without compromising on clean core and enterprise governance.
Speakers:
Geoff Scott, Chief Executive Officer, @ASUGtv
Muhammad Alam, Member of the Executive Board of SAP, SAP Product & Engineering
00:02 – Louisville: ASUG Tech Connect sync
00:49 – Why this Tech Connect matters: tech acceleration & community
01:08 – Today’s reality: AI pace, uncertainty & professional upskilling
01:41 – Less hype, more help: put AI to work for developers
02:31 – Skills & learning first; emerging tech and freeing time to innovate
Watch all SAP TechEd replays: https://www.sap.com/events/teched.html
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About SAP:
As a global leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit: https://www.sap.com/
The IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of technology and suppliers in a given market. The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each supplier’s position within a given market. The Capabilities score measures supplier product, go-to-market and business execution in the short-term. The Strategy score measures alignment of supplier strategies with customer requirements in a three to five year timeframe. Supplier market share is represented by the size of the icons.
According to the IDC MarketScape, “AI-enabled tools are revolutionizing field service management, transforming reactive operations into predictive excellence.”
SAP was recognized for the following strengths:
End-to-end field service management offering as part of the full enterprise suite: SAP Field Service Management is a fully integrated component of the SAP Business Suite, enabling end-to-end business process execution across planning, logistics, operations, finance, and customer service. It connects seamlessly with core SAP solutions such as SAP S/4HANA, customer experience, asset management, and supply chain management, ensuring that service delivery is fully aligned with enterprise-wide processes. This deep integration eliminates silos, enables real-time collaboration across departments, and supports consistent, efficient service execution across the entire value chain.
AI innovations and generative AI capabilities: SAP Field Service Management is infused with AI and generative AI to simplify and accelerate service delivery. SAP is able to support generative summaries of equipment history, work orders, and past service activities. SAP has established an embedded AI copilot for field service that enables users to execute commands, automate actions, and retrieve context-aware insights using conversational language with the benefit of boosting productivity and responsiveness across the service life cycle. SAP also has a robust auto-scheduling engine designed for complex, high-volume service operations.
Commitment to continuous innovation
Field service organizations face growing complexity, workforce shortages, and rising customer expectations that demand smarter, faster, and more connected service delivery. SAP continues to lead the market by integrating AI-driven insights, intelligent automation, and end-to-end connectivity across its portfolio.
SAP remains focused on enabling customers to:
Boost technician and dispatcher productivity
Drive customer-centric and revenue enabling operations
Reduce operational costs and accelerate complex workflows via intelligent automation and AI
Provide a connected and extensible platform for field service
SAP is proud to be recognized by the IDC MarketScape as a Leader in AI-enabled field service management. We remain committed to helping our customers run their service operations smarter, safer, and faster — combining data, applications, and AI to deliver measurable business outcomes and exceptional customer experiences.
Developers aren’t being replaced, but AI is making them faster. In the SAP TechEd opening keynote, SAP leaders demonstrate how builders can utilize the SAP Business Technology Platform (BTP) to transform ideas into secure, scalable outcomes. You’ll see how the app–data–AI flywheel comes together: best-in-class applications generate a governed data layer that powers intelligent agents and experiences.
The keynote highlights an open, choice-driven developer experience, featuring local SAP Build servers, a new VS Code extension, Model Context Protocol (MCP) support, and zero-copy sharing across SAP Business Data Cloud—now enhanced with a Snowflake partnership. It also introduces SAP-RPT-1, a relational foundation model purpose-built for tabular business data, enabling faster and higher-quality predictions without the need for bespoke models.
For building and operating AI at scale, SAP showcases ready-to-use and extensible agents, low-code Agent Builder, pro-code agents using the SAP Cloud SDK for AI, agent interoperability via the A2A protocol, plus lifecycle governance with Agent Hub and Agent Mining. You’ll also see intent-based development (“vibe coding”) across SAP Build and VS Code—including ABAP in VS Code and an SAP-tuned ABAP-1 model for developer productivity.
Customer stories from Uniper and Sartorius ground the tech in real outcomes, including a live warehouse demo with robots orchestrated by Joule. The session closes with a look at quantum optimization in partnership with IBM—pointing to a future where classical, AI, and quantum computing work in concert on real business problems.
Speakers:
Philipp Herzig, Chief Technology Officer, SAP
Michael Ameling, President, SAP Business Technology Platform, SAP
Muhammad Alam, SAP Product & Engineering, SAP
Geoff Scott, CEO & Chief Community Champion, @ASUGtv
Torsten Müller, CIO & Head of Operations, @SartoriusGlobal
Dr. Axel Wietfeld, Chief Procurement Officer, @UniperEnergy
00:00 – Opening: why builders matter
02:11 – Live link to Louisville & community pulse
09:29 – Developers in the AI-native era
11:02 – SAP app–data–AI flywheel on BTP
12:50 – Business Data Cloud updates + Snowflake
15:46 – Introducing SAP-RPT-1 (tabular AI)
35:23 – Demo: pipeline predictions with SAP-RPT-1 + HANA Cloud
41:42 – Benchmark engineering, Prompt Optimizer & AI for Europe
46:19 – Agents across LoBs; extensibility with Agent Builder
53:24 – Pro-code agents with SAP Cloud SDK for AI
1:01:29 – Agent interoperability (A2A), Agent Hub & Agent Mining
1:10:01 – Intent-based development (“vibe coding”) demo
1:20:12 – Customer story: Uniper procurement transformation
1:34:21 – Robotics warehouse demo orchestrated by Joule
1:46:01 – Quantum optimization with IBM & closing remarks
Watch all SAP TechEd replays: https://sap.to/60577zqy5
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About SAP:
As a global leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit: https://sap.to/60567zqyo
This week at SAP Connect, SAP unveiled the latest innovations designed to help companies build stronger, more meaningful relationships with their customers. In today’s world, customers expect intelligence, precision, and trust at every step of their journey.
Deep research AI and role-based assistants, coupled with SAP Business Suite innovations, take efficiency to new heights
SAP’s latest customer experience solutions are built to deliver on these expectations, empowering organizations to earn loyalty, drive growth, and create seamless, connected experiences.
In today’s market, loyalty and retention are the twin engines of repeatable business, the lifeblood of every organization. Earning and keeping customer trust has always been hard-won, but the bar is higher than ever. Recent findings from the SAP Emarsys Customer Loyalty Index show a five-point drop in “true loyalty,” customers who return without incentives. Only 35 percent of B2B customers reach strategic loyalty, defined as repeat purchases and long-term engagement. And nearly one-third of customers are lost to fragmented experiences. Brands now face a new reality: building lasting loyalty requires understanding customers and delivering consistent, connected experiences across every touchpoint.
Meeting the loyalty challenge: SAP Engagement Cloud and SAP Customer Loyalty Management
Yesterday at SAP Connect 2025, SAP Executive Board Member Muhammad Alam shared the vision for SAP Engagement Cloud as the next evolution in enterprise engagement. Built on SAP Business Data Cloud and the SAP CX suite of applications, it orchestrates engagement across the enterprise: customers, suppliers, employees, and more.
It also connects every function — finance, HR, marketing, and service –– and uses AI to turn business data into actions that drive outcomes: better delivery, faster service, and stronger loyalty. SAP Engagement Cloud will unify real-time interactions across marketing, commerce, sales, and service. By connecting every customer touchpoint to operational data such as logistics, finance, and supply chain, organizations can deliver accurate offers, real-time service, and personalized experiences at scale. This is especially important as only 18 percent of B2B customers reach strategic loyalty, according to the SAP Emarsys Customer Loyalty Index.
With embedded AI and Joule, SAP Engagement Cloud automates decisions, accelerates campaigns, and supports multi-brand, multi-region operations, empowering teams to deliver consistent, predictive, and unified customer experiences from day one.
The solution will be beta in November 2025 and is expected to be generally available in the first quarter of 2026, with an initial focus on customer experience.
SAP Engagement Cloud
SAP Customer Loyalty Management empowers teams to deliver personalized experiences at scale by giving every customer a single loyalty profile, no matter the brand, region, or partner. With loyalty data unified and natively integrated into SAP Private Cloud ERP and SAP Business Suite, teams can instantly monitor promotions, track reward usage, and understand financial impact in real time. This actionable insight feeds directly into planning, forecasting, and supply chain decisions, enabling businesses to adapt quickly and serve customers better.
Loyalty isn’t a separate marketing project, it’s woven into daily business operations. By centralizing loyalty data, SAP Customer Loyalty Management helps organizations understand each customer deeply and deliver consistent, connected experiences across every touchpoint.
The solution will be available Q4 2025.
SAP Customer Loyalty Management
AI and intelligence: the next imperative
At SAP Connect, we introduced how Joule, SAP’s AI copilot, is transforming customer experience by embedding intelligence directly into SAP Business Suite. Joule is not another layer, it’s built into the foundation, enabling smarter decisions and faster execution across every customer moment.
AI assistants in Joule bring role-based intelligence to customer-facing teams across service, sales, marketing, and commerce. Each assistant is tailored to the user’s role and business context, coordinating a network of AI assistants within Joule to automate tasks like resolving cases, chasing invoices, optimizing catalogs, and surfacing insights. This orchestration enables teams to focus on driving outcomes rather than managing operations.
For instance, Digital Service Agent delivers fast, multilingual support by reasoning over customer context and company knowledge. It provides accurate answers, escalates when needed, and continuously improves, reducing manual workload and enhancing customer satisfaction. This is available now.
Digital Service Agent
Deep research in Joule
With deep research in Joule, account planning moves beyond quick answers, delivering deep, strategic research and analysis in a single, connected experience. By tapping into SAP data, external intelligence, and trusted resources, users get richer insights for any business need.
Sales leaders and chief revenue officers can use the new account planning that leverages deep research in Joule to compress weeks of manual work into days. It synthesizes customer history, identifies key drivers, and drafts account plans, giving sales teams a complete, real-time view of every relationship.
Deep research in Joule will be available in beta December 2025.
Account Planning Deep Research
Intelligent applications for customer experience
SAP Business AI also powers intelligent applications that help businesses turn data into action:
Revenue Intelligence brings together data from CRM, commerce, and ERP to surface pipeline risks, customer health, and sales performance. Sales leaders and chief revenue officers gain a unified, real-time view to strengthen pipelines, improve win rates, and accelerate profitable growth.
Consumer Products Intelligence enables manufacturers and consumer packaged goods companies to optimize trade promotions and customer-facing offers. Integrated with SAP Integrated Business Planning and SAP Analytics Cloud, it uses real-time data from sales, supply chain, and production to analyze margins, monitor performance, and support financial planning, ensuring CX strategies are aligned with operational realities.
These innovations are tightly integrated with SAP Business Suite, ensuring every CX insight is grounded in real-time, harmonized data. They are currently in restricted private preview and expected to be generally available in H1 2026.
Adoption that drives value
Building on the Customer Loyalty Index findings about the importance of connected experiences, seamless, guided adoption is essential to delivering value. That is why WalkMe is now embedded across all SAP Customer Experience solutions.
WalkMe is a digital adoption platform that provides real-time, role-based guidance – right inside SAP interfaces. No IT tickets required. Teams get help in the flow of work, with step-by-step instructions that minimize onboarding time and reduce errors. Leaders gain instant visibility into where users struggle, so they can address friction and accelerate adoption.
The path forward
Loyalty is evolving, and so are we. Our priority is to help brands earn trust and adapt quickly.
The SAP Customer Experience innovations introduced at SAP Connect are designed for this challenge. They connect engagement with execution through solutions like SAP Engagement Cloud, Revenue Intelligence, and SAP Customer Loyalty Management; turn intelligence into action with embedded AI and automation; and give teams unified, real-time data to deliver measurable results and stay ahead in a rapidly changing market.
