AI in S/4HANA

The growing integration of AI into SAP systems is a a major transformation. Customers are driven by the need for faster decision-making, increased flexibility, and compliance with complex regulations.

This article from IgniteSAP explores how AI and ML features within S/4HANA and supporting technologies are changing the working practices of SAP consultants. It also examines their real-world applications, availability, and the impact on consultancies and career development of individual consultants.

SAP’s Intelligent Enterprise Framework

SAP’s Intelligent Enterprise framework is a strategy for embedding AI and machine learning into its systems. At the center are tools like SAP AI Core and SAP AI Business Services, as the foundation for making enterprise systems smarter.

The strength of SAP’s ecosystem relies on how its intelligent features work together. For example, Joule offers easier navigation, but also simplifies user enablement by summarizing complex content. AI in SAP S/4HANA already connects efficiently with solutions such as SAP Ariba, SAP SuccessFactors, and SAP Customer Experience. These integrations break down operational silos, creating systems that use real-time data to respond in a connected and comprehensive way.

Within the Intelligent Enterprise framework, Intelligent Scenario Lifecycle Management (ISLM eases the deployment of machine learning applications, supports generative AI use cases, and integrates large language models. By including tools for prompt management, it facilitates the creation of AI-driven workflows, helping consultants address a range of client needs with minimal development.

By exploring features like SAP Business AI enhancements, which include predictive analytics and intelligent insights across decision-making and customer engagement, consultants can develop strategies that solve specific problems while also addressing broader enterprise objectives more quickly and easily.

AI, ML, and Intelligent Features in SAP S/4HANA

Here are some of the AI-powered and intelligent features now available in S/4HANA and connected solutions:

Joule can be used within S/4HANA, and by integrating with custom agents via Joule Studio in SAP Build, its capabilities will expand further in 2025.

Features like AI-Assisted Financial Insights, also known as the “Virtual Analyst,” provide real-time explanations of financial data, uncovering dependencies and suggesting actionable insights to improve decision-making. Also, AI-Assisted Configuration for US Tax Jurisdictions automates complex tax setups, reducing errors and accelerating processes: a vital tool for multinational companies.

Operational improvements of AI in S/4HANA extend to areas like error resolution and asset management. AI-Assisted Error Resolution translates technical error messages into clear language, offering guidance to resolve issues.

Predictive Maintenance uses AI to monitor equipment health and forecast maintenance needs, and by 2025, it will be complemented by AI-Enabled Visual Inspection for Asset Monitoring, integrating image recognition for precise assessments. Advanced Asset Health Monitoring with Embedded IoT will embed real-time insights into equipment performance, further supporting predictive maintenance scenarios.

User-centric tools like the AI-Assisted Easy Filter allow intuitive querying within SAP Fiori apps (Fiori being the primary interface for S/4HANA), simplifying data retrieval through natural language processing. AI-Assisted Smart Summarization has also been developed for simplifying decision-making by summarizing SAP Fiori object pages into actionable formats, enhancing productivity across teams.

Other custom AI solutions are gaining traction within Asset Performance Management. By enabling tailored AI models, businesses can address specific challenges beyond standard ERP functionalities.

Supporting Solutions for Intelligent ERP

The core of intelligent SAP ERP lies in platforms like the SAP Business Technology Platform. SAP BTP connects advanced analytics with core ERP processes, offering tools such as SAP Datasphere for managing data pipelines and SAP Analytics Cloud for predictive modeling. For example, SAP BTP also supports features like the Generative AI Toolkit for SAP HANA Cloud, which allows users to build time-series forecasts without extensive ML expertise. By using SAP BTP, consultants can create modular solutions tailored to specific client needs without changing the core system.

RISE with SAP and GROW with SAP are key offerings that simplify the adoption of intelligent ERP systems with S/4HANA at the center. These bundles include over 100 AI use cases, such as AI-assisted financial analysis, resource matching, and intelligent filtering, making it easier for businesses to adopt AI capabilities efficiently.

SAP’s integration with IBM Watson AI adds another layer of functionality, allowing automation of routine tasks and extraction of insights across business lines. Combined with other solutions, such as AI for Demand Forecasting and Inventory Optimization and AI in Invoice Management, this collaboration enhances operational efficiency across multiple domains.

AI’s Impact on SAP Consulting Practices

The integration of AI and ML into SAP’s ecosystem is redefining the role of consultants by shifting their focus from static configurations to adaptive, data-driven strategies. These innovations enable consultants to reimagine traditional workflows, making them more agile and attuned to business dynamics.

For instance, Conversational AI for Procurement simplifies supplier interactions and purchasing processes, helping consultants introduce smarter, faster workflows to their clients’ operations.

AI innovations are also accelerating SAP S/4HANA implementations themselves.

For example, the automation of routine tasks, such as error resolution through AI-Assisted Error Resolution or invoice handling with AI in Invoice Management, reduces the time required for system configuration and testing. These tools help consultants focus on higher-value activities, such as designing tailored solutions or strategizing long-term client goals.

Generative AI capabilities, like those embedded in Joule and supported by ISLM, assist in creating adaptive workflows that ease deployments and encourage rapid adoption among users.

Beyond operational enhancements, AI tools enhance the strategic value consultants bring to their clients. Predictive analytics in workforce planning allows consultants to align staffing requirements with organizational goals proactively. Similarly, Smart Recommendations for Sales Teams, which analyze historical data to optimize pricing and product strategies, help consultants position clients for competitive advantage.

These intelligent features enable consultants to deliver measurable value, often demonstrated through metrics such as cost savings, efficiency improvements, or enhanced customer engagement.

The role of consultants as strategic advisors has never been more critical. With AI driving deeper personalization and automation, consultants are expected to guide clients in leveraging these capabilities to achieve broader business objectives.

This requires technical expertise and a deep understanding of industry-specific challenges. There is a widening skills gap as more and more AI-based innovations are released, but for those that can integrate training into their schedules, this can substantially increase their ability to command premium salaries. Certifications offered through platforms like SAP Learning Hub equip consultants with the skills to navigate this evolving landscape, ensuring they remain at the forefront of innovation.

Considerations for Implementing AI in SAP Projects

Embedding AI into SAP S/4HANA projects involves overcoming technical and organizational hurdles. Data readiness is often a challenge, as machine learning models depend on clean datasets. Consultants play a crucial role in identifying gaps and ensuring data is properly structured for AI adoption.

Hybrid environments, where cloud and on-premise systems coexist, also require careful planning to maintain efficient data flow and processing.

User acceptance is another important factor, given the speed of innovation. While AI tools such as AI-Enhanced Fraud Detection or AI-Assisted Browsing of Knowledge Bases in Field Service Management provide clear operational benefits, resistance from users unfamiliar with these tools can hinder adoption. Change Management consultants will need to address these concerns through tailored training, and by emphasizing how AI complements rather than replaces human contributions.

Metrics such as reduced processing times, improved forecast accuracy, and enhanced customer satisfaction demonstrate the benefits of AI, and consultants need to become adept at tracking the impact of their AI-powered SAP solutions, measuring success by setting clear objectives and tracking outcomes

Future Horizons: What Could Be Next for AI in SAP S/4HANA?

SAP has made it clear at SAP Sapphire and SAP TechEd, that AI will continue to play a big role in the future of S/4HANA.

Tools like Joule and Joule Studio already show what’s possible with generative AI, and we may see these evolve into even smarter assistants through 2025. SAP has talked about using these tools to improve areas like supply chain management and decision-making.

Edge computing is another area SAP has highlighted, especially for industries like manufacturing and logistics. The ability to run AI on devices closer to where data is generated could mean faster insights, like catching defects on production lines in real-time. SAP Edge Services already supports IoT and analytics, so it seems likely that these features will expand.

SAP has also started talking about “autonomous ERP,” systems that can adjust themselves without much human input, which at this point seems a distant ambition, though features like Intelligent Scenario Lifecycle Management (ISLM) are steps in this direction. While fully self-managing ERP systems might still be a long way off, we can expect steady improvements that make S/4HANA more intelligent and adaptable.

Collaboration tools are also expected to improve, with SAP focusing on deeper integrations with platforms like Salesforce and Microsoft Azure. This could make it easier for businesses to connect their systems and use AI to reduce the workload of tasks like supplier management or data sharing.

SAP has also been vocal about its commitment to ethical AI, including making sure its systems are explainable, transparent, and aligned with regulations like the EU AI Act.

User experience will also continue to improve, with SAP focusing on personalization. Tools like Joule and enhancements to SAP Fiori are designed to make interfaces more intuitive and tailored to individual users. These changes could save time and make systems easier to use.

AI-driven tools that track carbon footprints and optimize resources are likely to expand. While these tools have huge potential, their success will depend on how extensively businesses use them to meet their sustainability goals.

SAP’s plans for AI in S/4HANA are ambitious, but they’re also grounded in projects that are already underway. For now, these advancements offer a clear direction for SAP consultants to prepare for and a great opportunity to help businesses embrace what’s coming.

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