In the new SAP world, centered around the Autonomous Enterprise, the role of SAP S/4HANA is changing. Architecturally positioned below SAP Business AI Platform, SAP S/4HANA functions primarily as one of several source systems that provide data to AI agents. Process innovations, on the other hand, no longer take place in SAP S/4HANA but at the SAP Autonomous Suite layer. In this regard, the primary goal of the SAP S/4HANA transformation is now to complete the transition as quickly as possible and to be able to provide the architectural layers relevant for AI use in the Autonomous Enterprise with data.
SAP S/4HANA’s new role: In the concept of the Autonomous Enterprise, SAP S/4HANA becomes a data provider for AI agents on SAP Business AI Platform – process innovation will take place at the level of the SAP Autonomous Suite in the future, rather than in the core ERP system.
Recommended approach: lean brownfield approach instead of a double greenfield project: Since the eventual migration to the public cloud usually requires a greenfield project anyway, companies should move to SAP S/4HANA quickly, leanly, and cost-effectively via a brownfield approach.
Up to 30% accelerated transformation through AI: Artificial intelligence accelerates SAP S/4HANA projects across three phases – (1) documentation & assistance, (2) design & testing, (3) implementation & customization – while significantly reducing the workload on project teams.
Humans remain in charge: AI automates routine tasks and supports analysis, quality assurance, and development, but always operates under the supervision of experienced architects; professional review and human quality assurance remain indispensable.
A greenfield project is complex and expensive – which is why companies ideally undertake it only once. As a rule, the move to the public cloud eventually requires a new implementation using the greenfield approach anyway. If companies are already undertaking a greenfield project to optimize their processes as part of the transition to SAP S/4HANA and then move to the public cloud at a later date, they are effectively doing a greenfield project twice. However, this is unnecessary, especially since process innovation will take place above the core ERP system in the future. Therefore, the clear recommendation is: Make a lean transition to SAP S/4HANA via the brownfield approach now and save any potential greenfield project for the later move to the public cloud – if it’s even necessary at all.
In the effort to make the transition to SAP S/4HANA as efficient and cost-effective as possible, artificial intelligence makes a valuable contribution in several ways. The use of AI accelerates the transformation project – in terms of overall effort – by up to 30%, reduces the workload on project participants, and ensures high-quality results.
The possibilities for leveraging AI are extremely diverse and can be expanded in stages over time. The range of activities where artificial intelligence provides effective support extends from traditional documentation and assistance tasks through quality assurance to technical areas such as software code development.
Level 1 covers typical documentation and assistance tasks. With the help of AI, it is easy to consolidate knowledge from the minutes of individual meetings and integrate it into a workflow so that the expertise is automatically processed further. This creates a knowledge base that grows continuously over the course of the project. Creating such a continuous workflow significantly reduces the workload for project participants. Routine tasks run in the background, while the team can focus on the real value-added work.
Artificial intelligence can also be effectively used for conceptual work and quality assurance to keep the various threads of a transformation project on track. AI delivers significant time savings when creating concept drafts based on existing documentation and when processing information. This is accompanied by better integration among the (business) departments involved in the SAP S/4HANA project. AI agents analyze business concepts and specifications, identify dependencies, and perform automated quality checks. The role of the people involved is shifting such that, in the future, they will primarily validate, supplement, and approve the AI’s work.
The third level covers technical use cases, such as software code development and automated deployment. Typical scenarios for value-added AI deployment include the creation of implementation plans, test case generation, suggestions for code customization and its documentation, and AI-supported project management with a focus on planning, task allocation, and sprint tracking.
In the context of SAP S/4HANA, artificial intelligence also enables the cost-effective migration of legacy custom developments to a modern cloud architecture. The actual application is retained, but technically separated from the ERP core and migrated to SAP Business Technology Platform (BTP). In this scenario, AI thus plays a key role in helping companies improve their clean core capability.
In the age of the Autonomous Enterprise, the SAP S/4HANA transformation must be reimagined. The focus is no longer on the comprehensive redesign and optimization of business processes, but rather on the rapid establishment of a future-proof data and system landscape as the foundation for using AI agents. A lean, AI-supported brownfield approach enables companies to achieve this goal efficiently.
Artificial intelligence automates routine tasks, supports analysis, quality assurance, and development, and increases both the speed and quality of transformation projects. What is important here is that AI operates under the supervision of experienced architects; technical review remains crucial, and quality assurance by human users is indispensable. Companies that consistently combine SAP S/4HANA and AI not only accelerate their migration but also lay the groundwork for continuous innovation – where it will take place in the future: on SAP Business AI Platform and the SAP Autonomous Suite, built on top of the core ERP system.