Migrating to SAP S/4HANA Cloud is a critical transformation, especially as SAP’s mainstream maintenance for its core ECC products is set to end in 2027. Limited budgets, technical constraints, and interruptions to business operations are the major challenges for migration. However, FITS believes that AI technologies can be utilized to increase efficiency and mitigate the risks for cloud migration. 

Building a Data-Driven Business Case with AI

Before commencing migration planning, AI can simulate the potential financial impact. By leveraging Process Mining on existing ECC systems, FITS identifies current inefficiencies and quantifies the ROI of migrating to S/4HANA through process standardization. This provides compelling, evidence-based justification for the decisions based on the project value rather than just the cost considerations.

AI-Led Delivery: A Game-Changer

AI-driven automation and decision-making streamline the entire migration lifecycle. From pre-migration to post-migration, AI tools like Generative AI (GenAI) optimize processes, reduce costs, and enhance efficiency. 

Pre-Migration: Clean Core with AI

A "Clean Core" is essential for modernization. Apart from the technical issues and concerns, FITS not only utilizes Business Process Mining to optimize the business processes but discovers and visualizes the actual end-to-end business processes. This approach uncovers hidden inefficiencies and deviations, providing a clear roadmap for the processes reengineering on top of the standard. Furthermore, AI-powered tools automate the cleansing, validation, and mapping of legacy data, ensuring high data quality from day one in the new cloud environment. All those efforts ensure a lean, agile SAP landscape.

During Migration: Efficiency, Accuracy & Predictability

AI automates testing, validation, and project management, minimizing risks. Tools like WRICEF automation accelerate timelines. This extends to predictive project management, where AI models analyze project data to forecast potential delays, flag resource conflicts, and identify emerging risks, enabling proactive intervention instead of reactive problem-solving.