The race to modernize SAP has become an endurance test for thousands of organizations still operating with legacy environments, historical customizations, and processes difficult to migrate without risk. In this context, Kyndryl has introduced a new approach to transforming SAP systems with a clear promise: shorten timelines, reduce manual effort, and lessen the weight of accumulated complexity through agentic AI applied to migration from SAP ECC to SAP S/4HANA.
The announcement, made on January 21, 2026 from New York, gives a name to the initiative: Clean Field. It is framed as a “disciplined” path toward a clean core that enables modernization without dragging along legacy code and dependencies, which often become the biggest obstacle to transformation. According to Kyndryl, their approach relies on collaboration with Nova Intelligence to apply agentic AI to particularly costly tasks: analyzing, adapting, and remediating SAP code during migration.
What Clean Field aims to solve: the bottleneck of code and customization
SAP modernization rarely fails due to lack of intent. What usually complicates it is the details: customizations, ABAP developments, bespoke integrations, “as-is” processes, and system dependencies that no one wants to touch for fear of breaking critical operations. In such landscapes, transformation can become slow, rigid, and expensive.
Kyndryl presents Clean Field as an approach to build a more adaptable digital foundation while progressing toward S/4HANA with greater scope control. The company’s goal is for clients to migrate data, processes, and systems with a cleaner core, less technical debt, and a more modular architecture prepared for future changes.
The difference isn’t just in the “destination” (S/4HANA), but in how you get there: Kyndryl claims that agentic AI enables automation of part of the remediation work traditionally requiring large teams, long testing cycles, and extensive manual review.
Agentic AI in SAP: from automation to task orchestration
The term “agentic AI” has gained popularity to describe systems capable of breaking down a goal into tasks, executing them with some autonomy, and coordinating steps with intermediate validations. Applied to SAP projects, its potential value lies in chaining activities that are typically performed “by hand”: code inspection, incompatibility identification with a clean core, refactorings, artifact generation, and test support.
Kyndryl has also published a use case demonstrating impact: leveraging Nova Intelligence’s technology, they modernized more than 33,000 lines of ABAP code in 10 days, with a reduction in manual effort compared to traditional approaches (a comparison the company attributes to the project).
If these figures are consistently confirmed in client projects, it could signify a meaningful shift: the true bottleneck — repetitive work on legacy systems — might be compressed from weeks to days in certain components.
The “bundle” with SAP: data, processes, and architecture to sustain modernization
Beyond code remediation, Kyndryl frames Clean Field within a broader collaboration with SAP, leveraging several tools that SAP positions as foundational for analytics, governance, and automation:
- SAP Business Data Cloud (BDC): Kyndryl uses it to harmonize SAP and non-SAP data, integrated with Databricks, aiming to train models and support AI use cases (including SAP Joule) on a “trusted” database.
- SAP Cloud ERP: Kyndryl’s proposal involves introducing agentic AI at typical transformation phases, such as fit-gap analysis, data migration, and post-go-live optimization.
- SAP Signavio: envisioned as a tool to increase process visibility, identify inefficiencies, and lower risks when moving from exploration to design.
- SAP LeanIX: supports transformation planning and governance by automating some documentation and discovery tasks.
Meanwhile, the partnership between Kyndryl and SAP is strengthened by Kyndryl’s role as a global delivery partner for RISE with SAP, a notable detail positioning the company among major integrators competing to industrialize complex migrations.
What’s behind it: pressure to modernize and “get it right the first time”
The announcement comes at a time when many organizations are trying to solve a difficult puzzle: modernize SAP to enable advanced analytics and automation without turning the project into an endless rewrite. Clean Field aligns with a growing market trend: fewer “heroic” transformations and more industrialized change, driven by patterns, automation, and change management.
Yet, the sector recognizes that AI doesn’t eliminate risks magically. In SAP migrations, success depends on factors beyond code: data quality, process ownership, realistic testing, integration control, security, segregation of duties, and compliance. In this landscape, agentic AI can accelerate processes but also requires discipline: automating without a solid validation framework could lead to costly errors.
Therefore, the value of Clean Field — assuming it gains real traction — would lie not only in “faster migration” but in reducing the likelihood of ending up with a superficially modern S/4HANA that remains burdened with the same complexity. Kyndryl’s message is that moving the system isn’t enough; you must clean the core and prepare it for the next wave of innovation.
Frequently Asked Questions
What is a “Clean Field” approach in an SAP ECC to S/4HANA migration?
It’s a method focused on reaching S/4HANA with a clean core, minimizing dependence on customizations and technical debt, and fostering a more modular, adaptable architecture for the future.
How can agentic AI help modernize ABAP code in SAP projects?
It can automate repetitive tasks such as compatibility analysis, remediation, refactoring, and artifact generation, coordinating steps with validations to reduce manual effort in parts of the project.
What role does SAP Business Data Cloud with Databricks play in SAP modernization?
BDC aims to unify SAP and non-SAP data, and with Databricks integration, it facilitates analytics and AI over a governed, semantic database, helping build AI use cases on more reliable data.
What does “clean core” mean, and why is it important for long-term SAP sustainability?
It involves maintaining the standard core as clean as possible, avoiding invasive customizations. This typically makes upgrades easier, reduces operational complexity, and improves the ability to adopt new SAP ecosystem features.
via: kyndryl