Kyndryl has started using a new agentic AI-supported methodology aimed at SAP transformations hoping to accelerate the pace and simplify the process while also helping customers deal with SAP ECC and S/4HANA constraints at lower costs.
With the introduction of the Clean Field approach, Kyndryl aims to assist customers in developing a technologically advanced digital foundation while also eliminating legacy constraints that slow down large-scale ERP initiatives.
At the center of this methodology is Kyndryl’s partnership with Nova Intelligence, which uses agentic AI to optimize and automate the SAP code customizing process, focusing on the ECC to S/4HANA migration.
This will help Kyndryl customers achieve clean core migrations in a range of processes and SAP systems and help them develop modular SAP frameworks that are more responsive to shifts in enterprise objectives.
“Enterprises can no longer afford SAP transformations that are slow, rigid or weighed down by legacy complexity,”
said Michael Bradshaw, Global Practice Leader for Applications, Data and AI at Kyndryl.
“By combining our Clean Field approach and deep SAP expertise with agentic AI, we’re giving customers a faster, more disciplined path to SAP S/4HANA—one that reduces technical debt, requires less manual effort, accelerates outcomes and creates a digital foundation built for long-term innovation.”
Kyndryl said the Clean Field approach integrates closely with its broader IT modernization services and can be tailored to align with specific industry and business objectives.
The company is embedding agentic AI across SAP Business Data Cloud, SAP Cloud ERP, SAP Signavio, and SAP LeanIX to improve data harmonization, process visibility, transformation planning, and post-go-live optimization.
The announcement reinforces Kyndryl’s long-standing alliance with SAP and follows its recent recognition as a global RISE with SAP delivery partner.
Together, the companies aim to help customers de-risk SAP programs while accelerating time-to-value through AI-driven modernization.
