Key takeaways
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- SAP has delivered four agent-led migration assistants to Early Adopter Care customers navigating transitions to SAP Cloud ERP and RISE with SAP.
- The active tools automate and guide data quality remediation, test case generation, custom ABAP code modernization, and baseline business configuration.
- Paints manufacturer AkzoNobel is piloting the Data Management Assistant to prioritize data hygiene during a large-scale ERP landscape consolidation.
- Test preparation integrates with SAP Test Automation by Tricentis for automated, continuous validation at scale.
SAP has made four of its planned migration and modernization assistants available to early adopter enterprise customers transitioning to SAP Cloud ERP and RISE with SAP. Originally previewed at SAP Sapphire, the specialized AI assistants target the most resource-intensive bottlenecks of enterprise resource planning transitions: data hygiene, custom code remediation, test validation, and baseline business configuration. Paints and coatings producer AkzoNobel is actively piloting the Data Management Assistant during an ongoing multi-system consolidation, using automated analysis to prioritize data quality remediation across its landscape.
Large-scale ERP migrations have historically presented severe operational friction for enterprise IT departments, requiring thousands of technical decisions and sustained commitments from systems integrators. By embedding specialized autonomous and guided assistants into the migration workflow, SAP aims to accelerate project execution while enforcing its clean core architectural mandate. Four tools are operational today in the SAP Early Adopter Care program, with three additional assistants scheduled to address system discovery, program governance, and multi-country rollouts across the broader transformation lifecycle.
Agentic Assistants Enter Early Adopter Migrations
The four tools currently in early access focus on specific operational workstreams that often stall legacy transformations. Rather than presenting a single conversational agent, SAP divided functional responsibilities into targeted software assistants built to interact with existing platform tooling:
| Assistant | Target Workstream | Primary Operational Capabilities | Integrated Tooling |
|---|---|---|---|
| Data Management | Data scoping and remediation | Evaluates data quality metrics, identifies defects, prioritizes business impact, and executes automated or guided corrections. | SAP Cloud ALM |
| Test Management | Validation and QA cycles | Analyzes user stories and process definitions, derives test scopes, generates test cases, and specifies required test datasets. | SAP Test Automation by Tricentis |
| Custom Code | ABAP modernization and clean core | Scans custom developments, flags obsolete Z-code, classifies complexity, and applies automated or recommended code adaptations. | ABAP Platform / SAP Cloud ERP Private |
| Business Configuration | Tenant setup and scoping | Translates requirements into target configurations tailored by industry, extracts source settings, flags deviations, and logs audit trails. | SAP Best Practices engine |
For data workstreams, the Data Management Assistant analyzes existing database hygiene to flag inconsistencies before records are extracted and loaded into target cloud instances. In AkzoNobel’s deployment, Master Data Program Lead Thilak Selvam noted that the tool provided structured prioritization for critical master data defects, accelerating planning cycles during the company’s ERP landscape consolidation under RISE with SAP.
Testing preparation receives similar automation. The Test Management Assistant parses process flows and functional specifications to automatically generate test cases and identify required test data. To validate deployments at scale, generated test packages are handed directly to SAP Test Automation by Tricentis for unattended regression execution, reducing the manual burden on operational staff.
Enforcing Clean Core and Reducing Migration Overhead
A central objective of SAP’s assistant strategy is operationalizing its clean core architecture. Decades of on-premises SAP ECC deployments led enterprises to accumulate massive volumes of custom ABAP objects, modifications, and direct table accesses. This legacy technical debt often prevents organizations from adopting modern software updates and cloud analytics. Similar architectural challenges surfaced when DACHSER migrated its HCM operations to SAP S/4HANA Cloud, where isolating modifications proved essential to maintaining long-term software maintainability.
The Custom Code Assistant tackles this barrier by classifying custom ABAP components based on complexity and usage. Operating autonomously within defined guardrails, the assistant identifies obsolete code for decommissioning, flags deviations from SAP-recommended APIs, and applies automated remediation to low-complexity defects. For intricate extensions, it provides AI-generated code proposals designed to decouple customizations into side-by-side or clean core extensions.
Meanwhile, the Business Configuration Assistant accelerates initial tenant provisioning. By comparing existing customer business models against pre-packaged SAP Best Practices, it generates baseline enterprise structures and flags configuration mismatches. Crucially for regulated industries, the configuration engine records a complete audit trail of automated modifications, establishing verifiable governance over system parameter changes.
Governance Challenges and Early Adopter Realities
While agent-assisted tooling promises to compress transformation schedules, enterprise architects and IT leaders must evaluate the operational boundaries of automated ERP tooling. Early adopter access implies that models and automation routines remain subject to iterative refinement, requiring structured human oversight before executing changes in staging or production systems.
Automated code remediation and configuration generation present specific governance hurdles. Organizations cannot treat AI-generated code adjustments as turnkey deployments. Engineering teams must establish rigid validation gates, code review checkpoints, and regression protocols to confirm that automated fixes preserve proprietary business logic without introducing latent operational flaws.
Furthermore, these assistants do not eliminate the necessity of cross-functional alignment. While the Data Management Assistant can isolate corrupted records and suggest hygiene rules, determining business data ownership and retention policies remains an organizational responsibility. IT leaders should view these assistants as accelerators for technical execution rather than substitutes for enterprise architectural governance.
What happens next
SAP plans to expand its migration tooling into a comprehensive, seven-assistant portfolio covering the entire project lifecycle, with further technical details accessible via the vendor’s Migration and Modernization Assistants portal. The development roadmap introduces three forward-looking agents:
- System Analysis Assistant: Intended to scan source environments to build a comprehensive baseline of existing custom code, configurations, and interfaces, creating the contextual data foundation that informs all downstream migration assistants.
- Project Management Assistant: Designed to provide real-time project metrics, monitor execution velocity, identify delivery risks proactively, and coordinate tasks across technical and business workstreams.
- Rollout Assistant: Aimed at multi-national deployments to reconcile central enterprise templates against localized legal, fiscal, and operational requirements.
As the initial four assistants progress through the Early Adopter Care program toward general availability, enterprise IT procurement teams and CIOs evaluating RISE with SAP contracts should examine how their systems integration partners plan to incorporate agentic tooling into fixed-fee or managed-service implementation proposals.
