Organizations are finding themselves somewhat “lost in translation” when it comes to business/tech transformations: Fifty-eight percent of these initiatives end up going over budget, and global executives say only 57 percent end up being worth the required time, money and effort to complete them. As a result, nearly one-half of transformations remain “works in progress” as opposed to complete.
This doesn’t mean that transformative projects such as major cloud migrations are impossible. They’re not. But organizations need to take advantage of the tooling and capabilities available to complete these projects and find the balance of the speed needed for a large-scale migration with the necessary security safeguards.
Many organizations are struggling with this, as all SAP customers are required to migrate to the S/4HANA cloud system as part of the RISE with SAP initiative. In fact, three of five companies are still attempting to migrate to S/4HANA ahead of its upcoming deadline. What’s more, many companies are reluctant to use artificial intelligence (AI) agents such as SAP’s Joule, which can help with process standardization and automation.
Why the hesitation? Because they feel they lack the agility, capability and flexibility to embed AI copilots holistically and strategically into migrations. In addition, some are attempting to take on this intricate transition while carrying decades of technical debt. Modern SAP environments contain millions of lines of custom code, deprecated syntax and rigid legacy processes. Addressing such complexity within today’s timelines – while saddled with so much tech debt – seems prohibitive for many companies.
But teams must overcome these barriers to integrate agents, as the shift to an AI-assisted migration is now a necessity rather than a luxury. Without it, teams will surely encounter developer fatigue, rising security risks and bottlenecks in the form of tedious, manual remediations. In contrast, AI presents a protected path to automation and strategic prioritization – the ideal alignment of speed with long-term resilience.
SAP recognizes AI as a strategic enabler. This is why the “Clean Core” approach was introduced. Clean Core ensures S/4HANA cloud compliance, with optimal master data quality and business process governance, along with lower total cost of ownership (TCO).
Clean Core separates high-value customizations from obsolete noise so that migrations are completed efficiently, on budget and on time. It empowers AI to act as a force multiplier, shifting focus from “how much code exists” to “this is what actually matters.” From a broader perspective, it serves as a strategic component for organizations as opposed to a mere productivity tool, directly addressing three migration pillars:
Workforce. AI copilots reduce developer fatigue by generating boilerplate advanced business application programming (ABAP) code and explaining complex legacy logic.
Operations. AI-driven scanning validates the protected state of code in real-time, evolving security from a gatekeeper model to a guardrail one. Teams no longer manually block deployments for review. Instead, they leverage the AI security scanning to automatically check copilot-generated code against compliance baselines in real-time.
Security. Parallel AI systems manage risk as quickly as development accelerates, closing defense gaps.
So how can teams best implement Clean Core for their S/4HANA migration? We recommend these key steps for an “AI first” transformation:
AI-driven discovery and baselining. Deploy automated analysis to map the full SAP custom code landscape before it begins, and application-aware scanning to identify business-critical code, obsolete customizations and active risk. With this, teams gain clarity on where their “crown jewels” exist and where risk is hiding.
Assisted remediation with guardrails. Generative AI tools will refactor legacy code into S/4HANA-compliant syntax. Teams can automatically scan AI-generated output for vulnerabilities such as injection flaws or unauthorized bypasses. This embeds security in the pipeline, without slowing down progress.
Continuous threat governance. Round-the-clock monitoring proves essential, with machine learning (ML)-based detection distinguishing legitimate transformation activity from the exploitation of temporary misconfigurations.
Contrary to misgivings about comprehensive AI integrations for migrations being some mysterious, unobtainable entity, Clean Core is really about using intelligence to separate the signal from the noise. It takes advantage of automation to reduce the risk of growth, allowing for swifter adoption of the latest SAP AI advancements.
At the same time, teams transition from reactive reviews to continuous oversight – modernizing faster without expanding their attack surface. Thus, AI is no longer an enhancement. It serves a critical and foundational role to a successful migration, prioritizing value over volume so that speed and security scale together.
