AI is no longer an experimental initiative; it is a strategic priority. Yet for many enterprises, the journey from AI pilot to full-scale production remains complex, costly and uncertain. Organizations need AI platforms that are scalable, interoperable, energy-efficient and capable of delivering measurable business outcomes.

For decades, the foundation of SAP implementations has been based on the "people, process and systems" triad, in which each implementation (or upgrade) typically involves extensive process analysis and process-led redesign. This formula made sense when the workforce was largely composed of human data processors. But with the rise of Agentic AI - where AI takes over most of these transactional roles - the standard framework starts to fray.