
AI NEWS
Facilitating AI integration with simplicity at scale
Jabil, a global manufacturing giant with over 100 sites, is prioritizing enterprise technology integration to combat data silos and complexity. Under the guidance of SAP IT Director Harish Manohar, the company adopts a 'simplify-first, then-innovate' strategy using SAP Integration Suite and BTP. The goal is to establish a trusted data backbone that enables faster responses to supply chain disruptions and lays the groundwork for scalable AI applications like predictive forecasting.
THE NEWS
What happened
Jabil, a global manufacturing giant with over 100 sites, is prioritizing enterprise technology integration to combat data silos and complexity. Under the guidance of SAP IT Director Harish Manohar, the company adopts a 'simplify-first, then-innovate' strategy using SAP Integration Suite and BTP. The goal is to establish a trusted data backbone that enables faster responses to supply chain disruptions and lays the groundwork for scalable AI applications like predictive forecasting.
CONTEXT
Why it matters
Global manufacturing giant Jabil is overhauling its tech stack to fight data silos. With 100+ sites, they are adopting a 'simplify-first' approach using SAP tools to create a unified data backbone. This paves the way for smarter AI integration and faster disruption response.
AT A GLANCE
Key facts
- Jabil operates over 100 sites across more than 30 countries with a workforce exceeding 140,000 employees.
- The company is transitioning from fragmented, legacy systems and spreadsheets to a unified data backbone using SAP Integration Suite.
- Harish Manohar advocates for a 'simplify-first, then-innovate' mindset to avoid adding complexity before modernizing.
- Jabil is moving toward an API-driven, event-based integration architecture to ensure seamless data flow.
- The initiative aims to reduce technical debt accumulated over 25 years of site-specific tools and manual workarounds.
- Future AI initiatives, such as predictive supply chain insights, depend on the success of this foundational simplification effort.
SOURCE
Original source
This article is based on information published by MIT Technology Review AI.



