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Facilitating AI integration with simplicity at scale

MIT Technology Review MIT Technology Review Insights

Jabil is stripping out messy tools before adding more AI. The bet: simpler systems now make automation and forecasting actually scale later.

Based on reporting by MIT Technology Review, MIT Technology Review Insights — read the original for the full story.

Summary, retelling and take written by AI under human oversight; images are AI-generated illustrations. How we work · Report an error

Jabil is treating integration as a business strategy, not an IT cleanup. The global manufacturer runs more than 100 sites across more than 30 countries, and Harish Manohar, its SAP IT director, says that kind of spread quickly turns site-specific tools, spreadsheets, and manual workarounds into a drag on decision-making.

The company’s answer is blunt: simplify first, innovate second. Manohar says new technology layered on top of old complexity just creates more of it. So Jabil is trying to standardize processes, consolidate systems where it can, and build a more consistent data backbone across the company. The point isn’t modernization for its own sake. He says every transformation has to create measurable business value.

That matters because Jabil’s plants do not all run the same way. Different regions have different process maturity, legacy systems, and local workflows, and some parts of the business face extra compliance demands. Standardizing across that kind of mix means changing governance and process design without knocking operations offline. Not easy. But Jabil says the payoff is shared visibility, less manual data reconciliation, and a faster path from chasing information to acting on it.

The company has been using SAP’s BTP and Integration Suite as part of that push, along with an API-driven, event-based approach. It also wants to reuse more of what already exists instead of buying one-off tools for each site. For major processes, Jabil still looks best of breed, but for local needs it wants to borrow and adapt rather than start from scratch. That same logic runs through its move toward SAP’s clean-core approach and its shift into RISE, where tighter governance is meant to curb the heavy customisation built up over 25 years.

And the long game is clearly AI. Jabil is looking at predictive supply chain insights, intelligent exception handling, and AI-driven planning and forecasting. But those tools only get interesting once the data is trustworthy and the systems are connected. Manohar’s line lands because it’s not flashy: simplicity at scale is the advantage, and in manufacturing that usually beats another shiny tool.

My take — AI-written commentary, not fact-checked reporting

This is the unglamorous truth the AI crowd keeps dodging: messy systems make “intelligence” look like a slideshow. Jabil is doing the sensible thing by fixing the plumbing first, which is exactly why it’s boring enough to work. The industry loves fancy pilots; the companies that win usually spend their time killing off spreadsheet folklore.

Read more about this at: MIT Technology Review

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