Why AI First Slows, Then Accelerates Manufacturing Performance
Why AI First Slows, Then Accelerates Manufacturing Performance
Publish Date: 2026-02-11 15:20:00
Source Domain: www.pymnts.com
Manufacturers racing to deploy artificial intelligence (AI) are often experiencing an uncomfortable reality: productivity declines before gains materialize.
A study by MIT Sloan describes what it calls a “productivity paradox” in AI adoption. Drawing on firm-level data, researchers found that early adopters frequently see limited or uneven performance improvements when AI tools are layered onto fragmented workflows rather than embedded within redesigned operating models.
“AI isn’t plug-and-play,” said University of Toronto professor Kristina McElheran, a digital fellow at the MIT Initiative on the Digital Economy and one of the lead authors of the study.
In many cases, companies invest heavily in algorithms, automation systems and predictive tools without reworking decision rights, retraining employees or integrating data flows across production lines.
The result is a widening gap between AI spending and realized value. While some leading firms ultimately unlock gains, others stall despite deploying advanced systems.
AI Layered on Legacy Systems
According to the study, early AI deployments in manufacturing tend to be additive rather than transformative. Companies introduce predictive maintenance models, computer vision inspection tools or demand forecasting algorithms, but leave underlying processes intact. This creates friction between automated recommendations and human workflows, limiting measurable productivity improvements.
Advertisement: Scroll to Continue
We’d love to be your preferred source for news.
Please add us to your preferred sources list so our news, data and interviews show up in your feed. Thanks!
Manufacturing environments are particularly complex. Production lines depend on tightly sequenced tasks, supplier coordination and legacy industrial control systems. When AI is introduced without harmonizing these systems, it can increase coordination costs in the short term. Workers must interpret AI…
