Ford Rehires 300 Engineers to Improve Manufacturing Quality

Ford has reversed its AI-driven manufacturing approach by rehiring around 300 veteran engineers to address shortcomings in its automated production systems.

The automotive company had attempted to use AI across multiple operations, including quality control, in an effort to cut costs and boost productivity. However, according to Ford, the technology did not meet manufacturing expectations.

Charles Poon, Vice President of Vehicle Hardware Engineering at Ford, says: "Artificial intelligence is a fantastic tool, but it's only as good as the information you use to train it."

He added that the company "didn't pay as much attention" as it should have to the experience of its "most knowledgeable engineers" that have been with the company through multiple product cycles.

Training gaps in automated systems

During an October earnings call, Ford Chief Operating Officer Kumar Galhotra says the firm was deploying "AI across the entire industrial system".

Kumar added that this strategy would include the deployment of 900 AI-powered cameras in Ford plants, designed to "detect quality issues at the source" and "help mitigate supply disruptions".

These AI-driven systems, however, were not delivering the company's desired outcomes. 

"Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product," Charles says.

Experience versus automation

According to Charles, automated tools lack the training and expertise veteran engineers hold in order to run production processes efficiently. By reintroducing human workers, the company is reducing its AI presence and working with engineers to mentor younger workers and train up its systems. 

"We recognised that for us to enhance some of our automation and machine learning and artificial intelligence tools we needed to ensure that they were trained by the most experienced individuals," Charles says.

The company says human workers will now act as internal auditors and will run "mandatory weekly design reviews to hunt for and eliminate potential failure points before blueprints ever reach the factory floor".

Leadership changes and quality improvements

Ford's challenges around AI integration come as it returned to the top spot of the JD Power 2026 US Initial Quality Study for the first time since 2010.

According to Ford, this could not have been done without a "significant talent refresh".

This refresh, Ford says, involved the replacement of several senior leaders across engineering, supply chain and manufacturing, in addition to the hiring of hundreds of engineers who "carry the hard-earned wisdom of decades of design".

Kumar says that these engineers and technical specialists are "at the heart" of Ford's efforts to enhance production quality and will help by addressing manufacturing challenges prior to their integration into process workflows.