Why Ford's Return to Human Expertise Is a Wake-Up Call for Quality Professionals
AI can process data. Experience recognises risk.
For the last two years, artificial intelligence has been promoted as the answer to almost every business challenge. From manufacturing and inspection to auditing and compliance, organisations have rushed to automate processes in the pursuit of greater efficiency.
But one of the world's largest manufacturers has just delivered an important reminder.
Ford has rehired hundreds of experienced quality engineers after discovering that AI alone wasn't enough to achieve the level of quality the company expected.
For quality professionals, the lesson couldn't be clearer:
Technology should enhance human expertise — not replace it.
Ford's Quality Reality Check
According to reports from Ford executives, the company had increasingly relied on AI-powered quality systems and automated inspection tools across its manufacturing operations.
The expectation was simple.
Feed design requirements into AI systems.
Automate inspection.
Improve consistency.
Reduce costs.
Instead, the company found something many quality professionals have understood for years.
Experience matters.
Ford has now recruited around 350 experienced engineers and technical specialists, many returning from retirement or supplier organisations—to identify potential failure points before components even reach the production line.
Charles Poon, Ford's Vice President of Vehicle Hardware Engineering, summed it up perfectly:
"Mistakenly we thought that by just introducing artificial intelligence... that would produce a high-quality product."
Quality Is More Than Data
AI excels at recognising patterns.
But quality is rarely just about recognising patterns.
It requires:
engineering judgement
contextual understanding
historical knowledge
understanding how failures develop
recognising subtle warning signs that aren't written into a specification
Experienced quality professionals don't simply identify defects.
They understand why defects occur.
That knowledge often comes from decades of product development, audits, investigations and continuous improvement—not from datasets alone.
Tacit Knowledge Cannot Be Downloaded
One of the most interesting admissions from Ford was that many of its experienced engineers had left before their knowledge had been captured.
That's something many organisations are facing today.
Across manufacturing, construction, engineering and quality management, a generation of highly experienced professionals is approaching retirement.
With them goes years of practical knowledge that often isn't documented anywhere.
This is known as tacit knowledge—the instincts, judgement and experience built over countless real-world situations.
No AI model can recreate expertise that has never been captured in the first place.
AI Needs Quality Data, and Quality People
Ford isn't abandoning AI.
Far from it.
Instead, it is asking experienced engineers to train both its younger workforce and its AI systems.
That is arguably where AI delivers its greatest value.
Rather than replacing people, it amplifies their expertise.
Artificial intelligence can analyse enormous volumes of information far faster than any human.
But someone still needs to determine:
what "good" looks like
which data matters
whether an anomaly is actually a problem
when a process is behaving differently for legitimate reasons
how improvements should be implemented
Without that human judgement, automation risks becoming confidently wrong.
The Same Lesson Applies to Management Systems
This story extends far beyond automotive manufacturing.
Whether implementing ISO 9001, conducting internal audits or driving continual improvement, organisations often ask:
"Can AI write procedures?"
"Can AI complete audits?"
"Can AI manage our quality system?"
The answer is that AI can certainly help.
It can accelerate documentation, identify trends, summarise evidence and support decision making.
But it cannot replace:
leadership
organisational culture
auditor judgement
customer understanding
professional curiosity
experience gained through years of solving real problems
Those remain fundamentally human capabilities.
Quality Has Always Been About People
ISO 9001 has never been solely about documented processes.
It is built around competence, leadership, continual improvement and evidence-based decision making.
Technology supports those principles.
People deliver them.
Ford's experience demonstrates that organisations gain the greatest value when experienced professionals and intelligent technology work together—not in competition.
Final Thoughts
The conversation should never be AI versus people.
It should be AI powered by experienced people.
As Ford's experience demonstrates, quality doesn't come from automation alone.
It comes from the people who understand products, processes, customers and failure better than anyone else, and who use technology to become even more effective.
In quality management, that human element remains irreplaceable.