Artificial intelligence is now making industry-wide changes at a break-neck pace. Among those leading the way in the adoption of AI-driven automation, automakers were among the earliest and most enthusiastic adopters. From quality checks to proactive maintenance and manufacturing efficiencies, AI has offered faster manufacturing and lower costs.
Nevertheless, Ford Motor Company has called the bluff of the global manufacturing industry by recalling hundreds of quality – conscientious engineers, having just failed to believe that AI could be a match for a century of human experience in vehicle character and engineering common sense.
Why Ford Rehired Hundreds of Veteran Engineers
In recent years, Ford has dedicated substantial resources toward automated manufacturing methods such as complicated ‘artificial intelligence’-based quality control, and robotics on production lines. The goal: simple-raise productivity, lower manufacturing expense, and eliminate as much human oversight as possible.
However, the company faced several unforeseen obstacles.
Ford officials acknowledged that, automated quality checks failed to detect more intricate manufacturing problems and design defects which veteran engineers could typically identify by ‘instinct’ after 20, 30 and even 40 years experience.
Consequently, Ford brought back in over 300 Ford veteran engineers (known inside the company as “grey beards” for their wizened status) to rejoin the company’s quality control efforts and pass on knowledge to younger engineering groups.
AI Was Missing One Critical Ingredient
Artificial Intelligence works very effectively if you have huge, reliable data to learn from. But manufacturing can be unpredictable.
Designing a vehicle is subject to countless engineering design decisions, that need real experience rather than a database of past data.
The Vice President for Vehicle Hardware Engineering at Ford admitted the company overestimated the number of tacit knowledge that was to be lost as engineers left or retired. The ai components also were not aware of the smallflaws in parts made before production.
This highlights one of AI’s biggest limitations:
AI sees the patterns.
Engineers get context.
AI can anticipate results.
People weigh up the risks and make decisions.
That made all the difference.
Human Engineers Improved Product Quality
Ford says its re-introduction of experienced engineers into its engineering works has led to a marked decrease in manufacturing defects and warranty costs.
The expert engineersare now involved in design reviews necessary to meet certain standards,they foresee failure before production takes place and carry out mentoring for junior engineers.
They are not replacing AI, they are advancing it by offering more accurate feedback and training data.
Ford Is Not Abandoning Artificial Intelligence
Though the headlines might suggest AI failed, Ford is not shunning automation.
However, the company is moving toward a hybrid model of AI, and supporting engineers rather than replacing them.
Ford continues using AI for:
Software validation
Automated testing
Manufacturing analytics
Production monitoring
Predictive maintenance
AI-based software validation tests. The company says it has rolled out 100,000 plus AI-based software validation tests that enables engineers to find defect much earlier in vehicle development process. Results are examined by human experts for final engineering decisions.
A Lesson for the Entire Manufacturing Industry
10. Ford’s experience is however illustrative of a wider trend emerging across industries worldwide.
Much of the initial hype around AI by most companies seemed to focus on automation/ labour replacement. Reality is proving that AI provides the highest value when combined with experienced staff:
Industries where human expertise remains essential include:
Automotive manufacturing
Aerospace engineering
Healthcare
Pharmaceutical research
Infrastructure development
Semiconductor manufacturing
Not all of the decision making that occurs in these industries can be effectively mapped by algorithms.
Why Experience Cannot Be Replaced Overnight
Engineering know-how is accumulated through years of attempting practical, everyday problems.
Experienced engineers understand:
Material behavior
Manufacturing tolerances
Product failures
Customer usage patterns
Supplier quality variations
Design trade-offs
Quite a few of the realizations were undocumented, and were developed over numerous years working directly on the subjects.
Despite the fact that AI technology is capable of analyzing millions of data points, the systems still rely on human experts to identify strange cases and develop better training models.
Ford’s decision simply demonstrates that institutional knowledge is still one of the company’s most important sources of competitive advantage.
What This Means for Jobs in the AI Era
The fact that Ford is taking this step does not mean that adoption of AI is slowing down at E-FAB.
Instead, it suggests that the future workers will need to work along with autonomous machines.
Instead of cutting engineering positions, AI is anticipated to take over routine work and to free up time for engineers to work on:
Product innovation
Complex design decisions
Problem-solving
Strategic planning
Risk management
Companies want employees who know the roots of engineering, as well as the new science.
Ironically, the need for seasoned tech staff might actually increase as companies look for people to help manage artificial intelligence systems.
AI Works Best as a Partner, Not a Replacement
The technology is not what remains learned from Ford’s case.
Where machine learning is superior to a human; machine learning is excellent at providing insight from deep legions of data, not so well as experienced engineer bring skill, invention, responsibility and actual life knowledge.
The refocused emphasis on human skills signals a much wider trend in digitalising businesses. Instead of having to decide whether to rely on AI or people, they are learning how to blend the two together.
Conclusion
Ford’s move to bring back hundreds of aging engineers reminds us that artificial intelligence is a great aid – not a substitute for human judgment. As AI changes the way we manufacture cars, develop products and run companies, those that make the most of it will be those that marry automation with seasoned hands.
While many industries are rushing to adopt AI, Ford’s approach provides a useful template for what lies ahead: it is using AI to supplement human work not supplant it. That moderate formula may well be the template for manufacturing and engineering in the long run.
