Industrial vision's biggest competitor isn't its peers — it's manual labor.

Many people assume that the biggest competitor of industrial vision is another industrial vision company.
It is not.

The biggest competitor in industrial vision has always been – manual labour.

Doesn't that sound a little surprising?

When a customer comes to you hoping to replace manual inspection with a vision system,
many engineers' first reaction is:
can this scenario be recognised?
can the accuracy reach 99.9%?
how should the model be trained?

But what the customer truly cares about is often only one question:

Why should I use a machine instead of continuing to hire people?

01.An Example: Why Doesn't the Customer Buy?

A production line has two quality inspectors.
The annual labour cost is two to three hundred thousand yuan.
If your vision solution requires an investment of three to four hundred thousand yuan, plus tens of thousands in annual maintenance.
Why should the customer buy?

Just because the recognition rate is higher?
Not necessarily.
Because in the eyes of many factory owners, a mature worker can start today.
But a vision system, from solution design, equipment installation, and on-site debugging to stable operation, may take several months.

The machine not only costs money but also carries the cost of trial and error.

So many industrial vision projects do not lose to algorithms.

They lose to manual labour.

02.What Is Truly Worth Doing Is What Manual Labour Simply Cannot Do

But here is a problem many people overlook.
If it is only about replacing one person, industrial vision will indeed struggle to make money.
What is truly worth doing has never been "saving one person."
But rather what manual labour simply cannot do.

For example, high-speed production lines.
Inspecting hundreds of products a minute – the human eye simply cannot keep up.
For example, micron-level defects.
A crack one-tenth the thickness of a hair – the human eye can barely see it.
Another example is continuous 24-hour stable inspection.
People get tired and miss defects.
Machines do not.

You will find that truly successful industrial vision projects are never because manual labour is too expensive.

But because manual labour has reached its capability boundary.

So industrial vision is not "machines replacing people."

It is "machines extending human capability."

This is also why more and more high-value projects are concentrated in industries such as new energy, semiconductors, and high-end equipment.
Not because these industries have more money.
But because their requirements for precision, speed, and consistency have exceeded human limits.

03.What Customers Are Truly Willing to Pay For Is Still Not the Algorithm Itself

There is another trend worth paying attention to.
As AI develops, many vision systems in the future will become easier and easier to deploy.
The algorithm threshold will continue to fall.
But what customers are truly willing to pay for is still not the algorithm itself.
But whether it can create new value.

It is improving yield.
It is reducing downtime.
It is stabilising quality.
It is supporting higher production takt times.

Because what the boss is buying has never been a piece of vision software.

But a more efficient way of producing.

04.To Judge Whether an Industrial Vision Project Has Value, Ask This Question First

So to judge whether an industrial vision project has value, it is advisable not to ask first:
"Can this defect be recognised?"
But rather to ask first:

"If we don't use vision and rely only on manual labour, can this problem really be solved?"

If the answer is yes, and at a lower cost,
then this project will most likely struggle to succeed.
If the answer is no,
then industrial vision truly has its own value.

The biggest competitor in industrial vision in the future will still be manual labour.
But what truly wins is not the system with the highest recognition rate.
But those systems that can create value that manual labour cannot.