Model-Data Resonance: The Death Sentence Being Handed Down to Companies That "Only Do Management Software"

MIIT and the National Data Administration have suddenly proposed "model-data resonance." Many people still think it is just another new concept.
But many software companies have not yet realised –

this policy may be handing down a death sentence to a group of companies in advance.

Which type of company is most at risk?
Not those that cannot do AI.
But those –

that only know how to do "management software."

Have you noticed?
In recent years, a large number of software companies are still competing on:
OA, ERP, CRM, approval workflows, inventory management;
competing on features, price, and implementation.

But "model-data resonance" has released a very clear signal:

The focus of national promotion is no longer "enterprises adopting systems," but "enterprises possessing intelligent capabilities."

These are two completely different eras.

01The Essence of Past Software Was "Recording"; What Enterprises Need in the AI Era Is "Prediction and Optimisation"

What was the essence of past software?
It was "recording."
Employees fill in forms, leaders approve, the system keeps records, and finally reports are generated.
To put it plainly, most management software was merely digitising "what has already happened."

But in the AI era, what enterprises truly need is beginning to become:
can it predict equipment failures?
can it automatically optimise scheduling?
can it detect quality risks in advance?
can it make the system proactively offer suggestions?
can it reduce dependence on master technicians' experience?

Note the change here.
What enterprises are buying is no longer "features."
But rather:

industry models, data capabilities, scenario knowledge, process experience, and agent capabilities.

This is what "model-data resonance" truly aims to promote.

02What Is "Model-Data Resonance"?

What is "model-data resonance"?
In one sentence:

Let models truly consume industrial data,and let data truly become industrial intelligence.

So here comes the question: what does industrial AI fear most?
Not that the model is not strong enough.
But rather –

that the data simply cannot be used.

03The Software Industry Will See a Huge Watershed

So in the future, the software industry will see a huge watershed.

The first type of company is still selling "features."The second type of company has started selling "industry intelligence."

The gap will grow wider and wider.
For example, in the past, when building an MES system.
Customers asked: "Does it have this module?"
In the future, customers will ask:
"Can you help me reduce downtime?"
"Can you improve yield?"
"Can you reduce dependence on manual experience?"

You will find that the business logic of the software industry is undergoing a complete change.

What was delivered in the past: a system.What will be delivered in the future: a "continuously learning industrial brain."

04AI Is Rapidly Eating Away at the Threshold of "Standardised Management Software"

What is even more frightening is –
AI is rapidly eating away at the threshold of "standardised management software."

Previously, developing an approval workflow
required a product manager, front-end and back-end developers, and testers working together.
Now many processes can be generated by AI in minutes.

The CRUD capability that was once proudly held is rapidly depreciating.
What truly becomes valuable begins to be:

whether you understand the industry.whether you have real industrial data.whether you have a long-term accumulated knowledge base.whether you have industry models.whether you have agent capabilities.

05Why Have Many Software Companies Started to Feel Anxious?

Why have many software companies started to feel anxious?
Because they have suddenly discovered:

after doing projects for 10 years, what they have ultimately accumulated may be only code.No data, no models, no industry knowledge assets.

And these are precisely the most valuable things in the AI era.

So behind "model-data resonance," the truly major trend can be summed up in one sentence:

In the future, what eliminates software companies may not be peers.But new players who truly master industry data, industry models, and industrial agents.

The second half of the software industry is no longer about "who can develop systems."

It is – who can make machines truly understand this industry.