New Quality Productive Forces: Future Competition Is Not About Whose Technology Is Newer, but Who Can Turn Technology into Productivity

On October 9, the Central Committee of the Communist Party of China and the State Council issued the Opinions on Developing New Quality Productive Forces, deploying 19 key measures.
In this document, there is a noteworthy signal: it is necessary to both develop future industries and use artificial intelligence to transform traditional industries; it is necessary to both encourage innovation and explicitly oppose blind investment and rushing in blindly.
What exactly does this mean behind it?

In the next round of industrial competition, what matters may not be whose technology is newer, but who can truly turn technology into productivity.

Why is that?
In the past, when an enterprise wanted to improve efficiency, it often relied on adding staff, expanding factory buildings, and purchasing equipment. But now, AI, industrial software, and intelligent equipment are changing this logic.

For example, when a manufacturing enterprise introduces AI, it is not to put a smart robot on display in a showroom, but to solve real problems: Can it reduce defective products? Can it detect equipment failures in advance? Can it make production planning more reasonable?

No matter how advanced the technology is, if it cannot enter the production process and improve business results, it will be difficult to form a true competitive advantage.

01The Value of AI Is Moving from Technology Demonstrations to Industrial Applications

This is also why the Opinions not only emphasises technological innovation, but also specifically proposes promoting the deep integration of technological innovation and industrial innovation, fully implementing the "AI+" initiative, and supporting the digital and intelligent transformation of traditional industries.

Note, there is a big change here:

The value of AI is moving from technology demonstrations to industrial applications.

Who will this affect?

First, manufacturing enterprises. In the future, the gap between enterprises may not just be whether their equipment is new, but who better understands their own production data, business processes, and process experience, and who can turn these things into sustainable efficiency advantages.

Second, software enterprises. In the past, developing a system and completing project delivery counted as closing a deal. But in the future, if software cannot truly solve industry problems, competition based purely on features and price may become increasingly difficult.

What is truly valuable may be enterprises that understand both technology and industry, and can combine AI, industrial software, and real business.

02An Easily Overlooked Signal: Do Not Do AI for the Sake of AI

But there is another easily overlooked signal here.
The Opinions explicitly proposes adapting to local conditions, not seeking to be big and comprehensive, not creating bubbles, and not blindly pursuing novelty.

This means that developing new quality productive forces does not mean that all enterprises should chase the latest trends, nor does it mean that every region should build the same industrial parks and lay out the same projects.

In the future, the most dangerous thing may not be that enterprises do not have AI, but that they do AI for the sake of AI; not that there are no new industries, but that everyone crowds into the same track.

03The Essence of New Quality Productive Forces

In the final analysis, new quality productive forces are not about giving traditional industries a new high-tech name, but about reorganising technology, talent, data, and production processes so that the same resources create greater value.

So, a question worth raising:

In the next ten years, is an enterprise's true moat the possession of the most advanced technology, or the ability to turn technology into industry capabilities that others cannot replicate?

Feel free to share your views in the comments.