Automation of key processes will rise from 18% to 50%. Yet, it wasn't technology that made the difference.

By 2030, the median percentage of key manufacturing processes that are automated will rise from 18% to 50%.
This is the outlook presented in a survey conducted by PwC, covering 443 manufacturing executives across 24 regions worldwide.

Looking at this figure alone, one would naturally want to think that companies that invested in automation will win.
However, as I read through the report, the story was not that simple. What PwC is truly emphasizing is not the amount of automation itself, but how quickly technology can be introduced, connected, and made to function as a whole.

What makes 'Future-fit' companies different?

In this survey, PwC analyzed a combination of factors such as innovation speed, time-to-market, and agility in reallocating capital and resources, identifying the top 20% of the most agile and innovative companies as 'Future-fit' companies.

This group is already ahead in terms of automation. The current median is 29% for Future-fit companies and 15% for others. By 2030, this is expected to widen to 65% and 45%, respectively.

I found this figure interesting.
It is true that Future-fit companies are leading the way, but other companies are also expected to see significant growth from 15% to 45%.
My point here is that automation itself will become widely adopted across all companies in the future.
Therefore, the differentiator from here on out will not be 'whether or not you are automating,' but how quickly you can introduce it and connect it to on-site operations and data to make it functional.

It is the organization, not the technology itself, that creates the difference.

So, what makes the difference?
Looking at PwC's figures, the dividing line lies more on the side of the organization that masters the technology than the technology itself. For Future-fit companies, 74% responded that 'employees can act based on new ideas,' compared to 59% for others. 'There is a culture that allows for strategic risk-taking' was 69% versus 36%, and 'there is a data-driven decision-making process' was 75% versus 47%.

The 69% versus 36% difference is particularly striking.
Whether there is an atmosphere where it is okay to try new things. This should be directly linked to the speed of AI and automation adoption. No matter how excellent the technology you buy, I believe that in an environment that does not tolerate failure, it is difficult to move from PoC to full-scale implementation.

PwC itself states that competitive advantage is shifting from 'who has the tools' to 'who can introduce and orchestrate them the fastest.'

I interpret this orchestration here not as lining up individual AI and automation tools, but as connecting them to on-site operations, data, and decision-making flows to make them work as a whole.

The roles expected of AI and robotics are slightly different.

There was another interesting figure.
When asked what they expect from AI, 'growth' was 47% and 'productivity improvement' was 46%, which are at almost the same level. On the other hand, for robotics, 'productivity improvement' was high at 78%, while 'growth' remained at 13%.

Looking at this difference, it seems that robotics is viewed as a means to run existing work more efficiently, while AI is expected to have room for growth.
However, high expectations and the state of being ready to actually deliver value are different things. I believe that AI does not work like magic on its own, but only becomes effective once the problems to be solved are defined, the necessary data is connected, and a mechanism is in place that flows through to decision-making.

The source of revenue is also expanding outside of traditional manufacturing.

PwC expects that by 2030, 44% of total revenue in the manufacturing industry will come from sources other than the manufacturing of traditional industrial products and consumer goods themselves.

The background to this is the shift toward intelligent connected solutions that combine not only equipment but also software, data, and services, as well as subscription-based and outcome-based models. Future-fit companies also show a tendency to prioritize these areas as growth strategies.

Reading this far, it is clear that automation is not just a story about labor saving.
I believe the very axis of competition in manufacturing is moving, including not just what and how much to automate, but what kind of revenue model to create beyond that. It is no longer just about improvements within the factory.

Meaning for the Japanese manufacturing industry

What I felt again after reading this survey is that the difference is not in the presence or absence of technology, but in whether you have an organization that can utilize technology.

The automation figures stand out, but the real dividing line is before that. Is there an atmosphere where you can try new things? Can you make decisions based on data? Can you connect individual initiatives to the whole? That is probably the part that will be effective on the front lines.

What is difficult in the field of DX promotion is how to connect that technology into existing operations. Dropping it into a mechanism that actually works is much more mundane and much more difficult than creating the right mechanism. This PwC survey seemed to support that feeling quite clearly.

That is why, before talking big about changing organizational culture, we might need to look at smaller units first.
For example, whether you can take the first PoC to production. I believe that whether an organization can take that one mundane step will become the difference in 2030.

Articles related to this theme

・Over half of AI in manufacturing stops at the pilot stage. Why connected AI changes productivity

・Why does factory DX stop on the front lines? Three structures that get stuck before technology

・Samsung to make all factories 'AI-Driven Factories' by 2030. How will Galaxy-originated Agentic AI change manufacturing?

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In this note, I organize trends in factory AI, robotics, and smart factories by connecting management, technology, and on-site implementation.

Beyond just introducing individual news, I also track which companies enter factory DX from which entry point and where the difficulties of on-site implementation arise.

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Source/Reference Links

PwC | “Industrial manufacturers to more than double automation of key processes by 2030 as technology widens divide between leaders and laggards” |
https://www.pwc.com/gx/en/news-room/press-releases/2026/pwc-global-industrial-manufacturing-sector-outlook.html