Since the Industrial Revolution in the mid-18th century, every wave of technological innovation has redefined the development direction of advanced productive forces in manufacturing. Over the past two hundred years, industrial manufacturing has
undergone four rounds of transformation: mechanization, electrification, automation, and digitization.
At present, technological breakthroughs represented by generative AI are introducing new development paradigms for the manufacturing industry.
What will be the most competitive factory in the future? Based on a comprehensive global survey, in June 2025, a leading professional services company released a report titled 'Manufacturing of the Future'. In this report, Accenture summarizes its future
factory vision for 2040 as "hyper automation" - a new blueprint that goes beyond traditional automation and digitization.
The report points out that high standards of cost efficiency and quality have become essential foundations for factories to maintain a competitive advantage. In the future, the true differentiation advantage will be reflected in elasticity, sustainability, and
intelligence levels.
This will be driven by four major factors: labor, automation, AI optimization, and digitization. For manufacturing companies in 2040, there is no need to worry about whether to use technology anymore, as they will become "standard equipment", and the
real competitive advantage lies in whether companies can seamlessly integrate these technologies and expand them into integrated intelligent systems.
In the industries surveyed by Accenture, the planning period for factories is usually five to seven years, and "hyper automation" as a long-term vision after fifteen years still faces practical challenges such as talent shortage and slow AI deployment. But
Accenture believes that companies need to plan ahead and take action to reshape employee skills, promote intelligent automation applications, integrate AI into decision-making processes, and fully embrace digitization. This is not only a necessary condition
to support the short-term operation of the factory, but also the key to laying the foundation for long-term development.
What is the difference between 'hyper automation' and current Industry 4.0 practices? What challenges will human employees face in the future? What kind of changes will AI technology based on big models bring to the manufacturing industry? At the recent
2025 Summer Davos Forum, the author had a conversation with Fay Cranmer, Senior Managing Director of Accenture and Head of Industrial X and Supply Chain and Operations for the Asia Pacific region, to explore the concept of "hyper automation" and its
implementation path.
Super automated factory: maintaining flexibility while highly automated
But soon, factory operations will be fully focused on resilience, agility, adaptability speed, and efficiency. This requires AI to autonomously connect devices, intelligently allocate tasks to balance workloads, and optimize job sequences.
Some manufacturing leaders have taken the lead in trying AI driven simulation models. KION Group, a leading global provider of industrial vehicles and supply chain solutions, has partnered with Accenture and Nvidia to create an intelligent warehousing system
that integrates AI, robotics, and digital twins. This warehousing system utilizes physical AI technology to improve performance by simulating real-world behavior, while also training warehousing robots to cope with demand fluctuations, inventory changes, and
layout adjustments.
Relying on the "cognitive digital brain", enterprises are shifting towards AI driven intelligent operations. In the future, human-machine collaboration will become a key competitive advantage for enterprises.
However, the report shows that 38% of factory managers are still hesitant to deploy generative AI technology within their factories. The reasons for this are not only a long-standing lack of trust in technology, but also a limited understanding of its application
effects in the manufacturing industry. But the most crucial obstacle is the low and uneven quality of the data.
In current industrial manufacturing practices, the 'black light factory' is an advanced implementation form based on the Industry 4.0 strategy. With the help of highly automated, data interconnected, intelligent decision-making and other technologies, black
light factories can achieve a production mode of "turning off lights and running" and unmanned operation.
But Kramer said that once the level of automation exceeds a certain critical value, it can hinder progress due to the inability to adapt dynamically, and hyper automation is a solution for highly automated systems. Compared to the unmanned operation of black
light factories, hyper automation will strike a balance between the use of machines and humans.
She emphasized that humans are better at complex information processing, innovative thinking, and proactive decision-making, which are all abilities that are extremely difficult to endow machines with through programming. In terms of collaboration, supervision,
support, and maintenance of automated operations, humans still play a crucial role, and this role is becoming increasingly prominent. Therefore, humans will not disappear in the future highly automated factories.
But human value will be reevaluated. Kramer stated that the manufacturing industry still requires the presence of people, but the job content will undergo significant changes. The overall trend is that people will engage in higher-level, more knowledgeable, and
thinking work. The specific needs of enterprises will also undergo changes, for example, the electric vehicle field is shifting from traditional internal combustion engine design to "software defined car" design. Previously, 80% of what was needed were mechanical
engineers, while now 70% -80% of what is needed are software engineers.
Any advanced technology, without matching talents and processes, will be trapped in the technology validation stage due to the exclusionary effect of the existing production and operation system, making it difficult to achieve large-scale implementation. Therefore,
it is urgent to promote the transformation of the labor force.
Kramer mentioned that many employees in manufacturing factories have not even been exposed to email, and this must change. Companies need to enhance employees' digital literacy and enable them to adapt to collaboration with technologies such as machines
and AI, using these technologies to improve their work experience and efficiency.
The report suggests that by 2040, factories will no longer require traditional "management", but rather intelligent "collaborative operations". The super automated factory has the ability to self optimize and is empowered by AI, integrating robots, digital twins, and
manual supervision into an intelligent and super automated manufacturing ecosystem. This manufacturing ecosystem will not only be able to execute processes on a large scale, but also be able to anticipate potential disturbances in real time, adapt flexibly, and
optimize production, achieving real-time highly autonomous operation status.
In addition to retaining manpower and AI empowerment, humanoid robots are also a major element in making super automated factories more flexible. Kramer mentioned that compared to industrial robots, humanoid robots are often easier to "move" and redeploy,
have stronger adaptability to different tasks, and have great potential for application. However, there are currently not many landing validations for humanoid robots, and it is difficult to assert that they will definitely be fully implemented in industrial scenarios in the
future. Difficulties such as speed, cost, and system integration complexity still need to be addressed.
The report mentioned that pioneers in the automotive industry have taken the lead in conducting application testing of humanoid robots and achieved significant results. For example, after BMW put the Figure02 humanoid robot into use at its Spartanburg factory,
production efficiency increased fourfold.
It is interesting that there are significant differences in attitudes towards humanoid robots among respondents from different countries. In India, China, and Japan, 63%, 65%, and 72% of respondents respectively believe that humanoid robots have significant value
for assembly lines, compared to only 35% in the United States and 21% in Europe.
Kran assumes that in rapidly developing countries like China and India, people are more actively exploring ways to promote economic development and are more willing to try various new things to strive for a leading position. However, some developed countries are
more conservative due to the influence of existing labor policies. Although Japan is sometimes conservative, it also has a strong sense of innovation in technology.
