Since the mid-18th century and the advent of the Industrial Revolution, each wave of technological innovation has redefined the direction of advanced productivity in manufacturing. Over the past two centuries, industrial manufacturing has undergone four major transformations: mechanization, electrification, automation, and digitalization—culminating in today’s hyper-automated production environments.
Today, breakthroughs represented by generative AI are introducing a new paradigm to manufacturing. What will the most competitive factories of the future look like? Based on a global in-depth survey, a leading professional services firm released the report “The Future of Manufacturing” in June 2025. In this report, Accenture outlines the vision for the factory of 2040 as one of “hyper-automation”—a blueprint that goes beyond traditional automation and digitalization.
Table of contents
From Vision to Execution: The Need for Early Planning
In the industries surveyed by Accenture, factory planning cycles usually span five to seven years. As a long-term vision 15 years into the future, hyper-automation still faces real-world challenges such as talent shortages and slow AI deployment. However, Accenture argues that companies must plan ahead and take action now—reskilling employees, promoting intelligent automation, integrating AI into decision-making, and fully embracing digital transformation. These actions are necessary not only for short-term operations but also to lay the groundwork for long-term success.
Hyper-Automated Factories: Highly Automated Yet Flexible
Beyond “Dark Factories”: Human-Machine Collaboration
Currently, the “dark factory” represents an advanced manifestation of the Industry 4.0 strategy. Leveraging high levels of automation, data interconnectivity, and intelligent decision-making, such factories can operate without human intervention—even in the dark.
However, Fay Cranmer, Senior Managing Director at Accenture and Head of Industry X and Supply Chain & Operations in Asia Pacific, notes that once automation surpasses a certain threshold, it can hinder progress due to a lack of adaptability. Hyper-automation, then, offers a solution—balancing the use of machines with the involvement of humans.
Humans Remain Essential, but Their Roles Will Evolve
Cranmer emphasizes that humans excel at complex information processing, creative thinking, and proactive decision-making—capabilities that are extremely difficult to code into machines. In areas such as collaboration, oversight, support, and maintenance of automated operations, human roles remain critical and are increasingly important. Therefore, people will not disappear from hyper-automated factories.
However, the value of human labor will be redefined. Cranmer explains that while humans will still be needed, their work will shift toward higher-level, more knowledge- and thought-intensive tasks. Business needs are also changing. For instance, in the electric vehicle sector, there’s a transition from traditional internal combustion engine design to “software-defined vehicle” development. Whereas 80% of workers used to be mechanical engineers, now 70-80% need to be software engineers.
From Equipment Intelligence to Workforce Transformation
A notable example is the ongoing transformation of light equipment like 1 ton gantry cranes—from traditional electrical control to intelligent monitoring systems—using smart technologies to improve efficiency and safety in light-load handling.
No advanced technology can scale without matching talent and processes. If not integrated into existing production systems, new technologies often remain stuck at the proof-of-concept stage. This makes workforce transformation urgent.
Cranmer points out that many factory workers today have not even used email. This must change. Companies need to enhance digital literacy and help workers adapt to collaboration with machines and AI, using these technologies to improve job satisfaction and productivity.
Diverging Attitudes Toward Humanoid Robots
Interestingly, different countries show distinct attitudes toward humanoid robots. In India, China, and Japan, 63%, 65%, and 72% of respondents respectively believe humanoid robots bring value to assembly lines. In contrast, only 35% in the U.S. and just 21% in Europe share that view.
Cranmer believes that in rapidly developing economies like China and India, people are more eager to explore ways to drive economic growth and more willing to experiment and seek leadership. Developed countries, constrained by existing labor policies, tend to be more conservative. While Japan can be conservative at times, it also demonstrates strong innovation in technology.
Generative AI Has Great Potential—But Digital Foundations Must Be Strengthened First
Focus AI Deployment on Value-Driven Use Cases
Cranmer stresses that she does not believe AI will replace everything or everyone indiscriminately. Companies shouldn’t adopt AI just for the sake of using it. Instead, they should identify use cases that align with their specific goals and deliver clear value.
According to the report, 62% of factory managers surveyed believe AI is a key factor in driving comprehensive, hyper-automated factory operations. However, in the short term, most are prioritizing AI for maintenance, repair and overhaul processes, logistics optimization, and boosting production efficiency.
Data Quality and Digital Maturity Remain Major Barriers
Still, 38% of factory managers remain hesitant to deploy generative AI within their facilities. The hesitation stems partly from a longstanding distrust of technology and a lack of understanding of AI’s potential in manufacturing. But the most critical obstacle is poor and inconsistent data quality.
To elevate AI from a supporting role to an autonomous one, reliable data is essential. Without high-quality data, factories cannot move toward proactive management. As such, digitalization is the cornerstone of building a hyper-automated factory.
Choosing the Right Technology Partners Is Crucial
It’s also worth noting that selecting the right equipment manufacturers is particularly important in the journey toward hyper-automation and global competitiveness. Many companies give priority to the top 10 overhead crane manufacturers in the world, considering their technical capabilities and service reliability for mission-critical processes.
Yet the report finds that nearly half of factory managers surveyed still don’t give sufficient attention to core future factory capabilities such as digital twins, industrial IoT, and edge computing. These technologies simulate, analyze, and optimize production systems in virtual environments. Without them, information silos form, disconnecting design and production and undermining simulation-based decision-making and agile manufacturing.
From Technological Catch-Up to Leapfrogging into a Hyper-Automated Future: Awareness Is Key
Cranmer concludes that current levels of digital maturity are still far from ready for full-scale integration of generative AI. However, recognizing this opportunity allows companies—and even entire countries—to bypass traditional technological development paths and leapfrog into a hyper-automated future. For some nations, this represents a chance to reshape their position in the global industrial landscape.
