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2026-01-20 15:23:27
Outlook on Digitalization Levels in 2026
Written by Amikon Limited
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As a seasoned expert in the field of automation spare parts, Sandy has dedicated 15 years to Amikon, an industry-leading company, where she currently serves as Director. With profound product expertise and exceptional sales strategies, she has not only driven the company's continuous expansion in global markets but also established an extensive international client network.
Throughout Amikon's twenty-year journey, Sandy's sharp industry insights and outstanding leadership have made her a central force behind the company's global growth and sustained performance. Committed to delivering high-value solutions, she stands as a key figure bridging technology and markets while empowering industry progress.
This is my linkedin:
As a seasoned expert in the field of automation spare parts, Sandy has dedicated 15 years to Amikon, an industry-leading company, where she currently serves as Director. With profound product expertise and exceptional sales strategies, she has not only driven the company's continuous expansion in global markets but also established an extensive international client network.
Throughout Amikon's twenty-year journey, Sandy's sharp industry insights and outstanding leadership have made her a central force behind the company's global growth and sustained performance. Committed to delivering high-value solutions, she stands as a key figure bridging technology and markets while empowering industry progress.
The 2024 National Statistical Bulletin on Science and Technology Funding Input reveals that China's high-tech manufacturing sector is continuously increasing its investment in innovation, with R&D intensity rising significantly. Behind this counter-trend growth lies a significant challenge enterprises are facing: the difficulty of balancing complexity, cost, and speed when developing new products, systems, or services. Growing market demand for customizable, intelligent, and highly flexible products, software, and services directly drives up development complexity. Furthermore, enterprises are under cost pressure from clients: reducing development budgets while compressing project timelines. This pressure is particularly pronounced within China's manufacturing industry.
To address the triple challenge of escalating complexity, tightening budgets, and accelerating innovation, enterprises should prioritize establishing a comprehensive digital twin system as a core digital transformation strategy. According to the 2025 China Manufacturing Digital Transformation Industry Development Research Report published by a relevant institution, 86.7% of Chinese enterprises consider transformation essential. Investment in digital twins and digitalization signifies building a solid digital foundation, enabling organizations to adapt flexibly, grow steadily, and thrive amidst continuous change and unexpected challenges.
Through digitalized design and engineering processes, enterprises can define and develop products or production solutions more rapidly. Constructing digital twins of related systems is key to breaking down professional silos, fostering cross-departmental collaboration, ensuring data continuity, and promoting the automation of repetitive and tedious tasks, ultimately leading to significant efficiency gains.
Defining Levels of Digital Maturity
Digital maturity within the industry exists on a continuum, encompassing enterprises that have not yet initiated digital transformation to those already building comprehensive digital twin systems. Measuring whether an enterprise is a digital leader hinges on two core indicators: the maturity level of its most advanced digital domain or process, and the average digital maturity level across all domains and processes within the organization.
Digital leader enterprises have typically achieved high digitalization and system integration in at least one internal domain (e.g., engineering or manufacturing). These highly integrated domains serve as "industry benchmarks" for digital practice, characterized by using a digital thread to consolidate data and models within that domain, establishing a robust digital twin system. These domains often deploy AI technologies in specific applications (e.g., design assistants) and have begun adopting intelligent agent technologies that can leverage the digital thread to coordinate tasks across applications, laying the groundwork for ultimate cross-domain synergy.
For example, a leading manufacturer has deployed an integrated production digital thread enabling comprehensive connectivity of CNC machine tools. These connected devices can automatically push alerts for anomalous sensor readings during machining operations to personnel. Operators can then use the digital twin to review the machining process in a virtual environment, precisely pinpoint the moment the anomaly occurred, and diagnose the alert's root cause. This process facilitates earlier problem identification, enables more timely maintenance, and allows for rapid process optimization or updates when necessary. However, most enterprises remain at the initial stages of digitalization, and overall market digital maturity is still nascent. This presents a significant opportunity for enterprises to initiate or deepen their digital transformation to enhance long-term competitiveness and operational performance.
For example, a leading manufacturer has deployed an integrated production digital thread enabling comprehensive connectivity of CNC machine tools. These connected devices can automatically push alerts for anomalous sensor readings during machining operations to personnel. Operators can then use the digital twin to review the machining process in a virtual environment, precisely pinpoint the moment the anomaly occurred, and diagnose the alert's root cause. This process facilitates earlier problem identification, enables more timely maintenance, and allows for rapid process optimization or updates when necessary. However, most enterprises remain at the initial stages of digitalization, and overall market digital maturity is still nascent. This presents a significant opportunity for enterprises to initiate or deepen their digital transformation to enhance long-term competitiveness and operational performance.
The Industrial Metaverse: Ushering in a New Phase of Digitalization
The ultimate direction of digitalization is to propel enterprises toward the next phase: the Industrial Metaverse, born from the deep integration of digital technologies, AI, and comprehensive digital twins. It will construct an engineering and business decision-making environment centered on solid, precise, real-time data, where users can interact and perceive comprehensive digital twins intuitively and immersively. The Industrial Metaverse has been incorporated into future industry plans by multiple local governments. For instance, Shanghai and Shenzhen have released Industrial Metaverse action plans, promoting pilot projects in sectors like automotive and electronics manufacturing.
Amid the global wave of industrial transformation, enterprise responses to various challenges, whether solving specific problems or optimizing overall operations, will rely on the support of the Industrial Metaverse. Aligning with this trend, Siemens, through a dual-drive approach of internal R&D and customer collaboration, is continuously implementing practical application scenarios and strengthening core technological foundations including comprehensive digital twins and AI, paving the way for the Industrial Metaverse's realization.
Related development efforts include building governance frameworks for data connectivity and collaboration to integrate data generated by various authoring systems within an enterprise, accurately manage data temporality and validity, and present this data clearly through a unified user experience. Furthermore, development focuses on the practical application of AI and collaboration with hyperscale cloud service providers, aiming to lay the groundwork for the future large-scale adoption of the Industrial Metaverse. These collaborations have already spawned new functionalities capable of integrating 3D visualization, simulation technology, and real-time factory data into a unified immersive environment. Leveraging these technologies, engineers can accelerate the entire planning, engineering, and operational lifecycle, enable large-scale simulation and AI-driven workflows, and make reliable, data-driven decisions at all stages of design and operation.
These core capabilities will give rise to a series of powerful functionalities, such as integrating building infrastructure and production lines into a single engineering environment. Within this environment, AI can be used to rapidly simulate hundreds of potential factory layouts and identify the most efficient design. Utilizing simulation and AI-driven automation, personnel can complete facility optimization and capacity expansion in months rather than years, thereby significantly improving operational performance, enhancing energy utilization efficiency, and enabling more forward-looking capacity planning.
Related development efforts include building governance frameworks for data connectivity and collaboration to integrate data generated by various authoring systems within an enterprise, accurately manage data temporality and validity, and present this data clearly through a unified user experience. Furthermore, development focuses on the practical application of AI and collaboration with hyperscale cloud service providers, aiming to lay the groundwork for the future large-scale adoption of the Industrial Metaverse. These collaborations have already spawned new functionalities capable of integrating 3D visualization, simulation technology, and real-time factory data into a unified immersive environment. Leveraging these technologies, engineers can accelerate the entire planning, engineering, and operational lifecycle, enable large-scale simulation and AI-driven workflows, and make reliable, data-driven decisions at all stages of design and operation.
These core capabilities will give rise to a series of powerful functionalities, such as integrating building infrastructure and production lines into a single engineering environment. Within this environment, AI can be used to rapidly simulate hundreds of potential factory layouts and identify the most efficient design. Utilizing simulation and AI-driven automation, personnel can complete facility optimization and capacity expansion in months rather than years, thereby significantly improving operational performance, enhancing energy utilization efficiency, and enabling more forward-looking capacity planning.
Cultivating a Digital Mindset
Investing in a digital strategy is a critical path for enterprises to address current challenges, aiding not only innovation but also enhancing agility and resilience. More importantly, the value of digitalization compounds over time. Future projects will not only directly benefit from the agility and resilience accumulated through earlier digital practices but can also deeply integrate with these outcomes. Simultaneously, as practitioners become increasingly proficient with digital systems, valuable process knowledge will be continuously codified, allowing subsequent projects to realize value more rapidly.
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