Toward the end of July and beginning of August 2025, the application of AI (Artificial Intelligence) technology in the manufacturing industry entered a new phase. An analysis of the latest news and practical examples from around the world reveals that the application of AI in the manufacturing industry has moved beyond mere automation and is entering an era of true “cognitive manufacturing.
Humanoid Robots Enter the Manufacturing Industry in Earnest
Industrial Humanoid Revolution from Europe
In June 2025, the European manufacturing industry was shocked. Germany’s NEURA Robotics unveiled its third generation 4NE1 cognitive humanoid, Switzerland’s Hexagon announced its AEON industrial humanoid, and France’s Wandercraft announced Calvin in a strategic partnership with the Renault Group.
These robots are not simple automation tools. They are “cognitive” robots that safely collaborate with humans through sensor “skins” and AI perception systems, freeing workers from repetitive and heavy labor. They are expected to be a solution to the serious labor shortage problem, especially in the manufacturing and logistics industries.
Foxconn and NVIDIA’s Historic Partnership
Most notable is an innovative initiative by Foxconn of Taiwan and NVIDIA of the United States. Both companies have announced that beginning in the first quarter of 2026, humanoid robots will be deployed on AI server production lines at a new plant in Houston, Texas.
A groundbreaking aspect of this plan is that for the first time, NVIDIA’s products will be manufactured with the assistance of humanoid robots. The robots will be responsible for assembly operations, cable insertion, component pick and place, and other precision tasks that have the potential to fundamentally change the traditional electronics manufacturing process.
Accelerate practical application of AI predictive maintenance systems
From failure prediction to inventory management optimization
One of the most mature areas of AI use in manufacturing is predictive maintenance, and the latest trends for 2025 indicate that AI is being used to optimize the entire supply chain, beyond just machine failure prediction.
AI algorithms analyze machine data in real time to not only predict failures in advance, but also to automate parts procurement in conjunction with demand forecasting. This enables a shift from conventional “just-in-time” inventory to “just-in-time” MRO (maintenance, repair, and operations) inventory management, which simultaneously significantly reduces inventory costs and minimizes unplanned downtime.
As an actual success story, chemical manufacturer Hexpol has successfully built a multi-plant parts sharing system to avoid lead times between plants in neighboring states, and has implemented a system that checks inventory levels and instantly identifies and reserves needed parts.
AI Quality Control System Innovations
Inspection accuracy that surpasses that of humans
In the field of quality control, AI-powered computer vision systems are revolutionizing manufacturing. The latest AI quality control systems perform product inspections in milliseconds, reliably detecting even the most minute defects that human inspectors might miss.
According to a Rockwell Automation survey, 95% of manufacturers are investing in AI, with quality control being the top priority application for the second year in a row. This is because AI quality control systems go beyond simple inspection automation, demonstrating simultaneous improvements in production speed and quality.
Quality inspection is often a bottleneck in conventional production lines, but AI-equipped systems can increase production speed while inspecting all products with high accuracy. This allows production workers to focus on more advanced tasks such as root cause analysis and process improvement.
Integrated use of Digital Twin and AI
Optimization by Virtual Factory
The integration of digital twin technology and AI has made the concept of the “virtual factory” a reality in the manufacturing industry. By creating detailed virtual replicas of machines and systems, performance simulation, failure prediction, and process optimization are possible without physical intervention.
Particularly in new product development, the digital twin is used as a training environment for AI models, allowing them to be tested in a variety of scenarios before deployment in the real world. This simultaneously reduces development costs and time-to-market.
Convergence of Industrial IoT (IIoT) and AI
Building a Smart Factory Infrastructure
The convergence of Industrial IoT (IIoT) and AI is the foundation for the realization of a true smart factory. Enterprise IoT is projected to account for 72% of market revenues by 2028, and its integration with AI technologies is driving its growth.
Advances in edge computing are enabling data processing closer to the source of data generation and real-time decision making with low latency. This has made the creation of autonomous manufacturing systems that do not rely on cloud connectivity a reality.
Investment Trends and Market Growth
Active financing and market expansion
Investment trends for the first half of 2025 indicate increased investment in the manufacturing robotics sector. Notable fundraising includes Gecko Robotics, an industrial infrastructure inspection robot, raising $125 million to become a unicorn company with an enterprise value of $1.25 billion. Also, autonomous delivery robot Coco Robotics and AI-powered robotic beekeeping system Beewise raised $80 million and $50 million, respectively.
Overall, the market has reached $16.5 billion in new industrial robot installations, with more than 4.28 million robots in operation worldwide. In particular, the mobile robotics market is projected to exceed $5.5 billion in 2024 and continue to grow at more than 20% per year through 2030.
Contribution to Sustainability
Realization of green manufacturing
AI technology is also making a significant contribution to improving the sustainability of the manufacturing industry: AI-driven energy management systems analyze energy consumption patterns in real time and suggest more efficient ways to use energy, thereby reducing energy use while maintaining production levels.
Predictive analysis and optimized production planning minimize material waste, prevent overproduction, and enable precise monitoring of carbon footprint.
Developing Human Resources and Addressing Workforce Issues
Closing the skills gap through technology
AI technology offers innovative solutions to the labor shortage and skills gap problems facing the manufacturing industry. Collaborative robots (cobots) have created a safe work environment with humans, and AI support systems have enabled a 2-year rookie to gain the same decision-making skills as a 30-year veteran.
The use of digital augmentation technology and real-time data insights has enabled workers to strengthen their skills and improve their decision-making capabilities, resulting in efficient factory operations with a small number of elite workers.
Autonomous Learning Machine Tools for Autonomous Production
Exhibitors at EMO Hannover 2025, such as Germany’s Datron AG, are realizing autonomous learning machine tools that use the knowledge learned by the machine to adapt the production process. The goal is to develop Datron milling machines into adaptive production cells that automatically adapt to part requirements and environmental conditions.
This not only reduces setup time and machining time, but also improves process stability, a decisive step toward autonomous production. and increase process reliability while extending tool life.
Future Outlook
The Age of Customized AI
Customized AI solutions for the manufacturing industry are projected to outperform general-purpose solutions starting in late 2025. AI systems trained on manufacturing-specific data will provide a deeper understanding of individual company processes and offer significantly higher ROI, from supply chain risk assessment to predictive maintenance to design optimization.
In addition, with the expansion of the servitization model, it will be important to provide services throughout the product lifecycle after the product is sold, and AI-based product usage data analysis will be key to creating new revenue streams.
summary
In the week of late July and early August 2025 alone, a series of innovative technology announcements and practical examples were presented in the field of manufacturing AI. From the full-scale introduction of humanoid robots to advanced AI predictive maintenance systems, quality control automation, and integrated use with the digital twin, these technologies are expected to make a significant contribution to productivity, quality improvement, and sustainability in the manufacturing industry.
Importantly, these technologies are not just visions of the future, but real-world solutions being implemented today. For manufacturing companies, the implementation of AI technologies is critical to maintaining competitiveness and future growth.
Source List
- Amiko Consulting – “AI Revolution in Manufacturing 2025: the latest trends report for the end of June and beginning of July 2025”
https://amiko.consulting/the-manufacturing-ai-revolution-in-2025-latest- trends-report-for-the-end-of-june-and-beginning-of-july-2025-week-1-july-2025-the-future-of-manufacturing-as-deciphered-from- global-ai-news/?lang=en - Metrology News – “AI-powered machines redefine the factory floor at EMO Hannover 2025”
https://metrology.news/ai-powered-machines-to-redefine-the-factory-floor-at-emo- hannover-2025/ - IIoT World – “The Rise of Industrial AI: Automation Trends to Watch in 2025”
https://www.iiot-world.com/artificial-intelligence-ml/artificial-intelligence/industrial-ai -trends-2025/ - The White House – “America’s AI Action Plan July 2025”
https://www.whitehouse.gov/wp-content/uploads/2025/07/Americas-AI-Action-Plan.pdf - Rockwell Automation – “Eight Key Trends in Industrial Automation in 2025”
https://www.rockwellautomation.com/en-us/company/news/the-journal/8-key-industrial- automation-trends-in-2025.html - TS2 Tech – “Industrial Robotics & Automation Breakthrough – June-July 2025”
https://ts2.tech/en/industrial-robotics-automation-breakthroughs-june-july- 2025/ - The Robot Report – “Top 10 Robotics Developments for July 2025”
https://www.therobotreport.com/top-10-robotics-developments-of-july-2025/ - McKinsey & Company – “2025 Technology Trends Outlook”
https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-top-trends-in-tech
