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In 2025, the size of the global AI market is expected to exceed $1 trillion. Against this backdrop, the automation industry is facing the brunt of job reconfiguration. According to McKinsey's latest study, by 2030, 800 million jobs worldwide will be impacted by AI. Today, we'll take a look at the top 10 jobs in the automation industry that could be affected and why, and how to get a head start on this change.
I. List of top 10 high-risk jobs
1. Basic Programming DebuggingEmployee (Unemployment risk: ★★★★☆☆☆)
Reason for substitution:
AI code generation tools such as GitHub Copilot have been able to automate 60%+ of basic code writing
Automatic debugging system to quickly locate and fix common bugs in 80%
Organizations prefer to retain a small number of senior programmers for architectural design
2. Traditional industrial robot operators (unemployment risk: ★★★★★☆☆☆)
Reason for substitution:
New generation of collaborative robots with autonomous learning capabilities
3D vision guidance system allows robots to autonomously complete complex processes
Remote Monitoring SystemAllows one engineer to manage multiple devices
3. Basic Programming Debugger (Unemployment Risk: ★★★★☆)
Reason for substitution:
Low-code platform allows even business people to develop simple programs
Automated commissioning tool to simulate various operating conditions for testing
Digital Twin Technology Enables Debugging of 90% in a Virtual Environment
1. Production Line Maintenance Technician (Unemployment Risk: ★★★★☆)
Reason for substitution:
Predictive maintenanceSystem failure prediction accuracy rate of 98%
Intelligent Maintenance Robot Can Perform 70% Routine Maintenance Operations
Device networking rate exceeds 90%, remote diagnostics become mainstream
5. Basic Equipment Assembler (Unemployment Risk: ★★★★☆)
Reason for substitution:
gigafactoryautomated assemblyLine Reduction 60% Manpower
Flexible gripper + 3D vision realizes "1,000 parts, 1,000 faces" assembly.
Collaborative robots work with an accuracy of 0.02mm (4 times better than manual labor)
6. System Monitoring Operator (Unemployment Risk: ★★★★☆)
Reason for substitution:
Intelligent monitoring system automatically handles 90% anomaly alarms
Digital twin technology simulates equipment operation in real time
Industrial Brain System Realizes Plant-wide Intelligent Scheduling
7. Manufacturing Quality Inspector (Unemployment Risk: ★★★★★)
Reason for substitution:
3D vision inspection speed up to 0.5 sec/piece (3 sec manual)
AI deep learning recognizes 2000+ defect patterns
Factory AI QC accuracy 99.99% (Super Manual QC)
8. Logistics sorter (unemployment risk: ★★★★★)
Reason for substitution:
Jingdong Asia One Warehouse Reduces Sorting Manpower by 70%
AGV + robotic arm combination processing efficiency of 5000 pieces / hour
Intelligent Path Planning System Reduces 30% Energy Consumption
9. Standardized Automated Control System Integration Project Implementers (Unemployment Risk: ★★★★★)
Reason for substitution:
AI Design Tool Generates 90% Standard Control Logic
Modularized Solution Library Reduces 70% Implementation Cycle Time
Cloud Collaboration Platform Enables ”Zero Site” Deployment
10. Data Entry Clerk (Unemployment Risk: ★★★★★)
Reason for substitution:
Intelligent OCR recognition accuracy rate of over 99.9%
RPA Robot Processes 20 Times Faster Than Manual Labor
Electronic invoice penetration rate exceeds 95%
Second, how to deal with career challenges in the age of AI?
Skill Upgrade Direction
- Interdisciplinary knowledge: learn interdisciplinary knowledge of automation and artificial intelligence, automation and new energy, etc., and master the integration and application of related technologies.
- Data Processing and Analysis: Proficient in using Python and other data analysis tools to process and analyze the huge amount of data generated by automation equipment.
- Complex System Design: In-depth study of the design concepts and methods of automated complex systems, and enhancement of system architecture design capabilities.
Career transition paths
- Focus on high-value segments: shift to creative design, decision management, etc., which are difficult for AI to replace
- Continuous learning of new technologies: 1-2 cutting-edge technologies per year, e.g. digital twins, edge computing, etc.
- Cultivate human-computer collaboration skills: learn to work efficiently with AI systems and utilize their respective strengths
AI brings not unemployment, but career upgrades. Over the next five years, the risk of unemployment in the automation industry is concentrated in low-skill, repetitive operations jobs, but industry change also brings many high-value employment opportunities. Those who can quickly adapt to change and take the initiative to learn new skills will, on the contrary, have a better chance of development in this change. This is because it is not jobs that are often eliminated, but rather the way in which they are done.
