How AI Will Reshape Education, Jobs, and Engineer Skills – Key Takeaways from GOSIM Conference

AI Impact on Education and Engineers

At the recent GOSIM conference, dozens of AI experts shared practical insights on how artificial intelligence will transform education, careers, and engineering work.

Shanghai Jiao Tong University’s Institute of Engineering Executive Dean Wang Jialiang delivered a talk titled “Education in the AI Era.” He argued that 90% of white‑collar jobs will be replaced by AI, 99% of people will become freelancers, and traditional “exam‑oriented” schooling will lose relevance. He even claimed, “My child does not need to go to university.”

Wang identified three archetypes for the AI era:

AI Natives : people who are aware of AI applications, can use AI tools fluently, and possess critical thinking and information literacy.

Unknown Explorers : lifelong learners who can discover and re‑frame problems, practice agile iteration, and continuously improve systems.

Unique Creators : individuals who maintain independent thinking, produce original creations, and demonstrate humanistic care and responsibility.

He advocated a new human‑AI collaboration paradigm: instead of humans merely asking AI questions, AI should pose questions that trigger deeper human reflection. The workflow includes recording discussions, building clear context, and integrating that context into the collaboration loop.

Learning should extend from the classroom to real‑world problems, actual projects, and valuable outcomes—a “learning by doing” model that replaces passive textbook consumption.

Traditional education focuses on standardized knowledge delivery and exam techniques, whereas a “life‑influences‑life” approach emphasizes genuine emotional connections and spiritual resonance between people.

Wang stressed that students in the AI era should become creators, not consumers, and that knowledge value grows through dynamic AI assistance rather than a linear “input‑store‑output” pipeline.

AI’s Effect on Professions

Salim Nahle, head of the Data and AI department at the University of Alsace (France), warned that repetitive, rule‑based jobs such as text entry, content creation, and data labeling face high automation risk. However, roles in marketing, programming, and education will evolve rather than disappear; professionals must learn to collaborate with AI to boost efficiency and innovation.

New job categories are emerging, including AI ethicists, prompt engineers, AI trainers, and data auditors, all of which require specialized skills and knowledge.

For engineers, routine tasks like diagramming and document writing are being automated. Meanwhile, demand grows for AI/ML specialists, cybersecurity experts, and sustainability engineers.

Software engineers will shift from pure coding to supervising, testing, and reviewing code; data engineers will focus on data governance, quality control, and AI evaluation; system engineers will incorporate AI safety, integration, and ethical considerations.

Key capabilities for engineers in the AI era include lifelong learning, soft‑skill development, agility, and specialized professional growth.

Key Insight: AI will not replace engineers, but engineers who master AI will replace those who do not.

Three skill groups are essential:

Hard Skills: data science, AI literacy, MLOps, cybersecurity, systems thinking.

Cognitive Skills: critical thinking, problem framing, creativity, adaptability.

Professional Skills: ethics, communication, teamwork, lifelong learning.

Universities must anticipate these shifts and embed them into curricula immediately.

Other Notable AI Sessions

Wang Xinmeng, technical lead at Koudi, presented “Koudi: Reshaping Productivity with Agnet,” covering the platform’s capabilities.

Huawei senior engineer Chen Shuangrui delivered “How to Build AI that Builds AI – Deploying Intelligent Agents in Real Enterprises,” analyzing bottlenecks of enterprise‑level agents and offering concrete case‑based solutions.

These sessions, along with many others, provide a rich repository of AI knowledge for anyone willing to study them.

Conclusion

The scariest scenario in the AI era is a person who cannot use AI and does not realize their own limitation. Success belongs to those who learn quickly, commit to lifelong learning, and exercise critical thinking.