Artificial intelligence can write code, solve equations, explain technical concepts, and generate ideas in seconds. For parents and students, that naturally raises a question:
If AI can do so much of the technical work, why spend time and money learning the fundamentals of engineering and STEM?
The answer is not that AI is unimportant. Quite the opposite. AI is becoming another powerful tool available to students, engineers, and creators.
Learning how to use it will matter. But using a powerful tool and understanding the problem you are trying to solve are not the same thing. That is why engineering fundamentals may become even more important in the age of AI.
Engineering Has Always Changed With Its Tools
Engineering has never stood still. Calculators changed how engineers performed calculations. Computer-aided design changed how products and structures were developed. Simulation software made it possible to test ideas before building physical prototypes.
None of those technologies eliminated the need to understand mathematics, physics, electronics, programming, materials, or design. Instead, they allowed engineers to spend less time on certain repetitive tasks and more time solving larger problems.
AI has the potential to do something similar. A student can now ask AI to explain an unfamiliar concept, suggest several ways to solve a problem, help debug code, or offer ideas for a design. These capabilities are valuable. But there is still one question AI cannot remove from the engineering process:
Does this solution actually work—and does it make sense?
Answering that requires more than generating an answer. It requires understanding.
Preparing Students for the Future Means Teaching Fundamentals and Modern Tools
At ThinkBuild Foundry, we prepare students to understand the fundamentals and use modern tools. This combination of fundamentals and modern tools is also reflected in what the professional world continues to value.
The World Economic Forum’s Future of Jobs Report 2023 identified analytical thinking and creative thinking among the most important skills for workers, even as AI and big-data skills continue to grow in importance.[1]
Engineering education standards tell a similar story. ABET’s criteria for accredited engineering programs continue to emphasize mathematics, science, engineering principles, experimentation, engineering design, problem-solving, and the use of modern engineering tools.[2]
That last part matters. It isn’t fundamentals or modern tools. It is fundamentals and modern tools. Students should learn how AI works and how to use it. They should also understand the principles underneath the systems they are building.
Building in the Age of AI
No one knows exactly what today’s students will be building with five or ten years from now. The tools will continue to change. AI systems will become more capable. New technologies will appear. That uncertainty is one of the strongest arguments for teaching engineering fundamentals.
We cannot prepare students for the future by teaching them every tool they will eventually encounter. We can help prepare them by teaching them what to do when they encounter a problem they have never seen before.
- Learn.
- Think.
- Build.
- Test.
- Question.
- Improve.
Then use every good tool available—including AI—to see how much further the idea can go.
This is not an outdated approach to STEM education. It may be exactly the foundation students need for the AI era.
Sources
[1] World Economic Forum. The Future of Jobs Report 2023. The report identifies analytical thinking and creative thinking as leading core skills while also identifying AI and big data as growing priorities for workforce training.
[2] ABET. Criteria for Accrediting Engineering Programs, 2025–2026. Engineering program criteria continue to require substantial mathematics and basic sciences, engineering topics, experimentation, engineering design, problem-solving, and use of modern engineering tools.