Author Name : Richelle Bindal
For centuries engineering has consisted of turning imagination into reality engineers have designed bridges capable of withstanding huge forces, developed machines that have transformed whole industries, built software that links billions of people and created technologies which at one time seemed impossible. Yet nowadays engineering is going through a new kind of revolution. Generative Artificial Intelligence is now able to write code, generate designs, analyse complex datasets, simulate systems and solve technical problems in a matter of seconds. This does lead to a challenging question: can
AI take the place of engineers? The simple answer is that it is unlikely. While AI might take over some engineering tasks, it is much more probable that it will transform the engineer than disappear the engineer. Generative AI is a form of artificial intelligence which is able to create new content such
as text, computer code, images, designs and mathematical solutions by learning patterns from very large datasets. AI-powered tools can currently help engineers with jobs that previously took hours of repetitive work for example, a software engineer can use such tools to produce a simple program, a mechanical engineer can examine various design options, and a civil engineer can make use of computational tools to analyse structures. As a result, the economic situation in the field of engineering is greatly altered since engineers no longer have to spend most of their time on routine duties and can instead
concentrate on more advanced problems.A major field involved in transformation is design and simulation. In the past, engineers would produce a design, test it, find out its weaknesses and then make repeated modifications. AI can speed up this process by looking at thousands of different options
and spotting promising solutions. For instance, in aerospace and automotive engineering, AI-supported generative design is able to examine a large number of configurations while taking into account constraints like weight, strength and efficiency. The engineer is not any longer just producing a single design; instead they are guiding a system that can explore a vast design space.AI is having a similar effect on the field of software engineering. It is able to assist developers in writing code in detecting bugs in explaining programs they do not understand and in producing tests. The fact that this is possible does not mean that programmers will become irrelevant rather, it alters the meaning of programming. In so far as machines can carry out routine coding tasks, human engineers then have to
specialize in defining problems, in understanding system architecture, in verifying the output and in making strategic decisions.The difference between carrying out a task and understanding a problem is important. An AI is capable of producing an answer that looks impressive without actually
understanding the physical, social or ethical implications of that answer. An engineer who is designing a medical device, an aircraft component or a power system cannot just accept a solution provided by AI merely because it appears to be mathematically correct; they have to take into account safety, reliability, regulations, cost, human behaviour and the possibility of unexpected failure. Engineering is just as much about responsibility as it is about calculation.There is one other significant limitation: since AI relies on data and objectives that are set by humans, if the training data is incomplete or biased then the AI will generate incorrect results; moreover, if the problem is not well defined, even a very powerful
model might end up optimising the wrong aspect. That is why engineers still play an essential role, as they are the ones who decide what should be designed, which constraints are important and whether the final outcome is safe and practical. Yet this does not imply that engineers have nothing to worry about. Certain traditional jobs and duties will certainly change. Tasks such as repetitive drafting, simple coding,
routine calculations, documentation and some kinds of analysis are increasingly being taken over by automation. As a result, engineering companies may need fewer people to carry out some tasks while at the same time requiring more advanced skills from the people they hire. An engineer in the future will therefore have to possess a wider range of skills. While a knowledge of technical subjects will still be important, it will have to be combined with an understanding of AI, data science, computational thinking, creativity and communication. An engineer who understands not only the basic science but also how to make effective use of AI could be considerably more productive than one who depends solely on
traditional method This change could also have a democratizing effect on the field of engineering. Advanced AI tools might enable smaller teams and independent inventors to design, simulate and
prototype ideas which once necessitated large organizations. For example, a student who has an idea for a robotic system could use AI to grasp unfamiliar programming concepts, simulate the various components and quickly carry out iterations of their prototype. AI could thus become not only a replacement for some skills but also an amplifier of human ability. AI is particularly skilled in terms of speed, pattern recognition and its ability to process vast amounts of information. Humans are still uniquely valuable in areas like judgement,responsibility, empathy, creativity, leadership and in understanding unclear real-world situations. It follows that the most promising future might not lie in a confrontation between AI and engineers, but rather in AI working in conjunction with engineers.
Picture an engineer in the year 2030 who, rather than spending a full day writing routine code or manually comparing different design options, could describe the problem to an
AI system, get back dozens of possible solutions, test these out using simulations and then carefully assess the results. In this scenario, their role would change from that of a main producer of individual technical outputs to one of designer, evaluator, and decision-maker within a smart technological environment. AI will not make engineering obsolete in the end, instead it will cause the meaning of what an engineer is to change. The engineers who will be most at risk are not necessarily
those who use AI, but rather those who refuse to learn how to work with it.The future of engineering will not therefore be completely the domain of humans or machines, but will
belong to humans who are able to guide machines. Although generative AI may be capable of designing more quickly, performing calculations more rapidly and coding more efficiently, the decision of what is worth building—and making sure that it serves humanity responsibly—will still be an engineering problem that demands human judgement.
