Artificial Intelligence is no longer a distant idea for engineering institutions. It is already inside classrooms, assignments, projects, labs and career conversations. For colleges and universities, the real question is not whether AI should be used, but how it should be used without weakening the very skills that engineering education is meant to build.
At the Campus to Career Summit 2026, held on 15–16 May and organised by the Higher Education Department, Government of Karnataka, in collaboration with KDEM and Elets Technomedia. Dr. Sriram Devanathan, Principal, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, spoke on “Engineering Education in the AI Era”. His address brought a balanced and timely perspective on what AI means for students, teachers, institutions and the future of work.
He began with a simple but striking thought. When two things come together, the outcome can be constructive or destructive. It all depends on the conditions in which they are used. The same, he suggested, applies to artificial intelligence. AI can become a powerful learning partner, or it can become a shortcut that reduces curiosity and independent thinking.
This is where engineering education faces its biggest test. AI has made information easier to access and solutions faster to generate. But easy answers can also create difficult problems. Students may begin to depend too much on AI tools, not only for writing or coding, but also for thinking. Over time, this can affect their ability to analyse, question, evaluate and create original solutions.
Dr. Devanathan pointed out that one of the most serious concerns is the loss of what he called “productive struggle”. In engineering, students learn by attempting, failing, trying again, calculating, testing and improving. That struggle is not a problem; it is part of the learning process. When AI removes that struggle too early, learning may become shallow.
He also raised another important concern: the ability to separate fact from fiction. In a world where AI-generated content can sound confident and polished, students must learn to verify information, not simply accept it. For future engineers, this skill will be as important as technical knowledge itself.
Yet, his message was not against AI. In fact, it was the opposite. He argued that institutions must find better ways to use AI inside the learning process. “AI is changing everything. Our response must be intentional, human-centred, and future focused,” he said.
This means the classroom must also change. The traditional model where the teacher speaks and students only listen is no longer enough. Dr. Devanathan called for a shift from the “sage on the stage” approach to a more collaborative model where the teacher becomes a guide, facilitator and co-learner. In such a classroom, students do not just receive knowledge; they participate in creating it.
AI can support this shift if used thoughtfully. Instead of banning tools or treating them only as a threat, educators can use AI live in classrooms to compare ideas, test assumptions, build arguments and solve problems together. The goal should not be to make students dependent on AI, but to help them use AI responsibly while strengthening their own judgement.
This also requires a fresh look at curriculum and pedagogy. Today’s learners are growing up in a digital-first environment. They respond better to interactive, visual and bite-sized learning experiences. But shorter attention spans should not mean weaker learning. Institutions must design teaching methods that are engaging while still pushing students towards depth, discipline and problem-solving.
For engineering colleges, industry alignment is another key priority. The journey from campus to career cannot be left to chance. Institutions must understand what employers need, identify emerging job roles, map the required skills, connect them with curriculum and assessments, and finally test whether students are truly deployable in real-world settings.
This is where AI can become useful again. It can help institutions understand changing job roles, analyse skill requirements and improve the connection between learning outcomes and career readiness. But the final purpose must remain human: to prepare students who can think clearly, act ethically and solve meaningful problems.
Dr. Devanathan also highlighted an often-overlooked part of education reform: faculty well-being. Teachers are expected to adapt to new technologies, redesign learning, handle administrative responsibilities and still inspire students every day. Without supporting faculty, no transformation can succeed. As he rightly noted, “If we invest in our teachers, we transform learning for generations.”
He also shared the example of Amrita University’s Live-in-Labs programme, where students and faculty work in rural and tribal communities to identify real problems, co-design solutions, implement them and validate the impact. Such experiential learning helps students move beyond textbooks and classrooms. It builds empathy, teamwork, innovation and practical problem-solving, skills that AI alone cannot teach.
In the AI era, engineering education must therefore become more human, not less. Technology will continue to change, and new tools will keep entering the classroom. But the purpose of education must stay rooted in people, values and meaningful capability.
The future engineer will not be defined only by how well they use AI. They will be defined by how well they think, question, collaborate and apply technology for the larger good. That is the real opportunity before engineering education today.
