India’s engineering graduates remain among the country’s most employable degree-holders, with B.E./B.Tech candidates recording an employability rate of 70.15%, according to the India Skills Report 2026.
Yet the same report puts overall employability across educational domains at just 56.35%. At the other end of the labour market, demand is shifting rapidly: job postings for AI/ML engineers and data scientists have recorded growth of more than 600%, according to the report.
The numbers point to an apparent contradiction. India continues to produce technically qualified engineers, even as employers increasingly look for capabilities that a degree alone may not demonstrate. The gap is not necessarily one of talent. It is increasingly one of readiness.
This Engineers’ Day, TheNews21 asked educators and industry leaders what actually makes a young engineer ready for the workplace — and why technical knowledge, while essential, is no longer enough.
Beyond Technical Knowledge
Ask people who train or hire young engineering graduates what often goes wrong when they enter the workplace, and the answer is not always coding ability or subject knowledge.
It is what happens when that knowledge has to be applied outside the classroom “Technical skill gets a graduate an interview; it rarely gets them through the first six months on the job,” says Sanmeet Sidhu, Chief Training and Development Officer, Thapar Institute.
“What trips up new engineers most often isn’t a gap in what they know, it’s not knowing how to work in a team where priorities shift daily, communicate a technical problem to someone who isn’t technical, or take feedback without treating it as a verdict on their ability. The ones who come out job-ready are usually the ones who sought out group projects, internships and real ambiguity on their own, not just the ones with the highest GPA.”
Ritika Gupta, CEO and Global Education Mentor, Aaera, believes the bar itself has moved as technology takes over more routine work. “AI is increasingly taking care of tasks that are repetitive and require vast amounts of information. Individuals must therefore concentrate on problem-solving, decision-making, communication, and strategy rather than on learning specific technical processes.”
The implication is significant: knowing how to perform a technical task is increasingly different from knowing what problem needs to be solved, why a particular solution makes sense and how that solution should be communicated to others.
Internships Are Not Enough If They Remain a Checkbox
For many engineering students, industry exposure still arrives late in the degree — often through a compulsory internship shortly before placements.
Educators argue that this model may no longer be sufficient. “Employers don’t just want engineers who’ve completed a degree; they want engineers who’ve already been tested against a real problem before day one,” says Dr Urmi Mehta, Chief Industry Engagement Officer, Thapar Institute.
“Institutions that treat industry exposure as a checkbox, one mandatory internship in the final year, are underselling their students. The stronger model is continuous exposure: live industry projects woven through the degree, not bolted on at the end.”
She proposes a progression that begins much earlier: “Observe the industry in the first year, experience it in the second, contribute meaningfully in the third, and demonstrate readiness in the final year.”
That model changes the purpose of an engineering degree. Instead of spending several years acquiring knowledge before finally testing it in the workplace, students encounter real-world constraints while they are still learning — deadlines, incomplete information, changing requirements, teamwork and solutions that may fail the first time. Those experiences are difficult to reproduce in an examination hall.
Is AI Changing What ‘Job-Ready’ Means?
Generative AI has added another dimension to the question. If software can now perform in minutes tasks that once occupied a junior engineer for hours or days, does a new graduate need to know less — or considerably more?
Dr Jaswinder Saini, AI and Robotics Labs, Thapar Institute, argues that automation has not lowered expectations. “AI and automation haven’t lowered the bar for what makes an engineer job ready, they’ve moved it,” he says. “An engineer’s value no longer lies in merely executing routine tasks, but in identifying problems worth solving, judging whether the tool’s output makes engineering sense, and detecting failure cases that automation may have overlooked. Students who learn to treat AI tools as a starting point rather than a final answer will remain relevant.” That distinction is becoming increasingly important.
Using an AI tool is one skill. Knowing when its answer is wrong — or unsafe, inefficient or unsuitable for the real-world problem — requires engineering judgement. The changing pattern is also visible among professionals choosing to upskill.
Mohan Lakhamraju, CEO and Founder, Great Learning, says engineers form the largest share of learners enrolling in the organisation’s AI programmes. “AI is expanding the boundaries of what engineers can solve — to model and simulate complex systems, optimise designs, predict failures, and analyse vast amounts of real-world data,” he says.
“Nearly 60% of enrolments in Great Learning’s AI courses this year have come from engineers, our largest learner group by a significant margin. As AI enables engineers to tackle increasingly complex problems, technical judgement and intuition become even more important in determining what is viable.”
From Knowing the Answer to Solving the Problem
Taken together, these shifts suggest that the answer may not be another standalone subject added to an already crowded engineering syllabus. What may need to change is the way engineering itself is taught.
A curriculum centred largely on marks, examinations and predefined problems prepares students to find correct answers. The workplace often presents something very different: an unclear problem, incomplete data, competing priorities and no answer key. That is where adaptability, judgement and communication begin to matter as much as technical competence.
Prof Ajay Batish, Pro Vice Chancellor, Thapar Institute of Engineering and Technology, puts the distinction simply: “What separates a strong engineer from the rest isn’t technical knowledge alone; it’s the ability to apply that knowledge under uncertainty, and to keep learning as the problem itself changes.”
That may be the more useful question to ask this Engineers’ Day. Is the best engineer today the one who knows the most — or the one who can take what they know, confront a problem they have never seen before and work out what to do next?
