The engineering segment is undergoing a dramatic shift as we dive deeper into the era of Industry 4.0. Artificial Intelligence (AI), the Internet of Things (IoT) and Data Science are not just some of the buzzwords, but these are transforming industries and the very foundation of engineering education. However, the challenge being faced is that the educational systems are not keeping pace with the developments.
It is evident that engineering curricula at many universities lag behind the technological advancements. Girija Kolagada, VP of Engineering at Progress Software, said that the fast development of technology is depriving students of the opportunity to enter the workforce equipped with the skills employers need if the academic curricula fails to keep up the pace.
The reality is that students need more than just textbook knowledge. Practical, hands-on learning through lab work, internships and real-world projects are highly important. Engineers of tomorrow need to have experience with AI, IoT and data science from day one. It is not just about keeping up with technology, but about preparing for a future where the pace of innovation will only accelerate.
The solution to this widening gap lies in stronger collaboration between academia and industry. Kartik Ayalh from MassMutual India said that they partner with institutions to curate curricula that align with industry requirements and this is to help the students in gaining exposure to the technology platforms. The approach needs to become the norm if universities want to remain relevant. Engineering education can no longer exist in a vacuum and isolated from the needs of industries that demand immediate application of skills.
Tools like AI and Generative AI (GenAI) are redefining how engineers approach problem-solving. Technologies such as GitHub Co-pilot are changing the way students write code, streamline development and deliver projects faster.
Technical expertise is vital and it is not enough on its own. Rohit Nichani, President at Encora, said that engineers need to evolve into “T-shaped” professionals—those who have deep expertise in one area but also a broad understanding of adjacent fields like data, cloud and AI.
