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Nayagam P P |10849 Answers |Ask -Follow

Career Counsellor - Answered on Jul 12, 2025

Nayagam is a certified career counsellor and the founder of EduJob360.
He started his career as an HR professional and has over 10 years of experience in tutoring and mentoring students from Classes 8 to 12, helping them choose the right stream, course and college/university.
He also counsels students on how to prepare for entrance exams for getting admission into reputed universities /colleges for their graduate/postgraduate courses.
He has guided both fresh graduates and experienced professionals on how to write a resume, how to prepare for job interviews and how to negotiate their salary when joining a new job.
Nayagam has published an eBook, Professional Resume Writing Without Googling.
He has a postgraduate degree in human resources from Bhartiya Vidya Bhavan, Delhi, a postgraduate diploma in labour law from Madras University, a postgraduate diploma in school counselling from Symbiosis, Pune, and a certification in child psychology from Counsel India.
He has also completed his master’s degree in career counselling from ICCC-Mindler and Counsel, India.
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Question by Lalit on Jul 12, 2025Hindi

Dear Sir, I’m in IT from last 27 year, worked with companies Like Microsoft. My question: As we aware AI is taking many software jobs & within 2 years, all software jobs be taken care by AI so there is only need of small team who can just supervise the AI results. Microsoft has already build AI agents which will do end to end software development. Considering there will be very jobs in Software industry then why are you pushing every one to take Computer science ? Pls share the ans with complete data.

Ans: Lalit Sir, Thanks for coming back after an year. Please note, I’m not advocating Computer Science for every student. In fact, I’ve also recommended branches like Civil Engineering, Agriculture Engineering, Medical Informatics, and even AI & ML based on individual preferences. I encourage you to review all my responses in context, rather than focusing on a select few. Many factors influence a suitable recommendation—such as available colleges/branches, rank, home state, location preferences, institutional reputation, affordability, gender, student interest (e.g., if someone is uninterested in AI & ML, it’s not advisable to push them), and placement trends. These are just a few of the many variables considered, not an exhaustive list. I hope this provides clarity. ALSO, please note, Computer science remains essential even as AI transforms software development, because a robust CS foundation underpins the design, innovation, and critical thinking that AI tools cannot fully replicate. Demand for software engineers is projected to grow by 25 percent from 2022 to 2032, yielding roughly 153,900 new U.S. openings annually, and BLS forecasts 17 percent growth in developer roles by 2033, indicating sustained need. AI accelerates routine coding tasks—Gartner predicts 50 percent of engineering orgs will deploy AI platforms by 2027—but cannot replace human-led architecture, creative problem-solving, or domain-specific design. AI agents depend on high-quality training data and falter with novel requirements, introducing unanticipated errors, overengineered or insecure code, and maintenance challenges when context is lacking. Overreliance on AI can erode developers’ critical thinking and domain expertise, while algorithmic bias and hallucinations demand human oversight to ensure correctness and ethical compliance. Moreover, the economic pipeline for CS graduates remains vital: U.S. CS vacancies are projected to exceed 1.2 million by 2026, and PwC finds AI-skilled workers earn significant wage premiums across industries. Equally important are computing fundamentals—data structures, algorithms, systems design, and software engineering principles—that empower professionals to supervise AI outputs, optimize performance, and architect resilient systems. A CS curriculum cultivates adaptability and computational thinking applicable beyond coding to emerging fields—cybersecurity, data science, IoT, and AI research—ensuring graduates can pivot as technologies evolve. While AI specialization prepares students to advance generative models, a broader CS education equips them to integrate AI responsibly into complex software ecosystems, lead interdisciplinary teams, and drive innovation. Balancing AI branch studies with core CS knowledge safeguards against automation risks and preserves the human ingenuity that remains the cornerstone of software excellence.