Which Careers Will AI Change? Skills to Add During Your Degree
By Eduvy Editorial · 25 September 2026 · AI & Education
AI will change the work inside almost every career a 12th-pass student can choose, but not equally. The tasks going first are routine and screen-based: data entry, bookkeeping, first drafts, basic testing. Hands-on care and judgement-heavy roles are among the least exposed. The practical answer is the same for every degree: go deep in your field, learn to use AI tools inside it, and build the human skills that sit on top. Below is what the research says, what it means field by field, and a checklist for all four years of college.
What the research actually says
- World Economic Forum, Future of Jobs Report 2025: employers expect 170 million jobs to be created and 92 million displaced worldwide between 2025 and 2030, a net gain of 78 million. They expect 39% of workers' core skills to change by 2030. Today 47% of work tasks are done mainly by people, 22% mainly by technology and 30% by both; by 2030 employers expect a roughly even three-way split.
- International Labour Organization, May 2025: one in four workers worldwide is in an occupation with some exposure to generative AI, but only 3.3% of employment falls in the highest-exposure group. Clerical jobs are the most exposed. Because most jobs still need human input, the ILO says transformation of jobs is the most likely impact.
- NITI Aayog, Roadmap for Job Creation in the AI Economy (October 2025): by 2031 India's tech sector could lose 1.5 million jobs or create up to 4 million, depending on the choices made now. Routine roles such as junior QA engineers and L1 support agents face the most risk.
- nasscom and Deloitte (August 2024): demand for AI talent in India is projected to grow from 6 to 6.5 lakh people to more than 12.5 lakh between 2022 and 2027.
How exposed is each career? The ILO's rating
The ILO's 2025 index places each occupation in one of six bands: not exposed, minimal exposure, then gradients 1 to 4, where 4 is the most exposed. Exposure means AI can do some of the tasks. It does not mean the job disappears.
| Occupation | ILO 2025 band |
|---|---|
| Nursing professionals; civil, mechanical and electrical engineers | Not exposed |
| Pharmacists; lawyers; product and garment designers; interior designers | Minimal exposure |
| Electronics engineers; graphic and multimedia designers; management and organisation analysts | Gradient 2 |
| Software developers; accountants; legal secretaries; medical records and health information technicians | Gradient 3 |
| Web and multimedia developers; financial analysts; accounting and bookkeeping clerks; data entry clerks | Gradient 4 (highest) |
Look at the pattern inside each field. An accounting and bookkeeping clerk is in gradient 4, an accountant in gradient 3. A legal secretary is in gradient 3, a lawyer in minimal exposure. Medical records technicians are in gradient 3, nursing professionals are not exposed. What protects a career is less the degree and more which level of the field you work at: routine processing, or judgement and responsibility.
Field by field: what changes and what to add
The task columns below are our reading of each field's daily work against the sources above, not a forecast. Every course named is a free NPTEL course listed on nptel.ac.in.
| Field | Likely automated | AI assists | Stays human | Skills to add during the degree | Free course to start |
|---|---|---|---|---|---|
| Software engineering | Boilerplate code, routine test cases, L1 ticket triage | Debugging, documentation, code review | System design, understanding what the client needs, security judgement, owning live systems | Data structures and system design; integrating LLM APIs and AI guardrails (NITI names both for full-stack roles); cloud | Programming with Generative AI (IISc Bangalore); Responsible & Safe AI Systems (IIIT Hyderabad and IIT Madras) |
| Core engineering (civil, mechanical, electrical) | Routine drafting, compiling reports | Simulation, predictive maintenance, design options | Site and shop-floor work, safety sign-off, testing real hardware | Python for data, simulation software, sensors and IoT basics | Machine Learning for Core Engineering Disciplines (IISc Bangalore) |
| Nursing | Parts of charting, scheduling, record coding | Early-warning alerts, documentation, patient information leaflets | Bedside care, assessment, procedures, talking with patients and families | Hospital information systems, data literacy, checking AI output against protocol | Healthcare Quality Management: Infection Control and Patient Safety (TISS Mumbai); Fundamentals of Artificial Intelligence (IIT Guwahati) |
| Pharmacy | Stock records, prescription data entry, first-pass literature searches | Interaction checks, screening and designing molecules | Dispensing responsibility, patient counselling, quality and regulatory sign-off | Clinical research and regulatory basics, pharmacovigilance, computer-aided drug design | Artificial Intelligence in Drug Discovery and Development (IIT BHU Varanasi); Computer Aided Drug Design (IIT Madras) |
| Commerce and accounting | Bookkeeping entries, reconciliations, payroll processing | Audit sampling, variance analysis, draft reports | Judgement on estimates, advising clients, audit and tax sign-off, ethics | Data analysis beyond Excel (SQL or Python), ERP software, financial analysis | Artificial Intelligence (AI) for Investments (IIT Kanpur); Data Analytics with Python (IIT Roorkee) |
| Management and BBA | Routine reports, scheduling, first-draft marketing copy | Market research, forecasting, customer analytics | Leading people, negotiation, decisions with incomplete data | Business analytics, briefing and judging AI tools, working with data teams | Artificial Intelligence (AI) for Management (IIT Madras); Business Analytics For Management Decision (IIT Kharagpur) |
| Law | First-pass document review, routine clauses, research lists | Case-law search, contract comparison, due diligence | Advocacy, advising clients, negotiation, checking every citation | Legal research with verification, technology and data protection law, contract-review tools | Artificial Intelligence, Law and Justice (NALSAR University of Law); Governance of Artificial Intelligence (NALSAR) |
| Design | Stock visuals, resizing, routine layouts | Concept variations, image generation, fast prototypes | User research, taste, brand thinking, final creative direction | UI/UX and interaction design, user research, prototyping with AI tools | User Interface Design (IIT Roorkee); Interaction Design (IIT Guwahati) |
Two sourced signals sit behind the design and commerce rows. The WEF report lists graphic designers and accounting, bookkeeping and payroll clerks among the fastest-declining jobs, while UI and UX designers appear among the fastest-growing. For software, NITI Aayog cites a BCG analysis finding AI raises productivity across software development by 10 to 20%, and by up to 50 to 60% for simple applications.
What parents should NOT conclude
- "Avoid nursing or pharmacy because of AI." The ILO rates nursing professionals as not exposed and pharmacists as minimally exposed, and the WEF expects care jobs such as nursing professionals to grow significantly by 2030.
- "Computer science is finished." Software developers are in gradient 3, yet the WEF lists software and applications developers and AI and machine learning specialists among the fastest-growing jobs. Routine entry-level work is what is shrinking, so the bar to get hired is rising.
- "An AI degree title is insurance." Skills and proof of work count. Every row in the table above adds AI skills to an ordinary degree.
- "Exposed means the job will vanish." The ILO's own reading is that transformation is the most likely outcome.
- "Skip commerce or design entirely." Aim for the right level in the field: the accountant rather than the bookkeeping clerk, the UI/UX designer rather than the template designer.
- "The college will teach it." NITI Aayog notes that India's AI curriculum takes time to catch up with new concepts. Plan to learn some of it yourself.
AI-proofing checklist: Year 1 to Year 4 (any degree)
Year 1
- Use one AI assistant for study every week and keep a log of where it was wrong.
- Finish one free NPTEL or SWAYAM course in basic data skills (spreadsheets or Python).
- Take on one role that makes you present, lead or organise.
- Start a portfolio folder and save every project, report and certificate.
Year 2
- Learn the data tool your field runs on and complete one small project with real data.
- Take one AI-in-your-field course from the table above.
- Ask your college how many credits it accepts from SWAYAM courses; UGC and AICTE rules allow credit transfer.
- Get a short internship, volunteer post or field posting and note which software professionals use daily.
Year 3
- Build one project where AI does part of the work and you check and correct it, and write down what you fixed.
- Learn your profession's rules on data privacy and ethics, and what your regulator says about AI use.
- Do a proper internship and ask to help with a tool or system rollout.
- Practise explaining your work to a non-expert in two minutes.
Year 4
- Write up two or three projects as short case studies: the problem, what AI did, what you did, the result.
- Prepare to show in interviews both how you use AI tools and when you do not trust them.
- Pick a first job for what you will learn in it, not only the title.
- Set a date for your next step: a postgraduate course, a certification or an entrance exam.
For more courses, FutureSkills Prime, a digital skilling platform run by MeitY and nasscom, lists AI and data courses alongside NPTEL and SWAYAM.
Related reading: B.Tech AI and ML vs CSE: Which Branch to Pick in 2026 · How to Use AI to Study in College Without Hurting Your Marks
Frequently asked questions
Which careers are least exposed to AI?
In the ILO's 2025 index, hands-on and care roles sit lowest: nursing professionals, and civil, mechanical and electrical engineers are rated not exposed, while pharmacists and lawyers are rated minimally exposed. No career is untouched, but these change more slowly.
Will AI replace nurses?
The current evidence points the other way. The ILO rates nursing professionals as not exposed, and the WEF expects nursing jobs to grow. AI will change documentation and monitoring; the care stays human.
Is B.Com or CA still worth it?
Yes, if you aim above routine processing. Bookkeeping clerks are in the ILO's highest band and accountants a band lower. Add data analysis and advisory skills during the degree so you work where judgement is needed.
Should my child switch to an AI course instead of the field they like?
Not necessarily. Demand for AI talent is growing, but fields such as law and pharmacy now have their own AI courses. Domain knowledge plus AI skills is a strong combination.
Are NPTEL courses really free?
Yes. NPTEL courses are free to enrol in and learn from. The certification exam is optional and costs ₹1,000 per course. NPTEL is run by the IITs and IISc and funded by the Ministry of Education.
If you are still choosing a field, compare options on the nursing, pharmacy, AI & ML engineering and management college pages. Edubro, the AI counsellor in the Eduvy app, can help you shortlist courses and colleges, compare year-wise fees and apply to several colleges from one profile.
Sources
- World Economic Forum, Future of Jobs Report 2025 (reports.weforum.org)
- ILO Working Paper 140, Generative AI and Jobs: A Refined Global Index of Occupational Exposure, May 2025; occupation bands from Annex Table A1 (ilo.org)
- NITI Aayog, Roadmap for Job Creation in the AI Economy, October 2025 (niti.gov.in)
- nasscom-Deloitte, Advancing India's AI Skills, August 2024 (deloitte.com)
- NPTEL: free enrolment, exam fee, funding (nptel.ac.in)
- NPTEL course catalogue, course names checked 25 September 2026 (nptel.ac.in)
- SWAYAM: free courses, UGC and AICTE credit transfer (swayam.gov.in)
- FutureSkills Prime, a MeitY and nasscom initiative (futureskillsprime.in)