Cons of the IT Field: An Honest Look at AI Layoffs, Job Security & Constant Learning
IT and software have created millions of well-paid jobs and remain a fantastic career for many. But every student deserves the honest picture before committing. This article isn’t here to scare you — it’s here to prepare you. Here are the real downsides of the IT field in the AI era, and exactly how to protect yourself against each one.
1. AI is reshaping entry-level work
Generative AI and coding assistants now handle a large share of routine tasks — boilerplate code, basic testing, first-draft documentation and simple support tickets. Historically these were the tasks that freshers learned on. As AI absorbs them, companies hire fewer people for purely repetitive work and expect new engineers to add value above what AI can do.
The takeaway isn’t “AI will take all jobs.” It’s that low-skill, repetitive IT work is shrinking, while demand for people who can design, judge and direct AI is rising.
2. Layoffs & hiring cycles are real
Since 2023, the tech industry has seen repeated, large layoff waves across startups and even the biggest companies, driven by over-hiring during the pandemic boom, cost-cutting, restructuring and a shift of budgets toward AI. Key patterns to understand:
- It’s cyclical: tech hiring booms and contracts with the economy — more than many core-engineering or government roles.
- Nobody is fully “safe”: layoffs have hit experienced engineers at top firms, not just freshers.
- Location matters: service companies, product companies and startups have very different stability profiles.
3. Never-ending learning (upskilling is mandatory)
In most fields, your degree knowledge lasts years. In IT, frameworks, languages and tools change constantly. What’s in demand today may be legacy in five years. This is exciting for some and exhausting for others.
- You must invest personal time in learning — often on weekends.
- Stagnating for even 2–3 years can make your skills outdated.
- “Continuous learning” is not optional; it’s the job.
4. Job security depends on your skill tier
IT job security is not uniform. It’s a spectrum:
- Highly automatable roles (basic manual testing, simple support, repetitive maintenance) are most at risk.
- Judgement-heavy roles (system design, architecture, security, ML, product engineering) are far more secure.
- The gap between “average” and “strong” engineers is widening — strong engineers are in more demand than ever.
5. Other honest downsides
- Burnout & screen time: long hours, tight deadlines and on-call rotations can affect health.
- Bench & project uncertainty in service companies — you may wait for projects or switch domains suddenly.
- Commoditisation: when a skill becomes easy to learn, salaries for it flatten.
- Comparison & pressure: constant social-media comparison of packages and switches.
How to future-proof your IT career
- Go deep, not just wide: master fundamentals — DSA, system design, CS core — that don’t expire. See our CS fundamentals.
- Learn to use AI, don’t fear it: engineers who direct AI tools will replace those who ignore them. Read How to Become an AI Engineer.
- Build real projects & a portfolio that prove judgement, not just syntax. See 5 Important Engineering Skills.
- Keep an emergency fund (3–6 months) so a layoff is a setback, not a crisis.
- Network continuously on LinkedIn — most opportunities come through people, not portals.
- Stay curious: treat learning as part of the job, not a chore.
IT is still a great career — for those who keep learning and build genuine skill. Walk in with open eyes, invest in yourself continuously, and the “cons” above become manageable rather than career-ending.