Large Indian IT firms have been cutting headcount while their revenue holds steady. Models write working code every day. So is the industry ending? No. But its shape is changing, and pretending otherwise does not help anyone deciding what to study.
What is actually happening
Four things at once, and they pull in different directions.
- Junior coding work is thinning. A model writes basic create-read-update-delete code quickly and adequately. That was the traditional first rung.
- Manual testing is being automated hard. Test case generation is one of the things models are genuinely good at.
- First-line support is going to chatbots. Not entirely, but enough to change hiring.
- Senior demand has gone up. Somebody has to review what the machine produced, and that somebody needs judgement you cannot prompt for.
The net effect is a widening gap. The top of the market is paying more and the entry level is paying less, and the middle is where it feels most uncomfortable.
Roles under real pressure
- Manual testers
- First-line IT support
- Generic content writing
- Data entry
- Front-end work that is only forms and buttons
- Routine translation
The common thread is not "easy work". It is work where the output is predictable from the input, and where being roughly right is good enough.
Roles getting more valuable
- AI and ML engineers — the people training and fine-tuning, not just calling an API
- AI operations — running these systems reliably in production is a real discipline now
- Software architects — deciding what to build, and what not to
- Cybersecurity — attackers got the same tools everyone else did
- DevOps and cloud — none of this runs without infrastructure
- Data engineers — models are only as good as the pipeline feeding them
- Domain experts who can code — finance plus Python, healthcare plus ML. This one is underrated and it is where the biggest jumps happen.
What salaries look like
These are indicative ranges from hiring conversations in the Indian market, not survey data. Treat them as direction rather than precision.
| Role | Around 2022 | Around 2026 |
|---|---|---|
| Fresher developer | ₹4–6 LPA | ₹3–5 LPA (down) |
| 2–3 year engineer | ₹8–12 LPA | ₹7–12 LPA (flat) |
| 5+ year senior | ₹20–35 LPA | ₹30–60 LPA (up) |
| AI / ML, 5+ years | ₹25–40 LPA | Well past ₹50 LPA at the top |
The interesting number is not the top of the table. It is the first row going backwards, because that is the rung most people are standing on when they read an article like this.
What to learn in 2026
- Fundamentals, properly. Data structures and system design still decide interviews, and they decide them more now, not less — because everything above that layer got cheaper.
- Python and ML basics. This has quietly become table stakes rather than a specialisation.
- Cloud. AWS or GCP, enough to deploy and debug something real.
- One vertical, deeply. Fintech, health-tech, ed-tech — domain knowledge is the part a model cannot pick up from your prompt.
- Communication. Unglamorous and consistently the thing that separates two engineers of equal skill.
- Fluency with the tools. Cursor, Copilot, Claude. Not as a novelty — as part of how you work daily.
What India specifically has
Scale and cost, still. Even with strong tooling, products need people who understand the problem, and there are a lot of them here. The shift is that the same person is now expected to produce considerably more, because the tools removed the slow parts.
The old team shape was many juniors and a few seniors. The new one is fewer, more senior people with good tooling producing the same product. That is why the middle layer feels squeezed — it is being squeezed.
A practical plan
- Stop treating AI as a threat and put it in your daily workflow. The people doing this are pulling ahead measurably.
- Invest in the two things models are worst at — domain understanding and dealing with people.
- Build something public. A repository, a blog, anything with your name on it. Visibility compounds.
- Aim at seniority deliberately, because the junior rung is the one that is narrowing.
- Ship one side project that uses AI properly. It teaches you more than any course and it is a better interview answer than a certificate.
Where this leaves you
The industry is not shrinking. It is changing shape, and the change rewards people who adapt quickly and punishes people who assume 2015 still applies. That has happened before in this field, and it will happen again.
If you are building a product and want it done the modern way, talk to us. We use these tools daily, and a person still reads every line before it ships.
FAQs
Should freshers still enter the IT industry?
Yes, but with stronger fundamentals and real fluency with AI tools. The old route of learning one language and waiting for a placement is genuinely closing. Depth in a domain plus the ability to ship still gets hired.
Are developers with five years of experience safe?
Generally yes, provided they use the tools. Experience without adaptation ages faster than it used to, because the gap between an engineer who uses AI well and one who does not is now visible in output.
Which skills are hardest for AI to replace?
Domain knowledge, system design and communication. All three depend on context that lives outside the codebase — in the business, the users and the constraints nobody wrote down.
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