Arjun works at a mid-sized IT services company in Pune. He has seven years of experience in Java development, a decent salary, and until about eighteen months ago, he had a reasonable confidence that his career was on solid ground.
Then his company started a project to automate the works his team handled. Not just some of them. Most of them. The project took four months. His team of twelve is now six. Three people were moved to other roles. Three were asked to leave. Arjun stayed, but not because his job was untouched. He stayed because he was the one who learned enough about the new AI-assisted testing tools to become an useful employee for the company.
He got a good salary increase for his new responsibilities. His colleague Rahul, equally experienced, equally competent in the old way of working, didn’t learn the new tools. Rahul is currently looking for a job.
This is not a dramatic story. It may be happening in hundreds of Indian companies right now, which rarely make headlines because the scale is gradual enough to avoid attention until it suddenly becomes a crisis.
The Data Behind What’s Happening
Gross hiring by Indian IT firms — Infosys, Wipro, TCS, HCL, and their peers — averaged roughly 2.3 lakh new employees per year for the five years ending in 2024. In the financial year ending March 2026, that number dropped to around 1.7 lakh. A drop of roughly 26% in new hiring volume.
At the same time, salaries for people with AI skills are going up sharply. A study by Scaler, assessed by independent research firm B2K Analytics, covering 12,000 professionals who completed structured AI and machine learning programmes. Their pre-programme salary was around ₹8 lakh. After completing the programme and getting placed, the average salary rose to ₹30 lakh — a 164% increase.
These two facts shows dramatical increase in salaries for AI-skilled professionals. The market is not collapsing. It’s bifurcating. People who have AI capability are being paid more. People who don’t are finding the market competitive than before.
What’s Actually Changing Inside IT Companies
The common assumption is that AI is replacing programmers. That’s not quite right. One has to understand the actual matters before making career decisions.
AI is replacing a specific type of programming work — the kind that involves translating a well-understood requirement into code that follows known patterns. Boilerplate code, standard integrations, common data transformations, routine bug fixes in predictable codebases. This is real work that millions of Indian IT professionals currently do, and AI tools like GitHub Copilot and similar assistants do it faster and with less error than most junior developers.
What isn’t changing: to understand what a client actually needs, designing systems that handle edge cases, debugging something genuinely required, making architectural decisions that will be required for the next five years, and managing the human side of a complex software project.
As a result, a senior engineer who deeply understands a domain, can work with AI tools to increase their output, and can take responsibility for decisions which is more valuable. A junior engineer who was primarily doing the code-generation work that AI now handles faster, is in a harder position.
This is why Cognizant launched “Project Leap” — a programme that simultaneously involves reskilling workforce and reduce headcount. The company is not reducing its capacity. It’s changing the composition of its workforce toward people who work with AI.
The Sectors Mostly Affected
BPO and back-office services — NASSCOM’s own data suggests that almost two-thirds of Indian BPO companies had already automated almost half of their data processing work by 2025. The remaining roles mostly related to judgment calls or client relationship management that requires human. Volume data entry, claims processing, and basic customer support are not growing employment categories.
Junior software development in IT services —India’s IT industry’s outsourcing models involved large teams doing defined, repeatable work for foreign clients. That model depended on the cost advantage of Indian developers plus their technical capability. AI reduces the advantage of scale because one AI-capable developer can do the work of several conventional developers. Large IT services firms are managing this by not replacing junior roles but increasing expectations from the people they hire.
Content and media — Editorial assistants, basic copywriters, and social media coordinators whose work is primarily producing standard-format content are finding their roles to be shrinking. The people who survive in these areas are the ones doing the judgment work — strategy, quality control, editorial decision-making — not the production work.
The Sectors Where Demand Is Actually Growing
Cloud and infrastructure engineering — Every company building AI systems needs reliable cloud infrastructure. Cloud architects, DevOps engineers, and infrastructure specialists who understand how to build and maintain systems as per requirement, are genuinely in demand. Salaries for experienced cloud engineers range from ₹25–₹50 lakh at the senior level.
Cybersecurity — AI makes cyberattacks more sophisticated. Defending against them requires human expertise that understands the strategy behind attacks, not just their technical signature. The cybersecurity talent gap in India is real and growing. CISA-certified and CEH-certified professionals with real experience can grab handsome payment.
Data roles with business judgment — Data analysts who run reports, are under pressure. Data professionals who can translate business problems into analytical questions, interpret results in a business context, and communicate findings to non-technical decision-makers have more value. The AI handles the computation; the human provides the business intelligence.
AI implementation specialists — Every company trying to use AI in its operations hits the same problem: the tools exist but making them work reliably for a specific business requires someone who understands both the business and the technology. This role has various names — AI product manager, AI implementation lead, AI consultant — but it’s real, it’s in demand, and it pays well.
Healthcare IT — India’s digital health infrastructure is expanding significantly. The bridge between clinical knowledge and technology skills is a talent that’s unlikely to be automated because both sides require human expertise and accountability.
What the 89% Number Say
A 2026 report by ETS (Educational Testing Service) found that 89% of Indian professionals are actively building new skills to stay relevant in an AI-driven workplace. That’s the highest percentage of any country surveyed.
There are two ways to read this.
The optimistic reading: Indian professionals are adaptable, motivated, and already moving in the right direction. The workforce is not waiting to be disrupted — it’s actively preparing.
The honest reading: 89% of people feel anxious enough about AI to be doing something about it. The fact that nearly everyone is acting, suggests the threat feels real; across the entire working population, not just in certain roles.
Both readings are probably true. The important thing is that the right response to anxiety about AI replacing your role, is not more anxiety — it’s specific action. Learning something particular that your specific role needs, is an upskilling in some sense.
The Practical Question: What Should You Actually Do
This depends on where you are in your career.
If you’re in the first three years of your career in an IT or services role, the single most important thing you can do is to become competent with AI tools in your domain — not just familiar with them, but competent enough that you produce better and faster output than others who don’t use them. This is the bar that gets you noticed and retained during the time when companies are reducing headcount in junior roles.
If you’re in the middle of your career — five to fifteen years of experience — your existing domain knowledge is a genuine asset. The question is whether you’re applying it alongside AI tools or ignoring AI tools and slowly losing ground on output, compared to people who use them. Most mid-career professionals can significantly increase their effectiveness with three to six months of serious attention to the AI tools which are relevant to their specific work.
If you’re in a senior leadership or management role, the risk is different. Your job involves judgment, relationships, and accountability — these are the things AI doesn’t replace. The risk is unaware about how the work is actually done by the teams you lead, because the tools they use are changing rapidly. Being aware of how your team uses AI —to understand it — is the relevant investment.
The One Thing to be Clear About
India’s IT job market is not collapsing. That’s not what the data shows, and it’s not what people inside the industry are experiencing.
What it shows is that the market is being repriced. Roles that involve executing common or known solutions to common/known problems are worth less. Roles that involve judgment, design, client understanding, and working with AI tools are worth more.
The people in Arjun’s situation who stayed and adapted are doing fine. The people who treated the change as someone else’s problem until it arrived at their desk are having a harder time.
The useful takeaway is this: the window to adapt is open, and it’s shorter than it looks from the outside.
Where are you in this picture? Share your sector and situation in the comments — the discussion here usually helps people figure out what to do next more than any article can.