India IT jobs are entering a more divided phase as artificial intelligence reshapes the value of technology work. A TeamLease Digital report cited by The Times of India indicates that specialised capabilities in artificial intelligence, data, cloud engineering and cybersecurity are attracting substantial salary premiums, even as routine execution-led roles face greater pressure from restructuring and layoffs.
The shift is not simply about a new list of high-paying occupations. It points to a change in how India’s technology workforce is organised and rewarded. Job titles that once served as reasonably reliable signals of career progression are becoming less useful as employers place greater value on what professionals can build, integrate, secure, govern and connect to business outcomes.
Neeti Sharma, chief executive officer of TeamLease Digital, described the moment as a threshold for India’s digital workforce. In her assessment, the market is moving away from broad role-based valuation towards capability-based compensation. The distinction matters for cities because the technology sector has long supported large concentrations of skilled employment, office demand and household incomes across India’s urban economy.
The report, Digital Skills and Salary Primer FY2026-27, identifies four areas where premiums are concentrating: AI, data, cloud and cybersecurity. The highest-value positions are those that combine technical depth with responsibility for architecture, production systems, risk and scale. The compensation figures cited in the report show how sharply the market differentiates between these capabilities.
For entry-level roles, median pay for AI-core positions is placed at Rs 13.2 lakh a year. This compares with Rs 9 lakh to Rs 10.2 lakh for AI-adjacent roles and Rs 4.8 lakh to Rs 5.4 lakh for AI-support roles. Projected salary growth is also higher for the AI-core category, at 16% to 21%, compared with 13% to 18% for AI-adjacent roles and 7% to 8% for AI-support roles.
These figures describe a hierarchy within AI itself. They suggest that exposure to the technology is not enough to secure a premium. The market is distinguishing between professionals who support AI-related work and those who can develop, deploy or take responsibility for complex systems. That distinction is likely to affect how workers choose training, how employers define career ladders and how cities compete for specialised talent.
At the senior end, the report lists annual salaries of Rs 1.08 crore for AI architects, Rs 1.02 crore for industrial data architects and Rs 95.8 lakh for OT security architects. Sharma clarified that the Rs 108.6 lakh figure for AI architects is the median for professionals with more than 15 years of experience, based on an analysis of 37,000 roles. It is therefore not a market-wide salary norm, but an indicator of the value attached to senior professionals who can take ownership of architecture, production scale, risk and business outcomes.
This is an important qualification. Headlines about crore-plus salaries can obscure the structure beneath them. The premium is concentrated in senior and specialised roles rather than distributed across the entire IT workforce. The same market that rewards scarce expertise can place slower salary growth and greater uncertainty on routine work. The result is not a uniform technology-sector boom, but a sharper segmentation of employment.
The roles identified as being in strong demand include GenAI engineers, AI architects, machine learning platform specialists and cloud security professionals. Randstad Digital India managing director Milind Shah told The Times of India that niche technology skills may command a premium of between 10% and 25%, depending on expertise, complexity and business impact.
The geography of these premiums is also becoming less predictable. The report cited in the article places the annual pay of a GenAI engineer in Indore at around Rs 16.5 lakh, above the Rs 14.4 lakh cited for cybersecurity talent in Bengaluru. This comparison does not establish a general salary ranking between the two cities, but it does challenge the assumption that the largest established technology hubs will always offer the highest compensation for every specialised skill.
For urban economies, that is a notable signal. Technology employment has traditionally been associated with a limited group of large metropolitan centres, where companies, institutions and skilled workers have clustered. If highly specialised capabilities can attract premiums in cities outside the most prominent technology hubs, the distribution of opportunity may become more skill-specific and less dependent on a worker’s location alone. The material supplied does not establish whether this will produce a broad relocation of jobs or companies, but it does show that city-based assumptions about pay are becoming less secure.
The underlying mechanism is scarcity. Sharma said only about 16% of India’s IT professionals hold AI skills, leaving companies with a limited pool of people who can take AI projects from pilot stages to production and remain accountable for their results. In this account, the premium is not simply wage inflation. It reflects the difficulty of finding workers who can manage the full operational and institutional burden of AI systems.
That burden extends beyond coding. AI architects, data architects and security specialists are valued because their work sits at the intersection of technical design, governance, risk and organisational performance. As more companies attempt to move from experimentation to deployment, the ability to integrate systems and manage consequences becomes as important as the ability to create a model or write software.
The contrast with routine work is direct. Repetitive reporting, manual testing, basic operational support and rule-based processing are described as the areas facing the greatest pressure. The report does not say that these jobs will disappear. Instead, it indicates that salary growth may slow unless workers move towards higher-value responsibilities. That distinction is significant for urban livelihoods: employment can remain available while the path to wage growth becomes more demanding.
The recommended transition is one of adjacency rather than complete reinvention. A business intelligence analyst could move towards data engineering, a system administrator towards cloud work, and a quality assurance or identity-and-access-management specialist towards security and governance. For workers, the implication is that existing experience remains useful when combined with a new capability and demonstrated through practical outcomes.
The report and the comments cited by The Times of India divide this challenge across career stages. Entry-level professionals are expected to build foundations in software engineering, data and AI applications, while also developing practical implementation skills. Mid-career workers may benefit from AI engineering, machine learning operations and enterprise AI integration as organisations seek deployment at scale. Senior professionals are increasingly assessed on their ability to design enterprise systems, lead transformation programmes, manage governance and connect technology spending to measurable business results.
This changes the institutional role of employers as well. If companies value capability more than titles, internal training and career progression cannot remain tied only to conventional job categories. Workers moving from testing to intelligent operations or from analysis to decision intelligence need pathways that recognise transferable experience. The supplied material does not provide evidence on how widely employers are creating such pathways, but it identifies reskilling as central to managing the transition.
It also places limits on the usefulness of technology fashion. Employees are advised not to choose training solely because a particular tool is popular or associated with a high salary. The more durable combination is technical ability, industry knowledge, practical application and business judgement. In other words, the premium is attached not only to knowing a technology, but to using it to solve an organisational problem and taking responsibility for the result.
For cities, the broader question is whether the next phase of the technology economy will expand opportunity or deepen inequality within the skilled workforce. The available evidence confirms a widening difference between AI-core, AI-adjacent and AI-support roles, as well as significant premiums for senior architecture and security positions. It also shows that location alone does not determine the value of specialised work. What remains uncertain is how many workers can move across these capability tiers, how employers will redesign training and whether salary premiums will spread beyond a relatively narrow group of professionals.
The immediate signal is clear: India’s technology labour market is no longer rewarding IT work as a single category. It is increasingly pricing scarcity, system ownership, governance and measurable business impact. The cities that depend on technology employment will therefore be shaped not only by the number of jobs created, but by the quality of capabilities their workers can build and sustain.
