Even as restructuring and layoffs happen, some jobs in the IT sector are getting paid well - and across levels whether entry or senior.
Till a few years ago, software engineers in India were commanding high salary premiums and the IT sector was a reliable source of employment. While still employing lakhs, the artificial intelligence-led disruptions have meant that there is growing uncertainty on the relevance of traditional IT sector roles.As Neeti Sharma, CEO of TeamLease Digital says, “Every few years, the labour market crosses a threshold that is easy to miss in the moment and impossible to reverse in hindsight. India's digital workforce crossed one this year.”“This landscape brings immense opportunity, but it also collapses old certainties about how talent is valued. Job titles and role definitions are becoming less reliable indicators of capability or compensation,” she says.Even as restructuring and layoffs happen, some jobs in the IT sector are getting paid well - and across levels whether entry or senior. Which roles are in demand? What are the average salary levels for special capability sets and which roles are under pressure?
What are the salary levels for those getting hired at premiums?
The fundamental point to understand is that India’s technology talent market is witnessing a shift towards skill-differentiated compensation; with specialised capabilities in AI, machine learning, cloud engineering and data science becoming increasingly valuable.
According to a TeamLease Digital report on Digital Skills and Salary Primer FY2026-27, there is a widening pay gap in India’s technology sector, with premiums increasingly going to professionals who can build, integrate, secure and manage AI systems. Routine, execution-led roles are facing greater salary pressure, while specialised skills are becoming more valuable.
AI’s Role Disruption Map
The premium concentrates in four families, AI, Data, Cloud and Cybersecurity, and peaks where capability depth meets governance and scale.And, this divide is visible across AI skill tiers. For example, the report puts entry-level median pay for AI-core roles at Rs 13.2 lakh, compared with Rs 9-10.2 lakh for AI-adjacent roles and Rs 4.8-5.4 lakh for AI-support roles. The projected salary growth is 16-21% for AI-core, against 13-18% for AI-adjacent and 7-8% for AI-support.Not only that, the premiums also extend to architecture, data and cybersecurity.
The report says that skills such as GenAI engineers, AI architects, ML platform and cloud security are the highest in demand.
Entry level salaries
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. These figures reflect the value that is being placed on designing, securing and governing complex technology systems, beyond coding alone.“The 108.6 LPA figure is the median for AI Architects with 15+ years in our analysis of 37,000 roles. It reflects a senior role, not a market-wide norm. The differentiator is the ability to own architecture, scale production systems, manage risk, and connect technical decisions to business outcomes,” explains Neeti Sharma, CEO of TeamLease Digital.
Entry-level salaries for Tier 2 AI-Adjacent
Also, geographies no longer define premiums as much. For example, according to the report, a GenAI engineer in Indore earns around Rs 16.5 lakh per annum, and out-earns cybersecurity talent in Bengaluru that gets Rs 14.4 lakh.Milind Shah, Managing Director, Randstad Digital - India tells TOI that the compensation for niche AI roles can vary considerably depending on the depth of expertise, role complexity and business impact. On an average, talent with niche tech skills may command anywhere between a 10-25% premium.
Entry level salaries for Tier 3 AI-Support
Why are these roles commanding a premium? It’s a mix of skill shortage and the roles themselves generating more business value that routine IT jobs no longer are.According to Neeti Sharma, only about 16% of India’s IT professionals hold AI skills, so the supply is thin. She explains that companies are not able to find people who can take AI from pilot to production and stand accountable for it.“But this is not wage inflation. The market is pricing roles whose output is the AI system itself, which makes them the hardest to substitute. Routine support keeps operations running, and that is the layer AI is compressing first.
Employers are paying for scarcity, and for people who can own the outcome,” she tells TOI.
So, what can IT sector professionals do?
Reskilling is central to the shift. The TeamLease report points to pathways such as moving testers into intelligent operations, analysts into decision intelligence, and mid-career professionals into platform, product, governance and architecture roles.Its broader message is that combining core technical expertise with AI skills, domain knowledge and business judgement will increasingly determine salary growth.Milind Shah shares strategies for every level:
- At the entry level, he says professionals with strong foundations in software engineering, data and AI application can distinguish themselves through practical implementation skills.
- At the mid-career level, expertise in areas such as AI engineering, machine learning operations and enterprise AI integration becomes particularly valuable as organisations look to move beyond experimentation towards deployment at scale.
- At the senior level, compensation increasingly reflects the ability to architect enterprise AI systems, lead transformation programmes and ensure that technology investments deliver measurable business outcomes, he adds.
Early and Mid Career Salary Trends Across Roles
Biggest takeaway
So, what does this mean for tech professionals? The biggest takeaway is that professionals need to shift from being defined by the roles they perform to the capabilities they bring to the business.“As AI becomes embedded across technology functions, the value of talent will increasingly depend on the ability to adapt, solve complex problems and apply emerging technologies to real-world business challenges,” Milind Shah says.
- For early-career professionals, this means building strong technical fundamentals while gaining hands-on experience in AI, data and cloud technologies.
- For mid-career professionals, the priority is to move beyond execution and develop the ability to integrate technologies, improve workflows and translate domain expertise into scalable solutions.
- For senior professionals, the focus must extend to strategic decision-making, enterprise-wide AI adoption, governance and the ability to connect technology investments with business performance, he says.
For people who are in traditional IT sector roles, it’s important to understand that while the jobs are not disappearing, routine execution roles are reducing.Repetitive reporting, manual testing, basic operational support and rule-based processing face pressure as AI and automation reshape work. The report does not suggest that all these jobs will disappear; rather, salary growth may slow unless workers move towards higher-value responsibilities.
AI capability maturity framework: From skills to salary premiums
“Those in repetitive reporting, manual testing, and basic support are most exposed. The route up is adjacency, not reinvention: a BI analyst into data engineering, a sysadmin into cloud, a QA or IAM specialist into security and governance. Pair one technical skill with deep sector knowledge, and keep proof of work that moves a business outcome,” Neeti Sharma says.Not only that, this shift also has implications for how professionals approach career development.So if you are planning to upskill to keep yourself relevant, understand that it should not be driven solely by the popularity of a technology or the prospect of a higher salary.“Instead, employees should identify the capabilities emerging as critical within their industry, understand how these capabilities address business needs and build demonstrable expertise through practical application,” Milind Shah advises.