The New Salary Hierarchy
The latest 'Digital Skills & Salary Primer' from TeamLease Digital confirms what many in the industry have suspected: specialised AI skills now come with a significant salary premium. The report highlights a market that is splitting into distinct tiers,
with 'AI-Core' roles—those that involve building, training, and deploying AI systems—commanding far higher pay than 'AI-Support' roles. According to the data, professionals with skills in generative AI, machine learning, and data science can earn between 30% and 60% more than their peers in traditional IT roles with similar experience. This pay disparity isn't just a minor fluctuation; it represents a fundamental change in how companies value technical expertise, rewarding the ability to create and manage intelligent systems over more routine IT functions.
The Numbers Behind the Shift
The salary data reveals a gap that widens dramatically with experience. A GenAI Developer with zero to two years of experience can expect to earn around ₹11.2 LPA, while a Technical Support Engineer at the same level earns approximately ₹5.2 LPA. This gap expands further up the career ladder. At the six-to-eight-year experience mark, a GenAI or Machine Learning role can command a salary between ₹31-35 LPA, while a support role might offer around ₹14.6 LPA. In some cases, senior AI professionals in Global Capability Centres (GCCs) can earn upwards of ₹58-60 lakh annually. The driving force behind this is a classic case of demand outpacing supply. TeamLease estimates a talent gap of 53% for Generative AI skills, with the demand for such talent projected to cross one million roles by 2026.
The Most In-Demand Roles
The premium salaries are concentrated in a few key areas. The most sought-after professionals are those who can do more than just use AI tools; they are the ones who can build and integrate them. Roles like Machine Learning (ML) Engineer, GenAI Developer, MLOps Engineer, and AI Product Manager are at the top of the pay scale. An ML Platform Architect with over 15 years of experience can earn as much as ₹94.8 LPA. These 'AI-Core' professionals are responsible for the heavy lifting: designing algorithms, building data pipelines, and ensuring AI models are scalable and reliable. Following them are 'AI-Adjacent' roles like Data Engineers and Cloud Engineers, who also see a significant pay bump compared to their counterparts in more traditional IT functions.
A Crossroads for Traditional IT
The rise of AI-core jobs has created a challenging environment for professionals in conventional IT roles. While reports of AI destroying jobs may be overstated, it is undeniably reshaping them. There is mounting pressure on routine work like manual testing, basic operational support, and repetitive reporting. Some reports indicate that salaries in legacy IT services have stagnated or even declined over the last couple of years. Entry-level hiring for these roles has also shrunk, with some firms cutting fresher intake by as much as 20-25% due to automation. The clear message from the market is that experience alone is no longer the primary determinant of pay; it's the ability to work with and build upon AI systems that now dictates value.
The Upskilling Imperative
For India's vast tech workforce, this shift makes continuous learning non-negotiable. While reports indicate that around 20 lakh professionals have been upskilled in AI, only about 3 lakh possess the advanced skills that companies are willing to pay a premium for. The distinction is crucial. Simply knowing how to use an AI tool is becoming a baseline expectation. The real career growth and financial rewards lie in developing a deeper expertise in areas like Generative AI, machine learning, natural language processing (NLP), and cloud computing. The future belongs to those who can move from being users of AI to becoming its architects and integrators. For companies, the challenge is to build internal pathways that allow employees in support roles to graduate into core AI work, preventing a talent drain and building a future-ready workforce from within.
