The Great Divide in AI Talent
On the surface, the story of AI in India is one of explosive growth. A recent Nomura report highlights that for every job impacted by AI, 2.6 new ones are being created, with 83,100 AI-related hires against roughly 31,921 layoffs. But beneath this positive
headline, a significant shift is creating a two-tier labour market. The first tier consists of execution-focused roles, such as data annotation, running existing models, and performing routine technical tasks. These jobs are foundational but are also the most susceptible to automation and downward pressure on wages. The second, more lucrative tier belongs to a new class of professional who can bridge the gap between technical possibility and business reality. These are the individuals companies are scrambling to hire, often at a significant premium.
Tier One: The Strategic Business Technologist
The top tier of the AI hiring market is defined by roles that require more than just programming. Companies are seeking experienced professionals who combine deep technical expertise in areas like machine learning, generative AI, and MLOps with a sharp understanding of business operations. These are roles like AI Product Manager, AI Strategist, and senior Machine Learning Engineers who can ask the right business questions before building a technical solution. They are expected to understand profit and loss, identify revenue opportunities, and translate complex AI capabilities into tangible business value. This combination is scarce, and the salaries reflect it. Senior specialists can command salaries well over ₹40 LPA, with roles that blend AI and business strategy seeing some of the sharpest increases in compensation.
Tier Two: The Foundational Implementers
The second tier forms the backbone of the AI industry. It includes a wide range of crucial but more commoditized roles like junior AI engineers, data analysts, and support staff for AI systems. While demand for these roles exists, this is also where the impact of automation is most felt. As AI tools become better at coding, testing, and customer support, the demand for entry-level workers is weakening. An ICRIER survey noted that 55% of companies reported a decline in entry-level hiring, a stark contrast to the 14% reporting a decline in senior-level recruitment. While these jobs provide a vital entry point into the tech sector, they no longer serve as the guaranteed ladder to higher-paying positions without significant and continuous upskilling.
Why Business Acumen Is the New Gold
The market is bifurcating because AI is no longer a research experiment confined to a lab; it's a core driver of business strategy. Companies have moved past the 'what is AI?' phase and are now focused on 'how can AI increase our market share?'. This requires people who can speak both languages fluently—the language of algorithms and the language of balance sheets. Hiring managers report that while technical skills get candidates an interview, it's the ability to demonstrate a clear understanding of business impact that gets them hired and promoted. According to a NASSCOM survey, 68% of hiring managers in India now consider communication and business-facing skills as important as technical expertise for AI roles. The most valuable professionals are those who can ensure that massive investments in AI technology result in measurable business outcomes.
Navigating the New Job Market
For professionals and fresh graduates, this new reality demands a strategic approach to career development. Simply graduating with a computer science degree is no longer enough. Employers are prioritising skills-first recruitment, looking for candidates who can show proof of work through internships and real-world projects. For those currently in the foundational tier, the path to the top involves actively seeking out opportunities to develop business understanding. This could mean taking courses in finance or marketing, volunteering for cross-functional projects, or focusing on a specific industry to build domain expertise. The goal is to evolve from being a builder of AI tools to becoming a solver of business problems using AI tools. This pivot is the key to unlocking the highest value in India's dynamic new AI economy.
