Entry-Level Coding and Development
For years, the Indian IT industry has been a gateway for fresh graduates to enter the workforce through roles that involved writing basic, functional code. This is one of the areas feeling the most immediate impact of AI. Generative AI tools like GitHub
Copilot can now produce routine code snippets, complete functions, and even suggest bug fixes in hours, a process that once took days. This doesn't mean developer jobs are disappearing; it means the nature of the work is shifting. Companies now expect junior developers to use AI as a productivity tool, moving their focus from writing boilerplate code to higher-value tasks like system design, integration, and complex problem-solving. Hiring for entry-level positions has slowed as companies find AI can handle many routine tasks previously assigned to junior employees.
Quality Assurance and Software Testing
The role of the software tester is undergoing a seismic shift from manual validation to strategic quality engineering. Manual, repetitive testing is one of the functions most susceptible to automation, and AI is accelerating this trend. AI-powered tools can now generate test cases, predict areas of high risk, and run regression tests more efficiently than human teams. As a result, roles focused purely on manual execution are declining. However, the demand for Quality Assurance (QA) professionals with AI skills is booming. The new-age QA engineer is expected to manage AI-driven testing tools, interpret their outputs, focus on complex user experience validation, and build robust quality architecture—tasks that require critical human judgment.
Project Management and Support Roles
The changes extend beyond pure coding and testing. AI is also beginning to augment roles in IT project management and L1 support. AI agents can now handle proactive system monitoring, incident triaging, and basic customer support queries, reducing the need for large teams dedicated to these tasks. This allows human staff to focus on exceptions and more complex issues in what some are calling a 'human by exception' model. For project managers, AI tools can assist in optimizing resource allocation, predicting project timelines, and analyzing team productivity. The role is evolving from a coordinator to a strategic overseer who leverages AI-driven insights to make better decisions.
The Dawn of New AI-Centric Roles
While some traditional roles are being redefined, AI is also creating a host of entirely new job profiles that are in high demand. The Indian job market is seeing a surge in listings for AI/ML Engineers, Data Scientists, AI Model Trainers, and Prompt Engineers. Companies are actively seeking professionals who can build, fine-tune, and deploy AI models. New, highly specialized positions like MLOps (Machine Learning Operations) Engineers, who manage the lifecycle of machine learning models, and Agentic AI Developers, who build autonomous AI systems, are also emerging. These roles often command premium salaries due to the scarcity of specialized talent.
The Upskilling Imperative for All
The clear message across the industry is that evolution is essential for survival and growth. According to NASSCOM, a significant majority of employers report that AI has already impacted job responsibilities. The path forward lies in upskilling. For developers, this means moving from being a creator of code to an orchestrator of AI tools. There is a growing emphasis on skills-based hiring, where demonstrable expertise in AI, cloud computing, and data analytics is valued over traditional qualifications. Beyond technical skills, employers are also seeking professionals with strong problem-solving abilities, strategic thinking, and domain expertise, as these are areas where human intelligence remains irreplaceable.
