More Than Just Code
The narrative of mass job losses in coding overlooks a crucial point: AI is a tool of augmentation as much as automation. While generative AI can write basic code snippets, its real impact is in automating repetitive and routine tasks across various functions
within an IT organisation. This frees up human professionals to focus on higher-value activities that require strategic thinking, creativity, and complex problem-solving. The focus is shifting from performing manual tasks to orchestrating AI-driven systems. This means roles are evolving rather than simply disappearing. While entry-level hiring for roles dependent on structured tasks has seen a decline, the demand for professionals who can leverage AI is growing rapidly.
The Changing Face of Quality Assurance
The Quality Assurance (QA) or testing domain is undergoing a profound transformation. Traditionally, QA involved extensive manual testing, a repetitive and time-consuming process. Today, AI-powered tools are automating much of this work. These tools can generate test cases, predict potential defects using historical data, and even perform 'self-healing' automation, where the AI automatically updates broken test scripts. Consequently, the role of a QA professional is shifting from a manual tester to a Quality Strategist. Their job now involves designing comprehensive testing strategies, validating AI models for bias and fairness, and ensuring the overall reliability of increasingly complex, AI-integrated applications. This requires a new set of skills, including an understanding of machine learning models and data quality assessment.
Project Management in the AI Era
Project and program management are also being reshaped. AI tools can now handle many of the administrative burdens of project management, such as resource allocation, progress tracking, and risk prediction. This allows project managers to focus on strategic stakeholder management, navigating complex project dependencies, and ensuring that the project delivers real business value. The modern IT project manager needs to be as fluent in reading an AI-generated risk assessment report as they are in managing a project plan. They are becoming orchestrators of human and AI collaboration, ensuring that teams are using these new tools effectively to improve productivity and outcomes.
The Rise of New and Hybrid Roles
While some tasks are being automated, AI is also creating entirely new job categories. The Indian IT industry is seeing a surge in demand for roles like AI Engineer, Machine Learning Specialist, AI Product Manager, and Prompt Engineer. Beyond these specialised roles, many existing jobs are becoming 'hybrid'. For example, a business analyst might now use AI for data analysis to generate deeper insights, or a cybersecurity expert might use AI to detect threats more effectively. The biggest advantage in the current job market comes from having a combination of skills, such as AI expertise combined with deep domain knowledge in a specific industry like finance or healthcare. Job postings seeking AI skills have more than doubled, and this demand is spreading to non-tech roles as well.
The Urgent Need for Upskilling
This transformation underscores a critical need for continuous learning and upskilling. A recent NASSCOM report highlighted a concerning gap: while many young tech professionals are proficient in using AI tools, only a small fraction are truly 'AI-native'—possessing the deep engineering judgment to build with and command AI effectively. The industry risks creating a workforce that is AI-reliant rather than AI-driven. To stay relevant, professionals across all IT functions must move beyond just using AI and learn to integrate, manage, and innovate with it. Companies are increasingly moving away from broad-based volume hiring towards recruiting specialists, with skills in AI, cloud, and cybersecurity commanding significant salary premiums. The future of career growth in Indian IT is tied not to years of generic experience, but to demonstrated expertise in these emerging technologies.
