AI re-engineers India’s 250 billion dollar IT dream

The Indian IT sector, now one of the foundational pillar of the country’s economy is undergoing a profound and rapid transformation – a “once-in-a-generation reset” driven by the twin forces of automation and Generative AI.

This right now is not a cyclical slowdown but a structural shift that is simultaneously shedding traditional, volume-based roles and creating an entirely new, high-value ecosystem centred on human-machine collaboration.

The end of routine execution

AI and automation are rapidly taking over routine tasks that formed the bedrock of India’s traditional IT services model. Roles most affected are those based on repetition and execution; entry-level coding, manual quality assurance (QA), L1 IT support, and legacy application maintenance.

The consequence is a measurable workforce adjustment across the board. Major firms have been restructuring teams, leading to a silent wave of what are sometimes termed ‘skill-based adjustments’. The widely reported TCS restructuring, affecting upto 2% of its workforce, and similar actions across other major IT houses and GCCs are directly linked to the integration of AI tools that automate these routine functions.

In effect, the industry is transitioning from a headcount-scaling model to an intelligence-scaling model, resulting in a hiring slowdown for generic roles and an acceleration in demand for specialised talent.

The shift to ‘Intelligence-Native’ value

At core, the transformation is simple; its automation and Generative AI tools drastically reducing the human hours required for repetitive work. The industry’s decades-old model of charging for manpower is giving way to AI-first value creation.

As Dataquest spoke to industry experts the conversations noted that the industry is shifting from ‘AI-assisted productivity’ to where intelligence is an inherent capability embedded into products and customer experiences.

As Ganesh Gopalan, Co-Founder & CEO of Gnani.ai, puts it; "The Indian IT sector is undergoing a once-in-a-generation reset. As AI takes over routine engineering and support work, the definition of a ‘fresher’ has fundamentally changed. We’re no longer hiring for task execution; we’re hiring for problem framing, adaptability, and the ability to learn new systems at velocity."

Vikas Singh, Chief Growth Officer of Turinton AI, echoes this, stating that the fresher professional entering the AI space "isn't just a developer anymore. They're an architect in training. And they need to be, because generic coding itself is being replaced by AI." This intense focus on architecture and outcomes requires workers who understand the why behind the code.

The survival skill is agility

The displacement in routine roles creates both challenges and an imperative for current and future employees; reskilling is the new job security.

For freshers, the expectation is now to enter the workforce with a big-picture mindset and critical judgment. They are expected to work alongside intelligent systems, validate AI outputs, and apply domain understanding to business-specific problems.

Kaushal Bansal, Co-founder & CEO at Callerdesk, highlights that the expectation is clear, "tasks once considered ‘basic developer/QA/support’ are increasingly automatable. Companies are now redefining entry roles to prioritise adaptive learning agility and domain-thinking rather than purely syntax-level coding."

For the vast base of mid-level professionals, upskilling is essential for career survival and growth. The most critical non-technical skills being prioritised are those that enable strategic contribution in an augmented environment:

• Learning Agility: The ability to continuously learn, unlearn, and apply new knowledge in unfamiliar situations.

• Critical Thinking: Essential for evaluating AI outputs and asking the right questions.

• Problem-Definition & Business-Context Sense: The ability to map what the user or enterprise needs and articulate the right question, partnering with AI-enabled tools to deliver outcomes.

Srinivas Reddy, SVP and Managing Director, EPAM India, confirms this dual focus, "The most critical non-technical skill we prioritise for upskilling the mid-level professionals is learning agility. We foster the ability to continuously learn, unlearn and apply new knowledge in unfamiliar situations."

Monetising outcomes, not hours

Companies are moving from simply providing efficiency to becoming engines of AI-native value creation. This is changing commercial models across the industry.

Moving away from the traditional time-and-materials licensing toward impact-based partnerships and outcome-based commercial models, success is increasingly being measured by tangible outcomes like faster customer onboarding, higher sales conversions, or cost reduction, not by the number of developers on a project.

"On the business side, AI is no longer just a tool for efficiency; it’s becoming a new value engine... These aren’t just incremental tools; they are full-stack AI engines that can take over customer experience, sales engagement, and employee support end-to-end," states Ganesh Gopalan.

The path forward for Indian IT is clear: scale intelligence, not headcount. The focus on high-end specialisation, non-technical skills like critical thinking and learning agility, and the commitment to outcome-based commercial models are together re-engineering the sector for sustained competitive advantage in the AI era.