90% of engineering graduates AI-native or AI-proficient: Nasscom study
Nasscom's AI-native index finds nine in 10 engineering graduates are AI-native or AI-proficient, but identifies gaps in orchestration and technical grounding
About 90 per cent of India’s early career technology talent is either artificial intelligence (AI) native or AI proficient, a Nasscom report said, highlighting a critical component in enterprise AI adoption, even though it has lagged behind expectations in the last few years.
The study assesses AI native capability across 11 dimensions which include AI reliance, fluency, orchestration, creation, judgement, cognitive independence, technical grounding, learning, foundational capability, AI-augmented productivity, and responsible AI use. It covers final year engineering students in computer science and related disciplines, as well as technology professionals with up to three years of work experience.
The index, with an overall score of 62, establishes a baseline for understanding how India's future technology workforce is adapting to an AI-first world and for tracking its evolution in the years ahead.
“The overall score reveals that AI-native capability is uneven across dimensions. India’s early career technology talent demonstrates relative strengths in AI judgement, foundational capability and responsible AI use, while significant capability gaps emerge in AI orchestration and technical grounding. These findings suggest that although AI adoption has become widespread, building deeper engineering capability remains the next frontier,” the report said.
Within that capability, AI proficiency was predominant at 68 per cent, followed by AI native at 23 per cent. This suggests that the next challenge is no longer about driving AI adoption, but accelerating the transition from AI proficiency to AI nativeness through stronger engineering judgement, orchestration, and technical depth.
The report cautions that being AI native is not just about certifications, tool usage and familiarity with prompting techniques. It is rather defined by the ability to collaborate productively with AI, critically evaluate and challenge AI-generated outputs, build and orchestrate AI-powered solutions, and retain independent reasoning and engineering judgement when AI falls short of expectations.
“These dimensions assess how effectively talent collaborates with AI, solves real-world problems, builds AI-enabled solutions responsibly, exercises independent judgement while retaining strong technical foundations and avoiding excessive reliance on AI,” the report added.
The technology and IT services industry has shown a propensity to hire young engineering graduates with niche skills in recent times, saying it's easier to work with them as they are more nimble and at ease while working with the newest technology tools.