India’s engineering workforce faces a widening AI-confidence-capability gap: Study
The study, which surveyed 400 experienced software engineers and tech recruiters, found that while AI is reshaping engineering roles, there is a significant gap between perceived AI readiness and actual deep expertise. A striking 89% of engineers believe they are AI-ready, yet only 19% are deeply engaged in building AI/ML systems, highlighting a substantial gap between confidence and demonstrable skill.
Engineers cite key obstacles to upskilling: 55% cite a lack of time due to work demands and 49% highlight the financial barriers to accessing quality training. These considerations prevent even highly motivated professionals from gaining the hands-on experience and depth required for advanced AI work.
The study also uncovers a pronounced equity risk for women in tech. 65% of women engineers report severe work-life balance pressures that limit their learning time and 56% cite a lack of AI mentors or role models as a significant barrier. These disproportionate challenges risk exacerbating existing gender disparities in the evolving AI landscape.
“The study clearly shows India’s AI ‘confidence-capability gap’: immense enthusiasm for AI, but a real lack of great, hands-on skills to build and own AI systems. In today’s uncertain job market with ongoing changes, this gap threatens individual careers and India’s tech leadership. Companies need engineers with proven, practical AI skills—not just familiarity with tools—to drive innovation,” said Abhimanyu Saxena, co-founder of Scaler.
“Closing this gap is crucial. It means offering structured, project-based learning to make engineers vital builders of our AI future,” he added.
The implications of this gap are acutely felt in hiring. Recruiters are tightening standards, with 86% reporting challenges in finding genuinely AI-skilled candidates. This pushes companies to rely more on practical validation, such as technical tests and real-world projects, rather than self-reported proficiencies, making it harder for candidates to demonstrate their capabilities if they lack deep, applied experience.
“Our research highlights a core paradox in India’s AI talent ecosystem: signal versus substance,” said Prabhu Ram, vice-president, industry research group at CyberMedia Research. “While 89% of engineers express AI readiness, only 19% are engaged in sustained AI system development. This divergence is distorting hiring signals and creating friction for both employers and candidates. Recruiters are responding by tightening evaluation frameworks and placing greater emphasis on technical tests, real-world projects and depth of problem-solving.”
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