CMR-Scaler study reveals why 86% of recruiters struggle to find skilled engineers

India’s software engineering workforce faces a growing "confidence–capability gap," according to a joint study by Scaler and CyberMedia Research (CMR). The report, which surveyed 400 experienced engineers and tech recruiters, found that while 89% of engineers believe they are prepared for AI roles, only 19% currently build AI or machine learning systems.

This data suggests that while engineers show high interest in AI, few possess the deep technical expertise required to develop and own complex systems. This divergence creates friction in the labour market, as self-reported proficiency often fails to meet technical requirements during the hiring process.

Structural barriers to upskilling

The research identifies specific obstacles that prevent motivated professionals from gaining applied experience. Work demands leave 55% of engineers with a lack of time for training, while 49% cite the high financial cost of quality programs. These factors limit learning to surface-level tool use rather than comprehensive system development.

Gender disparities also persist in the path to AI proficiency. The study indicates that women engineers face higher hurdles, with 65% reporting that work-life balance pressures restrict their learning time. Furthermore, 56% of women cited a lack of AI mentors or role models as a primary barrier to their professional growth in this field.

The recruiter’s challenge

The mismatch between perceived and actual skill affects hiring standards. Approximately 86% of recruiters report difficulty finding candidates with genuine AI skills. Consequently, companies are moving away from self-reported resumes. Instead, they increasingly use technical tests and real-world project evaluations to verify depth in problem-solving.

Abhimanyu Saxena, Co-Founder of Scaler, noted that this gap threatens both individual career paths and India’s position as a global technology hub. He stated that companies now require engineers with practical, project-based skills to drive corporate goals.

Prabhu Ram, Vice President of the Industry Research Group at CyberMedia Research, described the situation as a paradox of "signal versus substance." He observed that the divergence in data is distorting hiring signals and forcing employers to tighten their evaluation frameworks.

Shifting toward application-driven learning

The findings suggest a need to reset how the industry approaches skilling. Moving beyond tool adoption requires structured learning environments that focus on building actual systems. This approach matches recent government priorities, such as the Union Budget’s emphasis on industry-aligned training and human capital.

Closing the capability gap will likely require closer cooperation between the government, academia, and private industry. Industry leaders argue that providing accessible, hands-on learning pathways is the only way to ensure the workforce remains relevant as AI continues to change the engineering field.