Only 10% of enterprises see measurable hiring gains despite 80% adopting AI: Study

Despite widespread adoption of artificial intelligence (AI) in recruitment, only one in ten enterprise organisations have seen measurable improvements in hiring outcomes, highlighting a significant gap between technology investments and actual recruitment results, according to a study by AI-powered digital recruitment company Taggd.

The study found that nearly 80 per cent of organisations are using AI tools in at least one function, either directly or indirectly, across different stages of the recruitment process. However, only 10 per cent reported measurable improvements in hiring outcomes.

According to the study, the findings highlight a persistent disconnect between investments in human resource technology and the ability of organisations to achieve better hiring results, which remains a key challenge for enterprises.


The study was released during the launch of Taggd's new AI-native recruitment delivery model powered by its agentic AI recruitment assistant, TARA.

Taggd said the new operating model combines its AI recruitment assistant with expert recruiters, known as Forward-Deployed Recruiters, to improve recruitment efficiency, reduce hiring timelines and deliver more predictable hiring outcomes.

Kiran Kumar, President, Platform, Taggd, said AI alone is not sufficient to solve complex hiring challenges.

"Data, agents, and domain put together gives an entirely different dimension in solving complex recruitment challenges, elevating our Forward-Deployed Recruiters to direct execution at a scale that simply wasn't possible before," Kumar said.

According to Taggd, the model is designed to combine AI with human expertise instead of relying solely on automation.

The company believes this approach can help enterprises bridge the gap between AI adoption and measurable hiring performance.

Devashish Sharma, Co-Founder and CEO of Taggd, said organisations using the platform have already witnessed improvements across several recruitment metrics.

He said the model has shown improvements in hiring speed, talent fit, real-time market intelligence and stakeholder satisfaction, while continuing to meet hiring commitments.

Sharma added that "Agentic AI architecture will also allow the company to expand its recruitment process outsourcing (RPO) services to mid-sized, high-growth businesses, enabling them to access enterprise-grade hiring capabilities."

The study suggests that while AI adoption in recruitment has become widespread, enterprises may need to combine technology with domain expertise and human intervention to translate AI investments into measurable hiring outcomes.