AI Transforms Talent Identification: A New HR Era

Published Date : 01/11/2025 

The landscape of talent identification is undergoing a seismic shift, thanks to artificial intelligence. HR heads across industries are leveraging AI to spot high-potential (HiPo) employees, transforming the way future leaders are identified and nurtured. 

When Zensar ran its in-house artificial intelligence (AI) hackathon, ZenseAI SPARK, it sparked more than just proofs of concept that even had the HR head chomping at his bit.

This platform not only encouraged creative problem-solving but also provided a valuable opportunity to recognise and nurture high-potential (HiPo), future-ready talent within our workforce, said Vivek Ranjan, chief human resources officer (CHRO), Zensar. This is a clear sign that moments meant for CTOs and COOs have become testbeds for HR.

The shift is not confined to a company or sector. HR heads across industries are spotting HiPo employees through an AI-informed lens. They say that while the HiPo playbook is being rewritten, the pen is still firmly held by people who know how to read the handwriting. However, as AI approaches critical mass, that may no longer be the case.

The new markers are less about tenure or managerial aspiration and more about learning velocity, AI-collaboration fluency, and the ability to reimagine work with technology. Yet, the decision to promote remains human-centred.

At Innovaccer, a digital healthcare company, the language is blunt and operational. Earlier, the classic view was to look for strong performers with conventional leadership traits. Now, that view has become toast. The new HiPos aren't just high performers anymore - they're as fluid as water, said Satyajit Menon, global head of people experience. He described HiPo identification today as a human-machine partnership.

He added that AI can scan performance data, skills, and growth trajectories at a scale humans simply can't, it even helps us spot people who might grow into future leadership roles before they've even raised their hands. The company's models are about 15-20% more accurate in predicting retention of high-potential talent on cross-functional AI projects. The firm also reported that immersive, AI-driven flight simulators have helped cut time-to-competency for key roles by nearly 40%.

Preeti Kannan, CHRO, IIFL Finance, echoed the shift in the identification process as one that is Human+AI, where technology can validate what managers observe, reduce bias, and even surface hidden HiPos who might not fit the traditional mould, while flagging early, measurable outcomes.

It's about mindset, ownership, and the courage to shape the future with technology, she said, adding that more than 60% of business functions are already using AI-led tools and that HR's use of AI for talent analytics, personalised learning, and an AI-led helpdesk has improved response efficiency by over 25%.

Consulting firms see the same trend across their client base. Competencies like AI-fluency, Human-AI orchestration will become core Hi-Po traits, said Anurag Malik, partner, people consulting, EY India, who points to platforms such as Competency Connect that fuse technical, functional, and behavioural assessments into continuous, AI-augmented personalised development plans. Malik argues that HiPo identification is moving from the end-of-the-year talent reviews/heavy assessments to in-the-flow-of-work assessments.

As more companies adopt and train their HiPo data, he expects the share of human judgment will reduce dramatically in the identification and even the succession planning process. However, he cautioned, As AI tools become stronger, organisations also need to ensure the quality of the underlying workforce data is robust for AI to enable reliable decision-making.

Legacy employers and startups alike are adjusting the old frames rather than discarding them. K A Narayan, president-HR, Raymond Group, said the changes the group is prioritising include AI literacy, navigating complexity and ambiguity, analytical skills, and futuristic business modelling. Raymond plans to give equal weightage to KPIs and leadership competencies and to future-oriented AI skills for the next year, with a pivot toward AI competencies thereafter.

We are now exploring the use of GenAI to support HiPo identification by analysing learning agility, innovation patterns, and adaptability to AI-driven workflows alongside managerial judgment. Our framework balances 75% traditional performance with 25% future readiness, including AI collaboration, data fluency, and experimentation, said Archana Krishna, CHRO, Simplilearn.

At Ericsson, emphasis is on amplification, not automation. It (GenAI) hasn't changed what great leadership stands for - empathy, inclusion, and collaboration remain central - but it has broadened what we value as potential, said Priyanka Anand, head HR, Southeast Asia, Oceania and India, adding platforms such as Degreed and Career Hub allow employees to build future-focused skills, showcase their progress, and take ownership of their growth.

Still, Anand emphasised that the final call always rests with people - our technology enhances decision-making; it doesn't replace it. 

Frequently Asked Questions (FAQS): 

Q: What is the primary role of AI in talent identification?

A: AI helps in scanning performance data, skills, and growth trajectories at a scale that humans cannot, helping to identify high-potential employees more accurately and efficiently.

Q: How does AI contribute to reducing bias in talent identification?

A: AI can validate what managers observe, reduce bias, and even surface hidden high-potential employees who might not fit the traditional mould.

Q: What are the new markers for identifying high-potential employees?

A: The new markers include learning velocity, AI-collaboration fluency, and the ability to reimagine work with technology.

Q: How does AI impact the decision-making process in talent identification?

A: AI enhances decision-making by providing data-driven insights, but the final call still rests with human judgment.

Q: What are some examples of companies using AI for talent identification?

A: Companies like Zensar, Innovaccer, IIFL Finance, and Ericsson are using AI to identify and nurture high-potential employees. 

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