Artificial Intelligence (AI) is rapidly transforming the world of work—and nowhere is this shift more palpable than in the realm of talent development. As organisations strive to equip their workforce for the future, AI-led tools are being heralded as game-changers. But while the promise of AI is tantalising, the critical question remains: how do you measure its return on investment (ROI)?

To unpack this complex equation, People Matters sat down with Sandeep Kohli, Talent Leader at EY Global Delivery Services (EY GDS). With a workforce exceeding 75,000 and a global delivery footprint, EY GDS is a testing ground for advanced, scalable talent solutions. In this exclusive interview, Sandeep shares how EY GDS is implementing AI in its talent strategy, the methodologies used to measure ROI, the importance of ethical AI, and where the next wave of AI-driven impact in talent development is expected.

"At EY GDS, we are committed to leveraging AI-driven solutions to enhance talent development, improve employee experience, and boost workforce efficiency," begins Sandeep.

For EY GDS, ROI isn't just a financial metric—it’s about value creation across multiple dimensions. One of the cornerstone tools they use is a skills intelligence platform. By analysing the skillsets of over 75,000 employees, the platform enables smarter decisions in project staffing, aligning the right talent with the right opportunities.

“This directly elevates the quality of our client engagements while also driving internal efficiencies,” he adds.

Beyond staffing, AI is also used in conversational coaching. Tools that simulate real-world scenarios help coach employees at scale—enhancing not only their learning journeys but also strengthening EY GDS’s Employee Value Proposition (EVP).

This multi-pronged value—spanning enhanced client outcomes, workforce agility, and improved employee satisfaction—forms the ROI matrix for AI initiatives at EY GDS.

AI vs traditional methods: A case for blended solutions

A common misconception in the talent development space is the idea that AI will completely replace traditional methods. Sandeep offers a more nuanced view: “AI-powered tools have made remarkable strides, offering experiences that are at par with traditional development methods. But they don’t surpass them in every situation,” he explains.

Over the past year, EY GDS has made significant progress with its AI-powered learning experience platform, which has been designed to upskill employees in AI and keep them relevant in the fast-evolving market landscape. This platform delivers highly contextual, personalised learning, enabling employees to engage with content that is tailored to their individual needs and career aspirations. This approach exemplifies the concept of "learning in the flow of work", taking personalised learning to an entirely new level.

However, Sandeep is quick to point out that while AI has proven transformative in several areas, there are still crucial aspects of talent development where human intervention is irreplaceable. “Leadership development, complex emotional intelligence coaching, and strategic career mentoring still require human-led interactions. These areas involve a level of empathy and nuance that AI cannot replicate,” he says.

In response to these challenges, EY GDS is taking a blended approach to talent development. The aim is to combine the scalability and efficiency of AI with the empathy and insight of human-driven methods. This balanced approach ensures that employees are equipped with the technical skills required for the future while receiving the personal mentorship and strategic guidance that traditional talent development methods offer.

Measuring ROI in a multi-variable environment

One of the biggest challenges in any AI deployment is attribution—figuring out what portion of the success (or failure) can be credited to AI, especially when numerous variables are in play.

Sandeep admits this is an ongoing journey.

“We are in the early stages of measuring ROI from AI-driven talent initiatives. One method involves comparing AI-powered project metrics with similar initiatives where AI wasn’t used. This gives us directional insights.”

EY GDS is also planning to use control group experiments—mirroring approaches commonly used in marketing and behavioural economics. These experiments will isolate variables such as market changes, employee engagement trends, or organisational restructuring to better understand the causal impact of AI on talent outcomes.

This iterative approach not only offers a more precise ROI calculation but also promotes evidence-based decision-making for future investments.

The data privacy imperative: Balancing insights with ethics

One cannot talk about AI without addressing data privacy—especially when employee data is involved. "At EY, the responsible use of AI is a fundamental pillar of our overall AI strategy,” says Sandeep emphatically.

The organisation upholds strict standards of data protection, transparency, and fairness, in line with its Global Code of Conduct. These principles are embedded into every AI initiative—from data collection to algorithmic decision-making.

EY has implemented multi-level governance protocols to ensure that privacy isn’t compromised in the quest for insights. These include:

• Clear consent mechanisms
  
  

• Data anonymisation techniques
  
  

• Audit trails for AI decisions
  
  

• AI ethics boards to review new implementations
  
  

This commitment to ethical AI use has two-fold benefits—it safeguards employee trust and ensures compliance with global data regulations such as GDPR and India’s DPDP Act.

Lessons from what didn’t work

Innovation rarely comes without friction. Sandeep is candid about the fact that not every AI initiative has been a runaway success.“Some initiatives faced challenges in user adoption and goal alignment,” he notes.

The key lessons? Involve users early, gather continuous feedback, and ensure the AI tools are not just smart—but also intuitive and relevant. This user-centric approach ensures that technology is an enabler rather than a hindrance.

Sandeep shares that post-implementation reviews now include usability testing, pulse surveys, and engagement metrics, which help refine tools continuously. “These feedback loops are vital to evolving both the tech and the talent strategy,” he says.

The future: Predictive analytics and personalised career pathing

So, where is AI in talent development heading next?

According to Sandeep, the next frontier lies in predictive analytics for strategic workforce planning.

“We’re looking at tools that not only identify current skill gaps but can also anticipate future ones—aligning training interventions accordingly.”

He envisions a future where AI tailors career pathways based on a combination of:

• Individual aspirations
  
  

• Market trends
  
  

• Business needs
  
  

• Historical performance
  
  

• Cross-industry benchmarks
  
  

This level of foresight can help create hyper-personalised career maps, enabling employees to see multiple trajectories for growth—be it vertical advancement, lateral movements, or even reskilling for a new domain.

Such a strategy ensures that organisations remain future-ready while employees feel empowered and aligned with evolving business needs.

A shift toward proactive talent strategy

EY GDS’s efforts are indicative of a larger shift within the industry—from reactive talent development to a proactive, data-driven talent strategy.

As per recent industry reports, organisations using AI-powered L&D tools have seen up to 40% faster time-to-productivity for new employees, and a 20-30% increase in training program efficiency. But the key is not just implementing AI—it’s measuring, adapting, and continuously evolving those systems.

This is where EY GDS is carving out a leadership position. With a strong foundation in skills analytics, conversational coaching, privacy-conscious design, and blended learning, the organisation is not just measuring ROI—it is redefining what ROI looks like in the age of AI.

Takeaways for HR and L&D Leaders

For HR leaders exploring or implementing AI in their talent strategies, Sandeep’s experience offers several actionable insights:

1. Define ROI beyond dollars: Consider employee experience, efficiency, and client outcomes as key ROI markers.
   
   

2. Blend AI with human touch: Use AI for scale, but keep humans in the loop for leadership and complex learning needs.
   
   

3. Use control groups: Isolate variables to accurately attribute outcomes to AI tools.
   
   

4. Prioritise ethics and trust: Build privacy and transparency into the core of your AI strategy.
   
   

5. Iterate, don’t perfect: Start small, gather feedback, and refine continuously.
   
   

6. Plan for the future: Invest in predictive analytics to align workforce skills with emerging business needs.
   
   

As AI tools continue to mature, the question for CHROs and L&D leaders is no longer whether to adopt AI—but how to do it right and prove its value. In this mission, EY GDS is leading by example—combining innovation with integrity, data with dignity, and technology with trust.