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In the latest episode of EY.AI Unplugged Season 2: AI Agents of impact, a part of the EY India Insights podcast series, Anurag Malik, Partner and Leader of People Advisory Services at EY India, talks about “Agentic AI and the future of work”, about how Agentic AI is changing HR and workforce strategies. The discussion highlights the influence of autonomous AI systems on talent identification, simplifying HR processes and supporting leaders with data-driven insights while maintaining human judgment.
Anurag further explains the EY four-persona framework for building AI skills across organizations and practical steps for HR leaders to integrate AI into daily work. With appropriate adoption, an employee can free several hours per week by using AI for routine tasks like drafting documents, summarizing meetings and analyzing data, allowing more time to focus on higher-value work.
Key takeaways:
Agentic AI can move high-potential talent decisions from intuition to structured, data-based insights.
In some cases, Agentic AI can reduce up to 70% of manual workload in HR workflows.
Data credibility and ethical use remain essential for AI-driven decisions.
Many organizations are at present following a four-persona framework for AI capability-building (Ambassador, Translator, Specialist, Aspirant).
Across the HR value chain—from hiring and onboarding to performance management, learning and exit—Agentic AI is making a strong impact. It supports tasks such as approvals, policy clarifications, scheduling, consolidating feedback and generating insights on individuals and talent from multiple sources. The adoption of Agentic AI in these areas is growing rapidly.
Anurag Malik
Partner and Leader, People Advisory Services, EY India
For your convenience, a full text transcript of this podcast is available on the link below:
Pallavi
Welcome to the EY.AI Unplugged Season 2: AI agents of impact, a special series by EY India Insights. In this episode, ‘Agentic AI and the future of work,’ we explore how autonomous AI systems are redefining roles, reshaping workplaces and empowering people to focus on higher-value human-centric tasks. As organizations experiment with Agentic AI intelligent systems — that can reason, act and collaborate — the episode discusses what this means for the workforce of tomorrow and how leaders can prepare for this transformation.
Our guest today is Anurag Malik, Partner and Leader of People Advisory Services at EY India. With over three decades of experience, Anurag has been at the forefront of helping organizations transform their people strategies, adapt to technology-driven change and build agile, future-ready workforces.
Pallavi
Thank you, Anurag, for joining us today. It is a pleasure to have you with us.
Anurag Malik
Thank you, Pallavi.
Pallavi
Anurag, to begin with, how is Agentic AI changing the way organizations identify and assess high-potential talent? Could you share examples where data or AI surfaced as unexpected leaders?
Anurag Malik
Sure, Pallavi. Agentic AI is having a significant impact on high-potential talent identification process. The high potential talent identification process is shifting from input-based process to a periodic workflow-driven decision-making model. Traditionally, high-potential decisions have come from sources like managerial judgment and performance reviews, or some organizations do point in time assessments. With AI, the lens of collecting data around high-potential talent has become much broader or is becoming much broader.
AI is helping organizations collate data from sources like projects, collaboration patterns, leadership behaviors, mobility and how individuals respond to specific stretch or specific assignments that they are put on. The source of data is not limited to people who are very visible, but individuals who are really contributing, agile, who are demonstrating the right kind of collaboration behaviors.
In EY we have a platform, an Agentic AI enabled platform called EY Competency Connect to bring behavioral, functional and technical data together to provide deeper insights, enabling organizations to take a high-potential talent decision. That is the shift happening from a point in time to something that happens continuously with the flow of work.
Pallavi
Thank you, Anurag. Adding to the previous question, as AI influences people's decisions, where should the line be drawn between the data and judgment?
Anurag Malik
AI is like the flashlight or the headlights of the car, while leaders are the steering wheel of the car. AI is helping interpret data so that leaders get insights on aspects that they might have missed: trends, blind spots, inconsistencies in data.
AI is providing insights where the perspective is to sharpen human accountability for these decisions. Now, what's certainly not happening is AI being used as a standalone. For selection, promotion, termination decisions, it is still finally a human accountability and human perspective that helps in taking these decisions.
There is a clear shift happening from what we used to call managerial judgment and leadership judgment or leadership gut feel to much more structured data inputs coming from AI that enable these decisions. We are also seeing that while the trend is very clear in terms of using Agentic AI — selection, performance and high-potential career decisions — organizations need to be careful that the underlying quality of data that enables these decision has to be credible.
Definitely, work needs to be done on ensuring validity and reliability of that data. The other aspect is the ethical use of AI, that organizations’ leaders hold themselves accountable for the way AI is being used, or data is being used to take decisions is within the boundaries of what we call ethical use of AI.
Pallavi
Thank you, Anurag. Beyond talent assessments, where is Agentic AI having the biggest operational impact in the HR?
Anurag Malik
Pallavi, it is having an impact across the HR value chain, what we call as workflow execution. If you look at the HR value chain, starting from hiring to onboarding to performance management to learning to exit, Agentic AI is having a very significant impact. Aspects like approvals, policy clarifications, scheduling, consolidating feedback, generating insights about individuals about talent from multiple sources — the usage of Agentic AI is growing by leaps and bounds. The interesting thing happening is that many processes which were dependent on multiple data sources or data lying across multiple systems or decisions which were based on inputs from multiple individuals, AI is simplifying, consolidating and providing an easier body of data that is available for decision making.
Let me give you a specific example. We are working for a very large IT services company and the process we picked up for Agentification was around internal job mobility. As we looked at the process, we realized that it is something that the organization would run every quarter and thousands of people would be eligible for job rotation or job mobility, but the amount of transactional workload that would go into consolidating data, people seeking perspective from their managers and ensuring that the right kind of business logic is applied. It was an extremely transactional exercise. With Agentic AI, we believe that we are going to take off almost 70% of the transaction workload. Just an example around the potential that Agentic AI brings to HR workflow simplification and execution.
Pallavi
Thank you, Anurag. Pivoting towards our firm's efforts, how is EY helping organizations make significant investments for building AI capability at scale?
Anurag Malik
Organizations across sectors are focusing on strengthening and improving AI fluency across levels. It is no longer limited to leadership layers; it cuts across levels. The focus on AI capability building spans across basic awareness building initiatives, deep functional or deep technical know-how around home AI capabilities, depending on roles and expected outcomes from people at different level.
In our experience, as we have engaged with organizations across sectors, there is a good and simple framework for driving AI capabilities at scale. Across sectors, there are four personas that can be used to cluster the entire organization.
Persona number one is the ambassador persona. It is the leadership layer of the organization where AI capability-building needs to be focused on building strategic AI capabilities, helping leaders understand the best practices in their sector globally for AI use cases and ensuring they become ambassadors for championing AI and AI initiatives across the organization. That is the ambassador’s persona.
The second is the translator persona, which includes individuals who are functional specialists with deep AI capabilities. They help translate functional know-how into AI-based initiatives. It cuts across finance, supply chain, operations, engineering, HR, etc.
The third persona is the AI specialist or technology and implementation specialist, focusing on current technology, IT, digital, MIS population, building deeper technical capabilities in AI.
The fourth persona is the aspirant persona, which includes everybody else in the organization. The group requires basic AI capability-building for individuals across levels and functional areas.
These are the four personas and we have repeatedly seen organizations across sectors put their employees into these four personas and assign an appropriate learning journey. At EY, we started this initiative two years back, where we created our own UI, a guide called AI Varsity. Over the last two years, we have skilled almost 45,000 people across levels in India on AI skills.
Today, we are taking some of these learnings to our clients, across sectors and locations. It is one of the largest AI capability-building initiatives that EY is running in the country.
Pallavi
Thank you, Anurag. Lastly, how can HR decision makers enable the workforce to work confidently with Agentic AI?
Anurag Malik
I have repeatedly seen that it is important for leaders to understand that for AI to make a significant bend in their everyday life, they need to make it a part of their everyday work, not a side initiative or a project. The way people get comfortable using AI is by starting to use it in their day-to-day jobs for drafting documents, responding to emails, summarizing meetings and analyzing complex Excel data sets. We have seen people using AI in day-to-day applications and within a week, people are able to release three to eight hours of their time, which is time they can effectively deploy on other tasks.
The shift is not only about learning AI, it is about learning how to work with AI and understanding that AI can potentially do 25% to 50% or even more of your everyday work. You need to treat it as a working partner, not as a project. Once you do that, you will see greater AI adoption and comfort with AI will happen naturally.
Pallavi
Thank you, Anurag, for sharing your insights on how Agentic AI is reshaping the world of work and what it means for businesses and employees.
Anurag Malik
Thank you, Pallavi. It was an insightful conversation. I hope the experiences I shared will be useful for our listeners.
Pallavi
That brings us to the end of this episode, thank you to our listeners for tuning in to EY.AI Unplugged Season 2: AI Agents of impact. Stay with us as we continue to explore how AI drives innovation, inclusion and impact across industries.
You can listen to more episodes of this series on EY.com or on your preferred podcast platform. Until next time, this is Pallavi signing off.
