“There is a talent war, and the key differentiator will be how prepared your systems, processes, and workflows are for the future. The companies that harness the advantage of technology will come out on top,” said Rajendra Prasad, Global Head of TA, Nium.

During his conversation with Deepa Damodaran, Editor of HR Excellence Magazines at HR.com, at FiesTA 2025, held recently in Bangalore, Karnataka, India, Rajendra delved into how AI is transforming the TA industry, what TA leaders must do to align their goals with those of the business, future trends in TA, and more.

Excerpts from the interview:

Q: How do you see AI transforming talent acquisition and how do you plan to leverage AI tools in your organization?

Rajendra: AI is an inevitability that will gradually impact multiple functions, and talent acquisition (TA) is no exception.

The disruption we're witnessing in the TA space is more significant than I initially anticipated. A year ago, I thought we were five years away from true disruption in this area. However, I now realize that change is coming much sooner. I believe the disruption will occur within the next six to twelve months.

During this period, the way we approach TA will be completely transformed. I've already come across several tools that are revolutionizing how we schedule, screen, and source candidates.

From a business perspective, several tools are enabling the first level of interview screening, both on the tech and non-tech sides. This initial screening could soon be automated. The evolution of large language model (LLM) and generative AI tools has been remarkable—they are now replicating pauses, reflexes, and even the natural flow of conversation. Unless specifically told, you wouldn’t even realize you’re interacting with an AI bot.

The advancements in AI integration, whether on the ATS or CRM side, are phenomenal. Even traditional companies like iCIMS, SuccessFactors, Workday, and Phenom are innovating to include AI components, such as talent rediscovery or candidate outreach, which will eventually be automated.

As we discussed, some early-stage TA functions like scheduling, coordination, and sourcing will all be automated. One of the goals we’ve set as a company is to save 20% of our TA bandwidth through the introduction of AI.

Q: How do you address the apprehension within your team? For instance, concerns that certain skills might become obsolete or that jobs could be replaced?

Rajendra: We are actively normalizing these concerns. There’s no need to fear for those with talent. While certain low-level functions might be impacted, as I mentioned earlier, out of every 100 people in roles like scheduling or sourcing, only around 15 might be needed to maintain that personalized touch. This is the reality of the situation. We must find opportunities for those talented individuals in other areas of talent acquisition or HR.

Whether we like it or not, this change is coming, and we have two choices: embrace it and adapt, or resist and risk becoming obsolete. It’s really that simple.

Q: What message would you give to TA managers who are struggling to align their TA goals with business goals and demonstrate the importance of the TA function to leadership?

Rajendra: There are no shortcuts to this. You need to actively partner with the business to understand their needs and be able to translate that into a compelling candidate experience. Time is a precious commodity, whether for the TA team or the business. Especially in startups, where you’re pulling core engineers away from their work to conduct interviews, you can’t afford to throw multiple candidates into the process and hope one works out.

It’s crucial to ensure that the entire process is well-balanced, with guardrails in place to make sure that the time spent is valuable. The top of the funnel needs to be distilled down to high-quality candidates.

Ultimately, the respect and the "seat at the table" we seek comes from building trust with the business and proving ourselves as true partners. Today, we have the title of HR business partner, but in talent acquisition, we don’t yet have a formalized role like Talent Acquisition Business Partner (TABP).

We don’t have that structure in place yet. While a few companies have started using the title "TA partner," these roles often function as recruiters or sourcers, or fall within other subcategories. To be recognized as a TA business partner, you need to understand the business and the reasons behind their needs, and deliver accordingly.

In this process, it’s important to make the business take ownership as well. They must be accountable for aspects like employee referrals and the quality of candidates they provide. For example, the elevator pitch for a role shouldn’t fall solely on the recruiter to create—it’s the business’s responsibility to craft that pitch and communicate it clearly so recruiters can attract the right candidates.

Another ongoing issue is that while we, as recruiters, reach out to countless candidates, these candidates are often bombarded by dozens of other recruiters from competing companies. The reality is that top candidates aren’t lacking options.

Candidates are often bombarded with numerous opportunities, making it harder for any single message to stand out. So, how do you differentiate yourself? What kind of messaging catches attention? Simply having the recruiter reach out might not be enough.

It’s crucial to leverage your business to also engage with candidates directly. A message from a startup's CTO, for instance, carries much more weight than one from a recruiter. The likelihood of a candidate responding to the CTO's message is far higher, so how can you maximize this dynamic and work alongside the business to make a greater impact?

Q: How should hiring metrics evolve, and what’s the best way to calculate the ROI of recruiting efforts?

Rajendra: Looking at metrics, we’ve been seeing the same ones for the last 20 years, like time to hire or interview funnel metrics. It’s time to rethink how we use these numbers to better align with the evolving landscape of recruitment.

These are standard metrics many organizations track, like cost per hire or source mix. However, we need to evolve beyond just the numbers. The quantity game alone doesn’t matter. As a recruiter, if you’re presenting a candidate as the best fit given the resources and talent pool available, it should translate into how that person grows within the company over the next two to three years.

If that individual leaves within six months due to early attrition, it suggests that while you may have hired well initially, the organization may not have the right environment or culture to retain such talent.

The true measure of quality hire comes from tracking how an individual performs and grows over a longer period. That’s the key metric—how someone hired today develops over two to three years. I believe this should be a primary KPI, and systems should evolve to track it.

Now, in terms of AI and typical recruiting technologies, how well do they address these factors?

Q: With growing concerns around ethics and bias in AI, what steps should AI-powered recruiting tech providers take to ensure recruiters can use these tools responsibly?

Rajendra: AI tools are only as good as the data you feed into them. If the data set is biased—say, for instance, if a company is primarily sourcing candidates from top-tier institutions like IITs and NITs—then the ATS will also reflect that bias. The key is how you're training the ATS and what data you're providing.

It's crucial to implement checks and balances to avoid these biases. Tools like EightFold.AI and TidyHire, for example, offer bias checkpoints that allow you to filter and unfilter certain parameters. This helps ensure that you're addressing and mitigating biases in your recruitment process. Some systems have evolved so much that the bias factor is gradually being reduced.

The ethical concerns around AI, particularly bias, stem from the flawed data sets that some early-stage AI tools in talent acquisition were built on. These systems failed because they were operating with data that was inherently biased. However, AI is an evolving field. The more data you input and the more corrective measures and checkpoints you implement, the better the system becomes over time. It’s a continuous learning process that improves as you address these issues.

Q: Skills over degree, What’s your take on this trend in the Indian market, and how do you see it evolving in a market like India?

Rajendra: I’ve seen cases where people with 18 backlogs in their engineering degrees were hired because they brought the right level of rigor and determination to the table. But, of course, these instances are few and far between.

Take campus recruitment programs, for example. Companies rush to IITs and NITs, fighting for the prime day-one slots to find those top-tier candidates with high CGPAs and GPAs. And to some extent, this has been successful. But are those the only places to find great talent? Definitely not. You can find the “needle in the haystack” elsewhere too.

This is where tools can make a real difference. For example, I might hesitate to recruit from a tier-three city college, even though the best candidate could stand out there just as much as an IIT grad. Due to time and bandwidth constraints, we may miss out on these opportunities. But now, these candidates have a chance. They can excel on platforms like LeatCode, HackerRank, and HackerEarth, showcasing their skills through coding contests. Additionally, their contributions on GitHub can help them stand out. These tools provide a level playing field, opening up opportunities for talented individuals regardless of where they studied.

I’m not in favor of equating pure academics with pure talent. I’ve seen exceptional talent in places where you wouldn’t expect to find it—and we’ve hired those individuals. But these are often non-traditional companies, like EA Games and other gaming firms, that hire based on passion and skill rather than academic pedigree.

I do believe the industry needs to evolve. Larger companies might have the resources to focus on day-one recruitment at top-tier institutes, but we need to widen the scope and recognize talent from all corners, not just those with impressive academic records.

For startups, it’s a different challenge. They might not even secure a slot on day five of recruitment, so they need to look beyond the traditional talent pools to find the right fit. The unique value of the startup—its core work—should be what attracts talent. That’s where I believe the industry should shift its focus moving forward.

Q: What are your top trends for the TA industry in 2025?

Rajendra: This market is still in a "wait-and-watch" phase. Many venture capital firms haven’t yet opened their wallets, and even large tech companies like Microsoft have announced layoffs as recently as January 2025. So, the landscape is still evolving.

They're hiring on one hand, but also laying off on the other. The wave of layoffs that began in 2023 and continued into 2024 will likely extend into part of 2025. However, once the US market stabilizes and VC firms begin reinvesting, with interest rates dropping, the market will eventually rebound. When that happens, the talent acquisition function needs to be prepared.

We've all seen the mad rush of hiring that happened post-COVID. Companies threw money, headcount, and built large TA teams to address the issue. That rush will come again, though perhaps not immediately. But this time, AI will be a major player. Companies that have invested in AI and embraced it will be the ones to succeed. This is a talent war, and the key differentiator will be how prepared your systems, processes, and workflows are for the future. The companies that harness the advantage of technology will come out on top.

 
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