Skills over pedigree: How AI is redefining early career hiring

AI has quietly become the third party in every early-career interview. Candidates use it to polish resumes and rehearse answers; employers use it to screen thousands of applications in minutes. The result is a paradox: hiring has never been faster, and never harder to trust.

This tension anchored the recent People Matters webinar, Early Talent, Real Skills: Hiring for an AI-Ready Workforce, held in association with Internshala. Moderated by Varun Verma, SVP and Head of B2B, Internshala, the session brought together Savita Mittra, Senior Director, Talent Acquisition, AMEA, Mondelez International; Anju Chaudhary, Chief People Officer, XOXO Day; and Anjali Sachdeva, Vice President, HR at Clove Dental, to explore how organisations can identify genuine capability when AI sits on both sides of the hiring table.

Opening the discussion, Varun pointed to research showing that 39% of early-career candidates have already used AI somewhere in their application, while only 26% trust employers to evaluate them fairly.

The biggest shift: from "what you know" to "how you apply it"

AI has changed the equation on both ends. Candidates can discover opportunities and present themselves more confidently, but for employers, the bigger shift is in how capability is assessed.

For Savita, the differentiator is application: “It's one thing to know what you know, but the bigger thing is how you demonstrate and apply that in the real world.”

That becomes particularly important for early talent, where hiring purely for today's skills can quickly become outdated. Anju also pushed back on unrealistic expectations around AI expertise: “it's not gonna happen, especially with an early career.”

The challenge, then, is to create situations where candidates have to demonstrate how they think rather than simply present a polished version of themselves. For Anju, that means asking why candidates chose a particular path, what they would do differently and how they would approach the same problem years down the line. “I'm not looking for outcomes. I'm looking for how they think and approach,” she said. 

At Mondelez India, this shift from “tell me” to “show me” takes shape through Maestros, a case-competition-style programme that tests candidates' ability to collaborate and solve problems in real time. As Savita put it, “there's no way you're changing the scenario when you're putting in a resume versus when you're demonstrating that.”

Role-plays and live case studies serve a similar purpose, allowing candidates to demonstrate how they respond to a real scenario rather than a rehearsed one.

Where automation should stop, and where it earns its keep

The discussion also turned to where AI belongs in the hiring process and where it should stop.

At scale, automation can be necessary. Anju pointed to companies such as Home Depot, where seasonal hiring volumes can be too large for talent acquisition teams to manage manually. But the efficiency gained through automation should not replace human judgment. AI can flag that “the candidate meets eight out of 10 criteria”, but it should not be the final judge of qualities such as curiosity, agility or resilience.

The same principle applies to candidate experience. Anjali recalled her daughter's first day at a large company, where she was handed a folder to fill out and told to leave once it was collected, with only an HR reference number to show for it. The experience reinforced her view that automation should supplement, rather than replace, an empathetic process.

Her team has also moved away from multi-panel interviews, where candidates could face four or five interviewers and repeat the same story. Instead, there is a single, clearly defined interview board for each role, with feedback provided to every candidate regardless of the outcome.

For Savita, the starting point is purpose: organisations need to know “what are you trying to solve for” before reaching for a tool. Even as processes move towards agentic AI, she believes later-stage rounds should remain human.

“It is clearly about not taking away the human element at all”, she said, arguing that “the augmentation to judgment must matter, and not the judgment itself.”

Candidate experience is part of the employer brand

Technology is only part of the equation. Candidates also need clarity about how the hiring process works and what to expect.

Anjali captured the risk of getting this wrong: “The candidate who's not getting a job anywhere, he will stick on, but the candidate who's good, he will say, 'this is not the right company for me.'”

For Anju, that experience becomes part of how candidates perceive the organisation, regardless of whether they are hired. “Your candidate experience is the brand, the employer brand that you get an opportunity to create,” she said. 

Her own interview with Nike, for a role she ultimately did not take, remains an example of what she called “the best experience of my life.”

Skills-first hiring vs. pedigree

Skills-first hiring is gaining attention, but degrees and pedigree still influence shortlists. Anju acknowledged that an Ivy League or IIT/IIM background can “genuinely create an attraction for the hiring manager”, even when organisations have established skills-based frameworks.

Her concern is the gap between what HR designs and what hiring managers ultimately prioritise. The answer, she argued, is to equip hiring managers to define what a role actually requires before the interview begins.

Savita offered an India-specific perspective, pointing to the country's deeply embedded exam-and-ranking culture. Her framework considers academic fundamentals alongside EQ, “RQ, which is your relationship quotient,” and “DQ or TQ, which is your digital quotient,” treating pedigree as one input among several rather than the defining one.

The conversation also challenged “culture fit” as a hiring criterion. Anjali recalled high-calibre candidates who struggled to sustain themselves after joining an organisation. Anju questioned the framing itself, arguing that culture fit can become a bias. “I'd rather look for a culture add. What does this person bring that would add value to what we already do?” she added. 

Does AI reduce bias, or create new kinds?

AI could potentially help reduce some forms of bias, but it can also introduce new ones. Anju pointed to the growing excitement around candidates who have worked with advanced AI or agent-building tools, which can overshadow other essentials such as collaboration and cultural alignment.

For Savita, reducing pedigree bias requires hiring around clearly defined roles and assessing candidates against a broader range of skills rather than credentials alone. Anjali added that strong-pedigree hires have sometimes plateaued while others surpassed them through calibre, curiosity and a willingness to learn.

Anju illustrated the broader point with the example of a friend's son who scored a perfect 1600 on the SAT but was not admitted to his first-choice college. As she put it, “You could find gems from community college as compared to an Ivy.”

Is the resume still relevant?

The resume is unlikely to disappear, but its role is changing. Anjali sees it as useful for baseline information while giving little weight to narrative sections: “That's all story. The rest is coming out during the interview.”

Candidates can also build evidence beyond the resume, through GitHub profiles, Substack, LinkedIn contributions and awards, as Anju suggested.

Ultimately, the panel's message was to broaden the definition of potential. Pedigree and polished applications will continue to have a place, but neither is a reliable proxy for capability when AI can help manufacture both.

The stronger approach is to define what a role truly requires, test for it directly and create a process that allows candidates to demonstrate how they think, adapt and contribute.

AI can widen the funnel, sharpen screening and reduce administrative work. The judgment calls that matter most in early-career hiring still belong to people.