Unstop’s Ankit Aggarwal on Barclays Job Cuts and Future of Hiring
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Ankit Aggarwal is the Founder and CEO of Unstop, India’s largest early talent community engagement and hiring platform, connecting 32 million+ students with 35,000+ employers. Driven by a vision to democratise opportunities for India’s youth, he has built a skill-first ecosystem that helps organisations discover, assess, engage and hire emerging talent through AI-powered hiring automation.
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Ankit holds a B.Tech in Computer Science, an MBA in Marketing and Strategy from IMT Ghaziabad, and a General Management credential from Harvard Business School. Previously, he worked with Sapient, Deloitte and Teach For India.
Under his leadership, Unstop has powered leading initiatives, including Flipkart GRiD, Adobe India Hackathon and HUL L.I.M.E., helping over one million students secure internships and full-time roles
Q-What Does Barclays’ Planned Job Cuts Tell Us About the Future of Hiring and the Skills Employers Will Need?
The biggest disruption AI is bringing to recruitment may not be the automation of hiring itself. It may be the fact that employers are increasingly uncertain about which skills will remain valuable, which tasks will be automated and how to distinguish genuine capability from work produced with the assistance of technology.
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Reports of Barclays planning approximately 5,000 job cuts have brought the conversation around technology-led efficiency and workforce restructuring into focus. However, the implications extend beyond one bank or one restructuring exercise. Across industries, companies are examining how technology can change the economics of work, while recruiters face a more fundamental challenge: hiring people for roles whose responsibilities may look considerably different within the next few years.
This creates a new hiring equation. Organisations must reconsider not only how many people they need, but also what they need those people to be capable of doing. At the same time, AI tools are changing how candidates prepare applications, complete assignments and present their abilities. The result is a recruitment environment in which both the job description and the evidence used to evaluate applicants are becoming less reliable as fixed reference points.
Q- As Barclays and other companies pursue technology-led efficiencies, how might employers rethink the skills and roles they recruit for?
When organisations introduce AI to improve productivity, the immediate conversation often centres on efficiency, operating costs and workforce requirements. Yet reducing the number of people required for a particular task is only one possible consequence of automation. Another is that the nature of the remaining work changes.
Consider an analyst whose responsibilities previously involved collecting information, preparing reports and identifying patterns. AI can now assist with several of these activities. The analyst’s value may increasingly depend on interpreting findings, questioning assumptions, identifying errors and translating information into business decisions.
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Similar changes are emerging across software development, customer service, marketing and financial services. As technology takes on more routine activities, employers may place greater importance on judgement, adaptability, domain understanding and the ability to work effectively with AI.
This requires companies to rethink job descriptions before redesigning recruitment processes. Hiring for a role based entirely on yesterday’s responsibilities risks producing a workforce that is well prepared for tasks technology is already changing.
The more relevant question is no longer simply whether a candidate possesses a particular skill. It is whether they can apply that skill in a workplace where the tools, expectations and problems continue to evolve.
Q- Can recruiters reliably assess a candidate’s abilities when AI can help produce polished applications and assessment responses?
There is a second disruption that employers cannot ignore. The same technology helping organisations automate work is also helping candidates navigate recruitment.
AI tools can draft polished résumés, tailor cover letters to job descriptions, prepare interview responses and assist with technical assignments. Candidates can use them to communicate their experiences more effectively, but the technology also makes it harder for recruiters to determine how much of an application reflects independent capability.
A well-written response is no longer necessarily evidence of strong communication skills. A technically correct assignment may not reveal whether the candidate understands the solution. Even a carefully structured answer to a behavioural question can be generated without the underlying experience or judgement that the question is intended to assess.
This creates an arms race. Employers introduce more sophisticated screening tools, while candidates gain access to increasingly capable systems that help them perform well against those screens.
The answer cannot simply be more automation on the recruitment side. If companies respond by introducing additional AI filters without reconsidering what they measure, they risk creating a process in which machines evaluate material substantially produced by other machines.
Recruiters therefore need to distinguish between the ability to produce an impressive output and the ability to understand, defend and apply it.
Q- Are practical challenges, simulations and real-time problem-solving becoming more important in identifying job-ready talent?
Practical challenges, simulations and real-time problem-solving exercises offer one way to address this problem. They can provide employers with a more direct view of how candidates approach unfamiliar situations, make decisions and respond when their initial assumptions are challenged.
For example, an aspiring software engineer could be asked to review AI-generated code, identify vulnerabilities and explain the changes required. A marketing candidate could evaluate an AI-generated campaign proposal and identify where the strategy fails to address the target audience. An analyst could be asked to challenge an automated recommendation using incomplete or contradictory data.
These exercises test something beyond the ability to generate an answer. They examine whether a candidate understands the work well enough to question, improve and take responsibility for the result.
This does not mean AI assistance should always be prohibited during assessments. In roles where employees will routinely use AI tools, the ability to work with those tools effectively may itself be an important professional capability.
The distinction is between testing unaided foundational knowledge and testing the ability to deliver reliable outcomes with technology. Employers need to be clear about which capability they are evaluating and design their assessments accordingly.
Q- How can young professionals demonstrate genuine skills when both the work and the process of getting hired are being reshaped by AI?
For fresh graduates, the implications are particularly significant. Entry-level roles have traditionally provided opportunities to learn through routine tasks, observation and gradual responsibility. As some of those tasks become automated, employers may need to rethink how new employees develop practical experience.
At the same time, students entering the workforce have access to tools that previous generations did not. AI can support learning, coding, research and experimentation, enabling young professionals to attempt projects that might previously have required more extensive technical resources.
However, access to these tools does not automatically translate into professional competence. A student who can generate a working application must still understand its limitations. Someone who uses AI to analyse data must recognise when the findings are misleading. A candidate who produces a polished presentation must be able to defend the reasoning behind it.
This is where competitions, hackathons, real-world projects and structured assessments can become more relevant to early-career hiring.
At Unstop, we aim to make early-career hiring more skills-focused by giving students opportunities to demonstrate their abilities through challenges, assessments and employer-led programmes, rather than relying solely on resumes and academic credentials. The platform brings together talent sourcing, screening, AI-supported assessments, interview workflows and recruitment automation, helping employers identify candidates based on their demonstrated skills and potential.
The larger opportunity is to help employers evaluate talent more consistently across large and diverse candidate pools, while enabling students to showcase their capabilities and access opportunities that might otherwise be difficult to find through conventional hiring processes.
The next phase of AI-led recruitment should not be defined solely by faster shortlisting, lower hiring costs or greater automation. These improvements matter, but they do not answer the fundamental question of whether organisations are identifying people who can succeed as work changes.
For employers, that means defining job readiness around three connected capabilities: sound foundational knowledge, the ability to apply judgement to unfamiliar problems and the capacity to learn alongside evolving technology.
For candidates, it means moving beyond collecting credentials or producing polished applications. They need opportunities to demonstrate how they think, what they can build, how they use AI responsibly and whether they understand the outcomes they produce.
My conviction is that AI should help recruitment move from filtering people based on familiar signals towards identifying capability through meaningful evidence. Technology should make it possible to recognise potential across a wider talent pool, while human judgement remains responsible for interpreting that evidence and making consequential decisions.
The question raised by workforce restructuring is therefore not just whether AI will eliminate certain jobs. It is also about whether organisations are preparing their employees with the skills and capabilities that will be needed in the future.
Thank you, Ankit!