AI IS FLOODING GRADUATE RECRUITMENT — CAREER RABBIT SAYS HUMAN JUDGEMENT IS BECOMING MORE VALUABLE

THE AI INTERVIEW PARADOX: BETTER PREPARATION IS MAKING GRADUATE CANDIDATES SOUND MORE ALIKE

As artificial intelligence becomes embedded on both sides of graduate recruitment, London-based Career Rabbit is pursuing a hybrid model: using AI to dramatically increase interview practice while reserving its network of more than 300 industry professionals for the commercial reasoning, technical depth and genuine experience that automated systems can struggle to judge.

Artificial intelligence is rapidly changing graduate recruitment, but its growing use by both employers and applicants is creating a new challenge: if everyone has access to the same technology, how does a candidate still stand out?

Employers increasingly use automated systems to screen CVs, administer psychometric assessments and evaluate recorded video interviews. Candidates are responding with generative AI to research companies, shape applications and rehearse interview answers.

The shift is already evident among graduates. Bright Network’s 2025 research, based on more than 14,000 students and graduates, found that more than half had used generative AI to support job applications, up from 38% in 2024.

Greater access to technology, however, does not necessarily produce stronger or more distinctive candidates.

Career Rabbit (职兔), a London-headquartered global career coaching company, is attempting to address that problem by combining AI-powered interview practice with human coaching from professionals working across some of the world’s most competitive industries.

“AI can make interview practice more accessible and repeatable, but it cannot make every answer commercially convincing,” said Emma Han, Head of Learning and Development at Career Rabbit.

“Our principle is that technology should improve the quantity and consistency of practice, while experienced mentors remain responsible for context, judgement and industry relevance.”

AI Takes On Repetition, Mentors Take On Judgement

Career Rabbit supports international students and early-career professionals applying for roles across the UK, Hong Kong, the United States, mainland China, Singapore and other international markets, with services available in English, Mandarin and Cantonese.

Its offering spans career positioning, application strategy, CV development, online assessment preparation, AI-powered mock interviews, assessment centre coaching and final-round interview support.

Rather than positioning its AI platform as a substitute for a career adviser, Career Rabbit uses the technology to move repetitive interview rehearsal outside one-to-one mentoring sessions.

Candidates can practise questions under timed conditions, record answers, review their delivery and repeat the process before meeting a mentor.

That can expose recurring problems such as poor structure, excessive speaking time, repetition and failure to provide measurable outcomes.

The human session can then concentrate on more difficult questions: Does the example genuinely demonstrate the competency being assessed? Is the experience authentic? Does the candidate understand the commercial context? Can the answer withstand detailed follow-up questioning?

The Risk Of The AI-Polished Candidate

The distinction is becoming more significant as generative AI makes professionally worded answers available almost instantly.

A candidate can ask an AI system to produce a polished response to “Why investment banking?” within seconds. But fluency does not necessarily demonstrate genuine motivation, relevant experience or an understanding of the industry.

As more applicants use similar technology, Career Rabbit argues that formulaic preparation could actually make candidates increasingly difficult to distinguish.

“Students sometimes arrive with answers that sound impressive on paper but could have been delivered by almost anyone,” Han said.

“Our mentors ask what actually happened, what decision the student made, what changed because of it and what the candidate learned. AI can help organise the material, but it should not invent the substance.”

A weak interview answer may therefore be more than a presentation problem. It can expose an unsuitable example, inadequate understanding of the role or insufficient technical and commercial preparation.

From Chemistry To Investment Banking

One case handled by Career Rabbit illustrates the distinction.

An Oxbridge chemistry graduate, whose precise university has been withheld at his request, wanted to enter UK investment banking despite having no formal finance background.

Career Rabbit assigned mentors from the investment banking area he was targeting and assessed the gap between his scientific experience and the requirements of the role.

His CV was rebuilt to present the analytical and quantitative evidence from his chemistry degree in terms an investment banking recruiter could evaluate, rather than leaving his experience framed primarily as an academic science profile.

Preparation then proceeded on two tracks: repeated behavioural interview practice alongside systematic work covering accounting fundamentals, valuation methods and deal mechanics.

The student subsequently secured a summer internship with a leading “Bulge Bracket” investment bank.

Career Rabbit continued supporting him during the internship, focusing on workplace performance and preparation for a potential full-time return offer.

The case demonstrates why simply providing candidates with more interview questions may not be sufficient. The student needed to translate an academic background into credible commercial evidence while acquiring technical knowledge specific to the industry he wanted to enter.

Different Industries Demand Different Answers

Career Rabbit’s network comprises more than 300 professionals and industry specialists spanning investment banking, quantitative finance, consulting, technology, private equity, risk and asset management.

Candidates are matched with mentors from their target area because the definition of a strong interview performance changes significantly between industries.

Investment banking candidates may be questioned on accounting, valuation, transactions, markets and their motivation for joining a particular product or sector team.

Quantitative trading candidates can encounter probability, statistics, mental mathematics, coding and market-making scenarios.

Consulting applicants may need to tackle case interviews, market sizing, written exercises and group discussions, while technology candidates can be expected to explain projects, product thinking, coding approaches and system decisions.

AI can reproduce pressure, timing and repetition across these scenarios. Determining whether the reasoning itself is sufficiently accurate, sophisticated and commercially credible remains a more complex proposition.

“A strong interview answer is not simply grammatically correct,” Han said. “It must answer the exact question, reflect the standards of the industry and withstand follow-up questions.”

International Candidates Face An Additional Layer Of Complexity

Career Rabbit’s approach is primarily designed for international students and early-career professionals requiring structured assistance across several stages of recruitment.

That can include candidates simultaneously applying in several countries, targeting highly competitive areas such as investment banking, quantitative finance and consulting, transitioning from STEM subjects into commercial careers, or navigating online tests, recorded interviews and assessment centres.

Its model is therefore less focused on candidates seeking only a one-off CV review or fully automated self-service interview product.

Instead, technology provides repeated practice, industry mentors challenge the substance and technical accuracy of answers, and career consultants connect individual interview performance to the candidate’s wider application strategy.

Career Rabbit reports a 94.5% full-time offer success rate among students who completed its coaching programme during the 2025–2026 application cycle. The company attributes that figure to the broader programme of positioning, applications, assessments, interview preparation and mentoring rather than to its AI platform alone.

AI May Make Human Expertise More Valuable

The emergence of generative AI presents an unusual paradox for the recruitment industry.

Technology can dramatically increase candidates’ access to information and practice. But as AI-generated applications and interview responses become commonplace, employers may place greater value on evidence that cannot easily be generated by a prompt: genuine experience, technical understanding, commercial judgement and the ability to defend an answer when challenged.

For Career Rabbit, that means the future of interview coaching is neither entirely automated nor entirely traditional.

“AI will continue to change how employers recruit and how students prepare,” Han said. “The question is whether candidates use it to become more thoughtful and better prepared, or simply to produce more generic content.”

For further information visit: https://www.careerrabbit.co.uk/