Using AI in applications and interviews

Are you using AI in applications and interviews? Generative AI has changed how people search for jobs, craft resumes, and prepare for interviews. That isn’t inherently bad. In fact, when used well, AI can improve clarity, reduce anxiety, and level the playing field for candidates who aren’t native speakers or who struggle with written expression.

But used badly, AI in interviews to generate answers or to fabricate achievements, can also erode trust and trigger fairness and compliance risks for employers. So how do we balance this?

AI can sharpen your prep but not replace you

“It’s interesting to read online and in forums like Reddit on the increasing use of AI in video interviews from job seekers. Some candidates experiment with live AI prompts and eye contact tech to seem engaged. It raises questions about ethics, authenticity, and how AI should, or shouldn’t, shape candidate evaluation.” Jamey-Lynn Lowe, Talent Acquisition Lead, Salt

Why subjective “AI Detection” fails

Recent data from Adzuna shows that 65 % of job seekers in the UK and US are already using AI as part of their job search. That means AI is now part of the job market, both in the tools employers use and in how candidates like you prepare.

Online interviews can be unpredictable, and certain cues are unstable or misinterpreted, which can create unfair disadvantages. Laws exist to protect candidates: in the U.S., the EEOC enforces rules banning discrimination based on race, sex, age, disability, and other protected traits (eeoc.gov). AI can speed up hiring, but it can also unintentionally introduce bias. For example, underestimating candidates with certain disabilities or misreading facial cues across skin tones.

Similar protections exist around the world, so the takeaway is clear: your skills, reasoning, and voice are what truly matter. Employers are responsible for using AI transparently and ensuring human-led decisions. Companies like Mastercard for example have published candidate AI guidelines to clarify what’s acceptable in applications and interviews, helping you navigate these tools responsibly.

The line: where AI stops being helpful

When we think about AI in the context of being a jobseeker, think of AI as a pre‑work amplifier, not a live proxy. Interviewing is less about encyclopedic knowledge and more about how you think, explain tradeoffs, handle ambiguity, and collaborate. Human skills AI can’t demonstrate on your behalf.

Helpful uses for AI in job seeking

Brainstorming interview questions: From the job description, practicing answers, clarifying technical concepts, and improving grammar/structure in application materials. So long as content reflects your experience.

Researching a company and industry trends: Paired with verification from trusted sources.

Use it to prepare: Universities and career centres recommend using AI to prepare (research, STAR practice), not to perform. Don’t memorise AI scripts; adapt in your own words.

Risky uses for AI in Job seeking

Live prompting using AI to generate answers in real time: This can undermine an employer’s ability to assess your reasoning and may violate company policies. Several major employers explicitly prohibit this. If you need prompts or assistive tools due to a disability, be transparent and request them ahead of the interview rather than surprising the interviewer. This ensures fair assessment while keeping the process compliant and respectful for everyone.

Fabrication, inflated metrics, invented roles, or copy‑pasted AI text: That misrepresents capabilities. Besides trust issues, it can lead to disqualification.

Practical guidance for jobseekers using AI: Be specific, be you

Speak in your voice, not buzzwords. If you’re applying for a new role, don’t hide behind buzzwords. AI tools can easily reword your experience in ways that sound polished but generic, stripping out your authentic voice. Use AI to clarify and highlight what you accomplished, not to obscure it.

• Pause > perfection. Ask for a moment. Think out loud. It’s respected.
• Messy > manufactured. Speak in your own words; don’t perform a script.
• Be transparent. If you used AI to prepare, fine. In the interview, be you.
• Bring notes. It’s okay to refer to a few keywords or examples you want to cover.
• Own the gaps. If you don’t know, say so—and show how you’d find out.

Also, when thinking about your LinkedIn Profile, CV, or Cover Letter, be specific. Verifiable outcomes beat impressive adjectives every time. Whether using AI to help or not. You have a tiny window to stand out.

Make sure a reader can instantly see what you did, where you had impact, and what changed because of you.

“But my work is complex – how do I show impact without fake numbers?”

Not every role maps neatly to a single KPI. When hard numbers are murky or shared, use credible proxies:

• Scale: Led a cross‑functional squad of 14 across Legal, Risk, Data.
• Reliability: Reduced decision lead time from monthly to weekly governance.
• Quality: Cut incidents from ‘frequent’ to ‘rare’ over two quarters.
• Adoption: Policy adopted by three regions; referenced in FY25 operating model.

TL;DR for candidates using AI

• Use AI to prepare, not to perform.
• Replace buzzwords with proof. If numbers are hard, use credible proxies.
• Keep resumes readable. Clean format, relevant keywords, concrete outcomes.
• In the interview, show your thinking. That’s the point.

Sources & further reading

• Policy & compliance:
  EEOC primers and technical assistance on AI and selection
  UK DSIT Responsible AI in Recruitment guide.
• Employer policies:
  SAP’s Ethical usage of GenAI in recruiting
  Mastercard’s AI Use Guidelines for Candidates.
• Practical prep:
  HBR on using GenAI for interview preparation; Harvard’s Mignone Center guidance on AI for interviews.
• Market signals:
  HR Executive on candidate AI usage and recruiter concerns.
• Buzzwords & signaling:
  Business News Daily 10 useless words to delete from your LinkedIn
• ATS reality checks:
  The Tech Resume Inside Out (ATS myths)