When AI Resumes Turn Into Spam: The Hidden Cost of “Spray and Pray” Job Apps

According to BBC News, a surge of AI‑generated cover letters and CVs is letting candidates launch hundreds of applications a day – a practice insiders call “spray and pray”. The trend is reshaping the graduate job market, raising questions about fairness, authenticity and the real value of the hires that result.

The Rise of AI‑Assisted Applications – data and context

The Institute of Student Employers (ISE) surveyed 155 of the UK’s biggest graduate recruiters. It found that 92% of employers have seen or suspected AI misuse in hiring, up from 85% a year earlier. The most tolerated AI uses are drafting cover letters and CVs, followed by answering online application questions. Only 16% of surveyed firms are already using AI to screen candidates, but 29% plan to introduce it within the next year.

Graduate roles now attract an average of 141 applications each, and EDF’s latest graduate scheme received 12,000 applications – a 10% rise on the previous year. While the market has steadied after a sharp drop, competition remains fierce, prompting many applicants to lean on AI to keep pace.

How “spray and pray” works and why it feels tempting

AI tools can rewrite a résumé in seconds, insert buzz‑words that trigger keyword filters, and even generate plausible answers for online assessments. For a job‑seeker juggling ten to twenty openings daily, the time saved is measurable. Tom, a 22‑year‑old geography graduate, says he would not have survived the process without AI help, despite never using it in live interviews.

The workflow typically looks like this:

1. Upload a basic CV to a generative‑AI platform.
2. Prompt the tool to tailor the document for each role – swapping out industry jargon, adding specific achievements, and matching the job description’s language.
3. Copy‑paste the output into the employer’s portal and hit submit.

Because many applicant‑tracking systems (ATS) rely on keyword matches, a AI‑tuned résumé often slides past the first screening stage. The result is a flood of applications that look polished on paper but may hide gaps in actual competence.

The trade‑off: speed versus authenticity

The hidden cost of “spray and pray” is a dilution of signal. Recruiters receive more applications, but the data points that help distinguish genuine fit – personal anecdotes, nuanced motivations, and consistent storytelling – become harder to spot. In practice this usually means hiring managers spend more time on later‑stage assessments, such as behavioural tests or video interviews, to verify the candidate’s true capabilities.

For candidates, the shortcut can backfire. AI‑generated answers can sound rehearsed; interviewers have reported pauses while applicants wait for a script to load, or identical phrasing across multiple videos. When the interview reaches a spontaneous Q&A, the mismatch between a polished résumé and a stilted conversation can expose the reliance on AI, damaging credibility.

Employers also face a fairness dilemma. Those who refuse AI assistance may be out‑scored by peers who flood the system with perfectly keyword‑optimised documents. The playing field becomes uneven, and the risk of hiring under‑qualified staff rises – a concern EDF’s Hollie Moody describes as “risking hiring incapable staff”.

What employers are doing – policies and tech tweaks

Many firms are drawing a line at the assessment stage. EDF now reads CVs only in later rounds and leans on skills‑based online tests and video interviews that probe problem‑solving and cultural fit. The company also publishes guidance on acceptable AI use, urging candidates to treat AI as a drafting aid rather than a cheat sheet.

Some recruiters are adopting “AI‑proof” tools that randomise interview questions or embed live‑coding challenges that cannot be pre‑generated. Others are training hiring managers to spot tell‑tale signs of AI‑generated text, such as overly generic phrasing or lack of personal detail.

Below is a quick comparison of the most common AI uses and employer attitudes:

What to watch next – signals of a shift

Two trends will shape the next twelve months. First, more recruiters are expected to embed AI on their side of the table. The ISE data shows 29% of firms plan to introduce AI tools for screening, meaning candidates will face machine‑driven filters that are tuned to detect AI‑style language. Second, professional bodies may issue formal guidelines on AI ethics in recruitment, similar to the guidance already circulating in the UK’s graduate sector.

Job‑seekers should monitor employer communications for any updates to AI policies and be ready to adapt their application strategy accordingly. Candidates who can demonstrate authentic, self‑generated content alongside AI‑enhanced documents will likely stand out when the process reaches the human‑centric stages.

Practical steps for today’s applicants

1. Use AI as a first draft, not a final product. Write a short personal summary yourself, then ask the tool to polish grammar and formatting.
2. Customize each application. Replace generic buzz‑words with specific examples from your own experience – even if the AI suggests a phrase, verify it reflects a real event.
3. Practice unscripted interview answers. Record yourself answering typical questions without assistance; this builds confidence for the live video stage where AI can’t help.
4. Read employer AI guidelines. If a company publishes a stance on AI use, follow it closely to avoid disqualification.
5. Highlight your process. In a cover letter, briefly note that you used AI for formatting but authored the core content. Transparency can turn a potential red flag into a trust‑builder.

By treating AI as a helper rather than a crutch, candidates keep the speed advantage while preserving the personal voice that recruiters ultimately need to see.

Sources

• BBC News – ‘I applied for 200 jobs’ – How ‘spray and pray’ AI job applications can backfire