More candidates than ever are using AI to create flawless applications. Polished wording, optimized for recruiters—yet something feels off.
You open your inbox and scan through applications for an urgent role. Within minutes, you notice a trend: flawlessly formatted resumes with perfectly worded cover letters.
Impressive? Maybe. But something doesn’t sit right. The job descriptions feel vague, and the accomplishments sound too polished to be real.
This isn’t a coincidence.
These applications all read as though they were written by the same person—or by the same algorithm.
And the trend is growing. According to a survey by ResumeBuilder, younger job seekers are leading the way, with individuals aged 18–34 being more likely to use AI tools. A separate survey reported by Forbes found that 46% of job seekers are leveraging generative AI for resume and cover letter improvement. While this means applications look better than ever, it doesn’t necessarily mean the candidates behind them are better suited for the job.
Applicants today know exactly what hiring managers look for—and AI makes it effortless to craft an application. Candidates commonly use AI to:
For those of you working in municipalities and large organizations, this challenge is even greater. High application volumes, strict hiring regulations, and the need for standardized evaluations make it critical to assess candidates beyond their AI-enhanced documents. Recruitment teams now spend more time filtering applications—a time-consuming process that doesn’t necessarily improve hiring accuracy.
Many hiring teams have started adapting their recruitment strategies to detect AI-generated applications. However, most of these methods aren’t working as intended.
One of the most common tactics is looking for overly polished writing and excessive keyword optimization as signs of AI involvement. At first glance, this makes sense. But the problem is that some strong candidates are also great writers.
Penalizing well-written applications risks rejecting talent. Instead of filtering out AI-generated resumes, this approach risks eliminating candidates who might be the best fit.
To automate detection, some companies have turned to AI-detection tools like GPTZero or Originality.AI, which analyze sentence structures and repetition to flag potential AI-generated content.
But these tools have limitations:
False positives: Well-written, human-created applications are flagged as AI-generated. False negatives: AI-assisted resumes that have been modified pass through undetected.
This forces hiring teams to verify flagged resumes, creating more work rather than streamlining the process.
Another approach involves embedding custom prompts in job applications, requiring candidates to provide job-specific responses. And while this does filter out low-effort AI applications, it doesn’t solve the problem. Candidates can still use AI to refine their responses before submission, making it difficult to distinguish between genuine answers and AI-enhanced ones.
With no foolproof AI-detection method, many recruiters rely on manual screening.
The issue? It’s time-consuming. Hiring teams already deal with high application volumes, and manually reviewing resumes for signs of AI usage only adds to their workload
Why These Methods Aren’t Enough
Despite these efforts, AI-generated applications are slipping through hiring pipelines.
So what’s the solution? Hiring teams need a way to assess real skills, communication, and potential beyond what’s written on a CV.
More and more forward-thinking recruitment teams are shifting focus from resumes to pre-recorded video interviews. By asking candidates to demonstrate their skills and communication abilities through video, hiring managers gain a more authentic picture of who the person is.
For municipalities and large organizations that must ensure fairness, compliance, and hiring transparency, video interviews also provide a structured evaluation process—eliminating bias while ensuring equal opportunity.
See how video interviews can transform your hiring process. Book a Demo today!
Instead of relying on traditional CV screening, these companies have adopted video interviews to identify top talent more effectively.
Want to see how video interviews can help your team identify top candidates faster? Explore our customer success stories.
AI-generated applications aren’t going away—but that doesn’t mean hiring teams should get lost in a sea of polished resumes. The best way to cut through the noise isn’t to spend more time detecting AI-generated content. It’s to shift the focus back to real skills and real potential.
In fact, do we even need resumes anymore?
For many jobs, the answer is no. A lot of the things recruiters need to know already exists—on LinkedIn, in work portfolios, and across social media. Instead of screening documents, recruiters should focus on how candidates think and communicate.
At Recright, we believe hiring should be human-first. Pre-recorded video interviews give recruiters an unfiltered view of candidates so they can make better hiring decisions with less guesswork.
AI can handle the repetitive tasks: first contact, scheduling, follow-ups. That frees up recruiters to focus on what really makes a difference—human interactions.
Because while AI is reshaping recruitment, hiring managers and recruiters—not algorithms—should be in control.
Want to see how leading companies are using video interviews to find top talent?
As AI-generated applications become more common, many hiring teams are looking for better ways to evaluate talent. Here are some common questions about AI in recruitment and how video interviews can help.
1. How can recruiters spot AI-generated applications? AI-generated applications often have flawless grammar and generic wording. AI detection tools can help uncover this, but the most effective solution is to use video interviews, where candidates must demonstrate their actual knowledge.
2. Why are video interviews better than traditional résumé screening? Video interviews allow recruiters to assess candidates beyond what’s on a résumé. They offer insights into communication skills and team fit – qualities that text-based applications can’t convey.
3. Do video interviews help reduce bias in hiring? Yes! Standardized video interviews create a consistent and fair selection process, where all candidates are evaluated based on the same criteria. This minimizes unconscious bias and makes hiring more inclusive.
4. Can AI still be a useful tool in recruitment? Absolutely. AI can streamline tasks like scheduling and communication, but it should complement – not replace – human decision-making. Video interviews ensure that strong candidates aren’t filtered out just because they lack certain keywords.
5. How do video interviews make the hiring process faster and smoother? Video interviews speed up the hiring process by allowing recruiters to pre-screen candidates. Pre-recorded responses can be reviewed at any time, enabling multiple decision-makers to collaborate asynchronously.
See how pre-recorded video interviews can transform your hiring process. Book a Demo today!
AI-generated applications often feature flawless grammar and generic phrasing. While AI detection tools can help, the most effective way is to incorporate video interviews, where candidates must demonstrate their actual knowledge.
Video interviews allow recruiters to assess candidates beyond a resume. They provide insights into communication skills, and cultural fit—qualities that text-based applications fail to capture.
Yes! Standardized video interviews create a consistent evaluation process, ensuring all candidates are judged on the same criteria. This minimizes unconscious bias and improves fairness in hiring.
Absolutely. AI can streamline scheduling, and communication, but it should complement human decision-making. Video interviews ensure that AI doesn’t eliminate strong candidates based on keyword filtering alone.
Video interviews reduce time-to-hire by allowing recruiters to pre-screen candidates efficiently. Pre-recorded responses can be reviewed at any time, allowing multiple stakeholders to collaborate asynchronously.
