Khyati Sundaram, CEO of Applied, a London-based recruitment platform serving over 200 customers, reveals the telltale signs that job applicants have used AI to write their applications and résumés. With years of experience reviewing thousands of skill-based test answers since joining Applied in 2018, Sundaram has identified multiple subtle indicators of AI usage that hiring managers now routinely screen for.
The Detection Challenge: While AI can improve efficiency and formatting, Sundaram notes there’s no foolproof method to detect AI-generated content with 100% accuracy. Recent studies have shown large AI models falsely classifying documents like the Bible and US Constitution as AI-generated, creating a “cloudy atmosphere” for detection. To address this, Applied has implemented a similarity detector approach, where human reviewers compare 20-30 applications simultaneously to identify recurring patterns in syntax, paragraph structure, and language.
Key Warning Signs: The most common giveaways include unusual capitalization patterns, where every word in a sentence is capitalized or unnecessary capital letters appear in phrases. AI-written text also tends to generate excessive punctuation that doesn’t match natural speech patterns. Perhaps most revealing, AI-assisted résumés often share identical structural elements—the same number of headings, paragraphs, and bullet points across multiple applications for the same role.
Nuanced Evaluation Process: Applied doesn’t automatically reject candidates suspected of using AI. Instead, they employ a collaborative review process where multiple team members examine flagged applications and consider the candidate’s entire skillset before making decisions. Different organizations have varying policies, with some accepting AI use while others immediately discard suspicious applications.
Strategic AI Usage Recommendations: Sundaram acknowledges AI isn’t disappearing from the job application process and advises candidates to use it strategically. She recommends leveraging large language models like GPT for synthesizing information, improving conciseness, and creating structure—particularly valuable for non-native English speakers. Rather than using AI to complete applications, candidates should run job descriptions through ChatGPT to identify key skills and attributes hiring managers seek, then craft personalized responses based on those insights.
Key Quotes
AI can be a powerful tool for improving efficiency and formatting, but AI-written answers often sound generic and structurally look the same.
Khyati Sundaram, CEO of Applied, explains the fundamental problem with AI-generated job applications. This observation matters because it highlights how AI, despite its sophistication, can actually harm candidates by making them blend in rather than stand out in competitive hiring processes.
I’ve had conversations with several people on the job hunt who’ve told me they use AI to even out the power dynamic between themselves and employers, many of whom use AI in their own hiring processes. I think that’s fair.
Sundaram acknowledges the reciprocal nature of AI adoption in recruitment, recognizing that job seekers view AI as a leveling tool when employers already use AI for screening. This perspective is significant as it validates strategic AI use while emphasizing the need for authenticity.
We’ve found it much easier to see patterns emerging when examining 20 to 30 applications simultaneously rather than just looking at one in isolation.
This quote reveals Applied’s detection methodology, explaining why their similarity detector approach proves more effective than examining individual applications. It demonstrates how pattern recognition at scale becomes the key to identifying AI usage in the current technological landscape.
Our Take
This article illuminates a fascinating paradox in modern recruitment: AI detection itself requires human judgment and comparative analysis, not just more sophisticated AI. Sundaram’s similarity detector approach represents a pragmatic middle ground, acknowledging that perfect detection is impossible while still maintaining hiring integrity.
What’s particularly noteworthy is the nuanced stance on AI usage. Rather than blanket rejection, Applied recognizes legitimate use cases—non-native speakers improving clarity, technical roles demonstrating AI proficiency—while discouraging wholesale outsourcing of applications to AI. This balanced perspective likely represents where most industries will land: AI as augmentation tool rather than replacement.
The strategic advice to use AI for understanding job requirements rather than generating responses is astute, positioning AI as a research and preparation tool. This approach develops genuine understanding while leveraging AI’s analytical capabilities—a model applicable far beyond job applications to professional development broadly.
Why This Matters
This story highlights a critical evolution in the AI arms race between job seekers and employers. As AI tools become ubiquitous in recruitment, both sides are adapting their strategies, creating a new dynamic in hiring processes. The development of detection methods like similarity analysis represents employers’ response to widespread AI adoption, signaling that authenticity and personalization remain valued in competitive job markets.
The implications extend beyond individual applications. This trend reflects broader questions about AI’s role in professional contexts: when is augmentation acceptable versus when does it constitute misrepresentation? For businesses, the challenge lies in distinguishing between candidates who strategically leverage AI tools (a valuable modern skill) versus those who rely entirely on AI-generated content, potentially masking capability gaps.
For the AI industry, this represents a growing market for detection technologies and highlights the limitations of current AI models in distinguishing human from machine-generated content. The fact that even sophisticated models misclassify historical documents underscores ongoing challenges in AI accuracy and reliability, with real consequences for job seekers navigating an increasingly AI-mediated employment landscape.
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Source: https://www.businessinsider.com/how-employers-know-ai-used-job-application-resume-2024-10