High-volume hiring involves one unavoidable challenge: too many resumes, not enough time. When thousands of applications flood in for open positions, you need a manageable shortlist.
Resume screening software seems like the answer. But it often relies on rigid criteria (e.g., keyword matching or past hiring data), overlooks great candidates, and reinforces bias. Worse, it struggles to distinguish real skills from AI-generated experience.
In this post, you’ll learn why resume screening software falls short and how pre-hiring assessments lead to faster, better hires.
How Did Resume Screening Software Become the Norm?
The first resume is said to have been made by Da Vinci in 1482. For more than five centuries, the resume has lived on. Today, hiring teams rely on resumes to evaluate candidates, sifting through stacks of applications and cover letters. The goal is to complete two of the most time-consuming hiring tasks —reviewing candidate pools and internal screening! Out from under a pile of papers, human resources (HR) teams have since turned to resume screening software.
These tools promised to highlight candidates based on keywords, job titles, and work experience, soon becoming the industry standard for filtering job listing applicants. As artificial intelligence (AI) advances with ChatGPT, which can write a resume in seconds, and as one-click applications persist, the problem of resume buildup and backlog is real.
The Most Common Types of Resume Screening Tools
Most candidate screening tools fall into three categories:
- Keyword-based filters. These resume scanners look for relevant keywords (e.g., specific words or phrases) that match the job requirements.
- AI-powered screeners. More advanced systems use AI to look beyond simple keyword matches and assess experience, skills, and even writing style.
- Parsing tools. This resume-filtering software extracts key details (e.g., names, job titles, and certifications) from documents and social media profiles (e.g., LinkedIn). Then, it organizes them in searchable databases.
Many high-volume hiring teams rely on an applicant tracking system (ATS) as a central recruitment hub. Most ATS software includes built-in resume screening tools, while other systems simply manage workflows.
These hubs can handle everything—from job postings to storing contact information and scheduling interviews. HR Research Institute suggests that 93% of organizations use recruitment software for talent acquisition, with ATS being the most common type.
For example, here’s an ATS resume screener filtering by state and the keyword “PHP”:
The idea is simple: let software handle the heavy lifting to save recruiters time and effort. But does it actually find the best candidates? That’s where things get complicated.
The Problem with ATS and Automated Resume Screening Software
Resume screening tools promise to make hiring processes more efficient. But they can only be as good as the data they filter. And that’s where things start to fall apart.
Most hiring teams know that candidates’ resumes aren’t always reliable. According to a TopResume poll, over 77% of recruiters have spotted lies when reviewing them.
Now, with AI-generated resumes becoming common, it’s harder than ever to tell what’s real. Many are optimized to pass screening tools rather than reflect actual skills, often exaggerating experience or using vague buzzwords.
So, how can hiring teams trust the output if tools rank applicants on keyword optimization and flawed information?
Here are five reasons resume screening software falls short:
- Keyword-based filters miss talent. Many screening tools reject candidates who don’t use exact phrasing from job descriptions. A highly qualified applicant might say “budget forecasting,” but the system filters them out when looking for “financial planning.”
- AI resume screeners can reinforce hiring bias. Machine learning models are only as fair as the data they’re trained on. For example, Amazon’s AI recruitment tool infamously downgraded female resumes because of its training on past hiring decisions that favored male candidates.
- ChatGPT can create polished resumes in minutes. Many screening tools can’t detect AI, so companies may unknowingly prioritize applications made by a bot writer and a resume template (not the best candidate).
- Unreliable results cost time and money. How much effort do you save if tools filter out strong candidates for the wrong reasons? When hiring managers have to review overlooked applicants or constantly adjust filters, automation may not make the resume screening process more efficient.
- Format issues lead to automatic rejections. Many screening systems struggle with PDF file types, unique designs and fonts, or non-traditional CV layouts. A highly skilled designer with a visually appealing resume might get rejected because the system can’t parse anything that’s not in .docx (Microsoft Word) format.
Resume screening software often filters for compliance, not ability. If a candidate doesn’t check the right boxes or use specific keywords, they’re out. And that means companies miss out on talented people for reasons that have nothing to do with skill.
Why High-Volume Recruiters Should Forget Resumes Altogether
Resumes have been the cornerstone of hiring for decades. But they can create more problems than they solve. At best, a CV is a rough snapshot of work experience (not an accurate indicator of skill). At worst, it’s a carefully crafted marketing document designed to game the system.
Efficiency, accuracy, and fairness are critical in high-volume hiring. And resumes fail on all three counts:
- Recruiters waste time and delay hiring when they have to revisit overlooked candidates and second-guess decisions
- A well-written resume doesn’t prove someone can do the job—just that they know how to market themselves
- Resumes undervalue raw skill and potential, while candidates with specific job titles or years of experience have an advantage
This isn’t to say automation has no place in hiring—far from it. HR artificial intelligence (AI-driven technology that assists with candidate evaluation and decision-making) can be an extremely powerful tool when it screens based on ability.
What to Use Instead: Skills-Based Hiring Assessments
If resumes are flawed, what’s the alternative? Cut straight to ability. Let job seekers prove what they can do without these documents or interviews.
AI-powered skills assessments allow recruiters to evaluate applicants on real-world tasks. These open-ended simulations (e.g., dealing with an unhappy customer over live chat or making a sales call) give hiring teams objective insights into candidates’ competence.
Unlike resume screening software, the best assessment tools analyze and grade candidates’ soft skills with 98% accuracy. These assessments measure qualities like emotional intelligence, time management, leadership ability, and adaptability.
For example, tools with AI capabilities will:
- Detect role-specific people skills (e.g., active listening, probing, and empathy) in text and voice recordings
- Score language fluency, grammar, and comprehension in speech and writing
This focus on human skills leads to a higher quality of hire, as teams assess candidates based on how they’ll do the job, rather than resume-writing skills. Here are five of the top benefits of skills-based hiring assessments as they compare to resume screening tools:
- Faster, fairer hiring. High-volume recruitment processes demand efficiency. AI-powered skills assessments identify top candidates at scale without relying on guesswork.
- Improved job performance. Candidates who score highly in pre-hiring skills assessments perform better on the job than low scorers.
- Reduced bias. Automated systems won’t overvalue polished resumes or prestigious job titles—decisions are based on ability, not background.
- A better candidate experience. Many applicants feel frustrated when ATS filters reject them unfairly. They want engaging assessments to demonstrate their skills during job searches.
- Fewer bad hires. Skills-based hiring reduces bad hire rates by 400% for large enterprises.
Instead of using technology to review resumes, leverage AI in skills assessments. These data-driven, conversational tests remove bias and pointless filters, highlighting candidates who can truly perform.
Wrapping Up Resume Screening Software
High-volume hiring doesn’t need resume screening software to work efficiently. Hiring should be about what candidates can do, not who can craft the best resume. These documents are relics of the past—skills-based hiring is the future.
Image Credits
Feature Image: Via Unsplash/João Ferrão
Image 1: Via Klaxos
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