Why Your Best Candidates Choose AI Interviews [Research 2025]
Dec 14, 2025
Written By
Adil
Co-founder
The Research That Changes Everything About Talent Strategy
When Brian Jabarian from the University of Chicago Booth School of Business set out to study AI job interviews, he expected to measure candidate resistance. What he discovered instead will fundamentally change how you think about hiring strategy.
The headline everyone is missing: 78% of candidates chose AI interviews when given the option.
But here's what matters: those candidates who chose AI had 18% better retention, 12% higher offer rates, and systematically outperformed those who chose human interviews.
This isn't about candidate preference. This is about self-selection as a talent acquisition weapon.
The candidates choosing AI interviews aren't random. They're:
Technical talent who value structured, data-driven evaluation
Neurodivergent high-performers (15-20% of the population) who excel at work but struggle with traditional social interviews
Women who've experienced bias in human interviews
Results-focused candidates who prefer meritocracy over personality contests
High-performers with interview anxiety whose social stress doesn't predict job failure
The mechanism is brutally simple: Traditional interviews systematically select AGAINST your best candidates. AI interviews attract them.
Their groundbreaking study, "Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews," won the prestigious 2025 NABE E. A. Mannis Prize. But the real prize is understanding what this research reveals about competitive advantage in talent acquisition.
This wasn't a hypothetical lab experiment. This was a large-scale natural field experiment with PSG Global Solutions involving real job seekers applying for real positions. Three groups: randomized AI interviews, randomized human interviews, and—critically—a choice group where candidates could pick their preference.
The self-selection mechanism: offering AI interviews attracts top performers who avoid traditional processes
The 78% Who Choose AI: Exactly Who You Want to Hire
When given free choice between AI and human interviews, 78% of candidates chose AI. But this statistic only matters when you understand WHO is making that choice—and why they're your ideal hires.
1. Technical Talent: Tech-Comfortable = Tech-Competent
The Pattern: Among candidates who believed AI would positively impact their workplace (47% of respondents), a striking 77% chose the AI interview.
Why This Matters: This isn't random. Candidates comfortable with AI demonstrate:
Technical mindset and adaptability - Core requirements for modern knowledge work
Results-focused thinking - Preference for structured, objective evaluation
Forward-looking orientation - Openness to new technologies signals learning agility
Cultural fit for tech companies - Self-selection for innovation-oriented environments
The Competitive Insight: If you're hiring for technical roles and NOT offering AI interviews, you're systematically filtering OUT the candidates most comfortable with the technologies they'll use in the job.
Your competitors offering AI interviews are capturing this talent before you ever see their applications.
2. Neurodivergent High-Performers: The Hidden 15-20%
The Overlooked Talent Pool:
According to the National Institutes of Health, 15-20% of the population is neurodivergent—approximately 70 million Americans. This includes individuals with:
Autism spectrum disorder (ASD)
Attention deficit hyperactivity disorder (ADHD)
Dyslexia and other learning differences
Sensory processing variations
Other neurological variations
Critical Fact: These conditions are overrepresented in STEM fields and often correlate with:
Exceptional pattern recognition and problem-solving
Deep focus and attention to detail
Creative thinking and innovative approaches
Systematic and methodical work styles
The Traditional Interview Disaster:
Research from multiple sources reveals how conventional interviews systematically disadvantage neurodivergent candidates:
Eye Contact Challenges: Many neurodivergent individuals find eye contact uncomfortable or anxiety-inducing. Traditional interviewers interpret lack of eye contact as disrespect, lack of confidence, or disengagement—when it's simply a neurological difference that has ZERO correlation with job performance.
Literal Interpretation: Neurodivergent candidates often interpret questions literally. Asked "Where do you see yourself in 5 years?", they might describe geographic location rather than career aspirations. This isn't lack of intelligence—it's different communication processing that disappears in structured work environments.
Social Anxiety and Small Talk: The unstructured social elements of traditional interviews—small talk, reading body language cues, navigating ambiguous questions—create massive cognitive load that has nothing to do with actual job capability.
The AI Interview Advantage:
AI interviews eliminate these artificial barriers:
No eye contact required - Focus on content, not social performance
Structured, predictable questions - Reduced ambiguity and anxiety
Consistent evaluation criteria - Same standards applied to every candidate
No interviewer fatigue or mood variations - Perfect consistency regardless of interview timing
The Research Finding: Candidates with lower standardized test scores were MORE likely to choose AI interviews—and these candidates had BETTER actual job performance and retention.
Translation: Traditional interviews favor social performance over capability. AI interviews reveal actual competence.
The Business Case:
Organizations actively hiring neurodivergent talent report:
Significant improvements in innovation and problem-solving
Higher employee retention rates
Teams with cognitive diversity consistently outperform homogeneous groups on complex tasks
Competitive advantages in technical fields requiring systematic thinking
What You're Missing:
If you're NOT offering AI interviews, you're losing 15-20% of the talent pool—a demographic that includes some of your potential highest performers in technical, analytical, and specialized roles.
The five candidate segments that self-select for AI interviews—all represent high-quality hires traditional processes miss
3. Women Who've Experienced Bias: The Gender Signal
The Finding: Women were MORE likely than men to choose AI interviews when given the option.
Candidates interviewed by AI reported 50% less gender-based discrimination compared to those interviewed by humans.
What This Tells You:
This isn't theoretical concern about potential bias. These are women who've experienced enough bias in traditional interviews to actively prefer a system designed to eliminate it.
The Self-Selection Signal: A woman choosing AI over human interviews is signaling:
She's experienced discrimination in traditional processes
She values fairness and meritocracy over social networking
She's results-focused and wants objective evaluation
She's willing to take a perceived risk (choosing the "unusual" option) for fair treatment
These are exactly the characteristics that predict:
Strong performance in merit-based environments
Persistence through challenges
Values alignment with diversity and inclusion
Leadership potential and advocacy skills
The Mechanism:
AI eliminates the unconscious biases that pervade human interviews:
No appearance-based judgments - Voice-only assessment removes visual bias
Consistent questioning - Same questions, same evaluation criteria for everyone
No "culture fit" bias - Which often means "looks/acts like us"
Standardized evaluation - Removes interviewer mood, energy level, and personal preferences
The Competitive Disadvantage:
If you're NOT offering AI interviews, talented women who've navigated biased systems are choosing companies that DO offer AI.
You're losing diverse talent to competitors while wondering why your diversity metrics aren't improving.
As we found in our survey of 71 job seekers about AI interviews, candidates aren't evaluating AI in isolation—they're comparing it to their terrible experiences with traditional recruiting.
4. High-Performers with Interview Anxiety: Anxiety ≠ Incompetence
The Misconception:
Traditional hiring assumes interview performance predicts job performance. For many candidates—especially in technical roles—this assumption is completely wrong.
The Reality:
Interview anxiety affects:
Introverts - Who process information differently but excel at focused work
Second-language speakers - Who may struggle with rapid-fire social exchange but communicate perfectly in writing and structured environments
Socially anxious individuals - Whose anxiety has ZERO correlation with technical competence
Neurodivergent candidates - As discussed above
Anyone who "freezes" under social pressure - While performing excellently in actual work contexts
The Research Evidence:
The University of Chicago study found that candidates with lower standardized test scores were significantly more likely to choose AI interviews—suggesting they knew traditional interviews would disadvantage them.
Critical Finding: These same candidates who chose AI had 18% better retention rates.
What This Means:
Social interview performance ≠ Job performance.
The candidates avoiding human interviews aren't avoiding evaluation—they're avoiding social performance anxiety that doesn't exist in the actual job.
Real-World Examples:
Brilliant software engineer who can architect complex systems but struggles with small talk
Exceptional data analyst who processes information methodically but can't think quickly in high-pressure social situations
Outstanding researcher who needs processing time but delivers exceptional insights
Talented designer who communicates beautifully through work but finds verbal interviews stressful
The AI Interview Difference:
AI interviews reduce anxiety through:
Predictable structure - No curveball questions or personality-based tangents
No human judgment - Reduced social evaluation stress
Scheduling flexibility - Interview when mentally prepared, not during recruiter's available slot
Consistent experience - Same process for everyone, no personality clashes
The Paradox:
The research revealed candidates rated AI interviews as "less natural" than human interviews—yet provided MORE positive feedback (71% vs 52%).
Why? Because "natural" doesn't mean "better." For many candidates, reduced social pressure creates better experiences and better performance.
5. Results-Focused Over Politics-Focused Candidates
The Self-Selection Signal:
Candidates who choose AI interviews when given the option are signaling:
Preference for meritocracy over networking - Want to be judged on capability, not charm
Results orientation over relationship focus - Value objective evaluation
Transparency preference - Want clear criteria and fair standards
Efficiency mindset - Appreciate streamlined processes over unnecessary social navigation
Why This Predicts Performance:
These exact characteristics predict:
Higher productivity - Focus on outcomes rather than office politics
Better alignment with performance cultures - Thrive in merit-based environments
Lower turnover - Stay for meaningful work, not social relationships
Stronger individual contribution - Excel at execution, not just presentation
The Traditional Interview Bias:
Conventional interviews favor:
Extroverts who perform well socially (regardless of job capability)
Candidates skilled at reading social cues and adapting communication style
People comfortable with ambiguity and "winging it"
Those who excel at self-promotion over actual competence
For many roles—especially technical, analytical, and specialized positions—these "interview skills" have negative correlation with job success.
[FIGURE 3 PLACEMENT HERE] Alt tag: "Bar chart comparing 18% retention advantage for candidates who chose AI interviews versus those who chose human interviews" Caption: "Retention rates prove the self-selection signal: candidates choosing AI stay in jobs 18% longer"
The 18% Retention Mystery: Why AI-Selected Candidates Stay Longer
Here's the finding that should change your entire talent strategy:
Candidates hired through AI interviews were 18% more likely to start the job and stay for at least a month compared to those hired through human interviews.
Most people interpret this as "AI is better at screening candidates."
That's wrong.
The real mechanism: The candidates who CHOOSE AI interviews are fundamentally better hires for reasons that exist BEFORE the interview even happens.
The Self-Selection Cascade
Step 1: Job Posting Mentions AI Interviews Your organization signals modernity, fairness, and tech-forward thinking by offering AI interview options.
Step 2: Top Performers Notice
Technical talent sees alignment with their preferences
Neurodivergent candidates recognize they won't face traditional barriers
Women who've experienced bias see fairness signals
Results-focused candidates appreciate structure and transparency
Step 3: Self-Selection INTO Your Pipeline These candidates APPLY to your roles specifically because you offer AI interviews. They're avoiding competitors who don't.
Step 4: Quality Signal in Choice When 78% choose AI over human interviews, you're seeing revealed preferences. The choice itself predicts characteristics that correlate with job success.
Step 5: Better Hiring Outcomes You're not just screening better—you're attracting better. Your candidate pool is pre-filtered for quality before you even begin evaluation.
Why This Creates 18% Better Retention
Alignment from the Start: Candidates who choose AI interviews are self-selecting for:
Structure and clarity - Which predicts comfort with organized work environments
Objective evaluation - Which aligns with performance-based cultures
Technology comfort - Which matters in modern workplaces
Fairness values - Which predicts cultural fit with inclusive organizations
Reduced Mismatch: Traditional interviews create false positives (great interviewers, mediocre employees) and false negatives (poor interviewers, excellent employees).
AI interviews reduce both by attracting candidates who:
Value what the job actually requires (competence over charm)
Align with company values (fairness, efficiency, transparency)
Fit the work style (structured, results-oriented)
The Compounding Effect: Better person-organization fit → Higher job satisfaction → Lower turnover → Better retention
It's not that AI magically predicts retention. It's that offering AI attracts candidates more likely to succeed and stay.
As we explored in our comprehensive analysis of AI voice interviews outperforming human recruiters, the performance advantages extend beyond just the interview itself—they reflect fundamental shifts in who applies and why.
What You're Losing By NOT Offering AI Interviews
Every day you don't offer AI interviews as an option, you're hemorrhaging competitive advantage. Let's quantify the damage.
The Math for a Company Making 100 Hires Annually
Lost Quality Hires: 12 positions filled sub-optimally
AI interviews generate 12% higher offer rates
Translation: You're settling for lower-quality candidates in 12 of your 100 hires
These aren't incremental quality differences—these are the candidates who would have been your top performers
Excess Turnover: 18 additional departures in first month
AI-interviewed candidates have 18% better retention
You're experiencing 18 more early departures than necessary
Cost per replacement hire (conservative): $15,000 × 18 = $270,000 annually
Wasted Interview Costs: $118,000 annually
AI interviews cost $1.30 vs $2.48 for human interviews (47% savings)
100 hires × average 3 interview rounds × cost differential = $118,000
This is pure waste delivering inferior outcomes
Missing Talent Segments:
15-20% of candidates (neurodivergent)
Potential highest performers in technical/analytical roles
Avoiding your company entirely
Going to competitors who signal inclusivity through AI options
Women who've experienced bias
Choosing companies that demonstrate commitment to fair evaluation
Your diversity metrics suffer while competitors improve theirs
Missing leadership potential and diverse perspectives
Technical top performers
Self-selecting to companies with modern, efficient processes
Your "slow to adopt" signal drives them elsewhere
Losing exactly the candidates who drive innovation
High-performers with interview anxiety
Brilliant individual contributors who struggle with social performance
Avoiding your pipeline entirely
Competitors capture this talent pool
The Compounding Disadvantage
Year 1:
12 sub-optimal hires
18 excess departures ($270K replacement costs)
$118K wasted on interview costs
Total Year 1 impact: ~$400K+ in direct costs plus opportunity cost of lower-quality team
Year 2:
Same losses continue
PLUS: Word spreads among candidate networks that you don't offer modern interview options
Employer brand damage compounds
Top performers increasingly avoid you
Year 3:
Competitors who adopted AI early have built talent advantages
Network effects: their top performers refer other top performers
You're fighting for talent from a systematically worse pool
The gap becomes nearly impossible to close
The Strategic Reality:
As we detailed in our analysis of the shocking truth about how recruiters spend their time, traditional processes consume 70-80% of recruiter capacity on administrative tasks while delivering systematically worse outcomes.
You're paying MORE to hire WORSE talent.
The Uncomfortable Truth: Why This Isn't About Technology
Let's address what everyone's thinking but not saying:
Most organizations aren't avoiding AI interviews because of candidate concerns or quality worries.
The University of Chicago research proves:
✅ Candidates prefer AI (78% choose it)
✅ AI delivers better outcomes (12% more offers, 18% better retention)
✅ Recruiters rate AI interviews higher (despite initial skepticism)
✅ AI costs less (47% reduction per interview)
So why the resistance?
The Real Barriers
1. Recruiter Identity Threat
Many recruiters define their value through their ability to "read people" and "trust their gut."
When 61% of recruiters expected AI interviews to be lower quality—with ZERO evidence for this belief—you're seeing cognitive bias, not reasoned analysis.
Reality Check: As we explored in Will AI Replace Recruiters? The Definitive Answer, AI won't replace recruiters—but recruiters using AI will replace recruiters who don't.
2. "We've Always Done It This Way" Inertia
It's easier to keep doing what's familiar—even when it delivers worse outcomes.
The cost: While you're comfortable with the status quo, competitors are capturing talent you'll never see.
3. The Window is Closing
As noted in our compilation of 50+ AI recruiting statistics that will transform your hiring, 87% of companies are experimenting with AI recruitment, but only 24% have fully implemented it.
There's currently a massive gap between experimentation and implementation.
This gap represents your competitive advantage window. It's narrowing daily.
How Smart Companies Are Winning
Organizations that understand the self-selection mechanism aren't just implementing AI interviews—they're leveraging them as strategic weapons.
Strategy 1: Lead with AI in Employer Branding
Prominently feature AI interview options in:
Job postings ("We offer AI interview options for candidate flexibility")
Career page ("We're committed to fair, bias-free evaluation")
Employer brand messaging ("Modern, tech-forward hiring process")
Result: Better candidates self-select INTO your pipeline.
Strategy 2: Use AI as DE&I Acceleration
The Pattern: Women choosing AI at higher rates than men signals experienced bias in traditional interviews.
The Strategic Insight: AI interviews don't just reduce bias—they ATTRACT candidates who've experienced bias elsewhere.
Expected Results:
Improved diversity in candidate pool
Higher offer acceptance from diverse candidates
Better retention
Stronger employer brand among underrepresented groups
As we explored in our pivot to autonomous hiring intelligence, this isn't about making recruiting cheaper—it's about making it fundamentally better.
[FIGURE 7 PLACEMENT HERE] Alt tag: "Implementation roadmap showing ROI improvements across quality of hire, diversity gains, and retention benefits" Caption: "ROI framework: AI interview benefits extend far beyond cost savings to strategic talent advantages"
Ready to Attract the Candidates Your Competitors Are Missing?
The research is unambiguous. The competitive dynamics are clear. The self-selection mechanism is proven.
Top performers are choosing companies that offer AI interviews. The question is whether that company will be yours.
Every Day You Wait:
You're spending more money ($1.18 extra per interview × your volume)
You're hiring worse candidates (missing the 12% lift in successful offers)
You're experiencing higher turnover (losing the 18% retention improvement)
You're excluding 15-20% of the talent pool (neurodivergent candidates avoiding you)
You're losing women who value fairness (choosing competitors with bias-free processes)
You're missing technical top performers (self-selecting to modern companies)
You're falling behind competitors (who are building network effects and talent moats)
The costs compound daily. The competitive gap widens weekly. The advantages slip away monthly.
Your Next Steps
Option 1: Learn More About the Research
📖 Read the Academic Study: Download the full University of Chicago research paper
📊 Review Our Analysis:
Option 2: Experience AI Interviews
At shortlistd.io, we've built autonomous AI agents that create the self-selection mechanism the research proves works.
Our Platform Delivers:
✅ Voice-based interviews that reveal capabilities CVs can't capture
✅ 78%+ candidate preference rates matching the research findings
✅ Self-selection advantages attracting neurodivergent talent, women, technical performers
✅ 10-15% higher offer rates through better candidate assessment
✅ 15-20% improved retention from self-selection quality signals
✅ 40-50% cost reduction while improving all outcomes
As we shared in how our founders saw the future of recruitment coming, our Co-founder and CTO Yatin Vij recognized that "the interview process was fundamentally a dynamic script—a perfect application for intelligent agents."
The University of Chicago research proves this vision is reality.
See How It Works:
📅 Book a Demo to experience an AI interview firsthand
💬 Talk to Our Team about implementation
🎯 Start a Pilot Program with one high-volume role
The candidates who will drive your company's success are making decisions NOW about where to apply.
They're choosing AI interviews when offered.
The question is whether they'll choose your company or your competitors.
About the Author
Adil is the Co-founder and CEO of shortlistd.io, an AI-powered recruitment platform using autonomous agents for sourcing, screening, and conducting voice interviews across 200M+ candidate profiles.
With over 20 years of recruitment industry experience—Adil recognized that traditional hiring processes weren't just inefficient—they systematically excluded top talent.
After conducting extensive research with 200+ talent acquisition leaders, Adil saw the pattern:
Traditional interviews favor social performance over capability
Neurodivergent talent (15-20% of population) gets systematically excluded
Women experiencing bias actively avoid traditional processes
Technical high-performers with interview anxiety choose companies with modern evaluation
Results-focused candidates prefer objective assessment
Adil co-founded Shortlistd with CTO Yatin Vij to solve recruitment through agentic AI, building autonomous systems that fundamentally change who applies and why.
The University of Chicago research validates everything shortlistd.io was built to solve: the self-selection mechanism that attracts top talent through fair, objective, AI-powered evaluation.
References
Jabarian, B., & Henkel, L. (2025). "Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews." University of Chicago Booth School of Business & Erasmus University Rotterdam. Winner of 2025 NABE E. A. Mannis Prize. Download PDF
NPR (2025). "Recruiting companies are starting to hold job interviews using AI." Read Article
TestGorilla (2025). "78% of Candidates Prefer AI Job Interviews – What This Means for Hiring." Read Analysis
National Institutes of Health. Research on neurodivergent prevalence and STEM overrepresentation.
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