What Candidates Really Think About AI Interviews

The AI Interview Debate Is Missing the Point Entirely

Everyone's arguing about the wrong thing.

LinkedIn is full of hot takes about AI interviews. Some people claim they're the future of fair hiring. Others say they're dehumanizing and biased. The debate has become tribal: you're either pro-AI or pro-human, with no middle ground.

But here's what nobody's asking: What do candidates actually think?

Not the thought leaders. Not the HR tech vendors. Not the recruiters defending their turf. The people who actually sit through these interviews - what do they want?

So we asked them. 71 respondents, currently looking for work, recently hired, or fresh off a job search. We asked about their experiences with AI interviews, their concerns, their deal-breakers, and what would actually make the process better.

The results surprised us. And they should fundamentally change how we think about recruiting technology.

Spoiler: It's not about AI versus humans. It's about speed versus ghosting. And when you frame it that way, AI wins.

The Initial Split: A Perfect Divide

Let's start with the baseline: When asked if they'd be willing to take an AI interview, candidates split almost perfectly down the middle: 46.4% said yes, 46.4% said no, and only 7% were unsure.

This is a true 50/50 split - remarkably precise. Dig deeper and you see the breakdown:

• 22.5% are "definitely yes"

• 23.9% are "probably yes"

• Only 7% are sitting on the fence

• 22.5% are "probably no"

• 23.9% are "definitely no"

What's striking is how few people are undecided. This isn't a tentative "maybe." People have formed strong opinions - they're just divided. The opportunity isn't to convince fence-sitters. It's to shift the "no" camp by delivering real value.

The real question isn't whether candidates like AI interviews in theory. It's what makes them willing to try one in practice.

Why 46% Say "No Thanks" to AI Interviews

The opposition is substantial - a full 46.4% are unwilling to try AI interviews. And their concerns are specific, real, and worth understanding:

Lack of human connection tops the list. 49.3% of respondents cited this as a major concern- the highest of any factor. The discomfort of talking to a screen instead of a person matters more than technical concerns about the AI itself.

Fear of being misunderstood. 46.5% worry that AI might misunderstand their responses—particularly candidates with non-linear career paths, career changers, or those whose experience doesn't fit neat categories.

Soft skills assessment concerns. 38% are worried AI can't properly evaluate soft skills, interpersonal abilities, and the nuances that make them good at their jobs.

The impersonal factor. 33.8% say AI interviews feel impersonal, and an equal percentage (33.8%) worry they can't showcase their personality effectively.

Bias concerns exist but aren't primary. Interestingly, AI bias ranked lower at 28.2% - significant but not the top concern many assume it would be.

These aren't irrational fears. These are legitimate concerns about whether AI can capture what makes them valuable beyond what's on a resume.

What worries candidates most about AI interviews

Why 46% Are Open to AI Interviews

But here's the equally important story: 46.4% of candidates ARE willing to try AI interviews. These weren't necessarily technology enthusiasts - they were pragmatists who saw potential advantages:

Speed and efficiency. Many candidates mentioned frustration with traditional processes, sending hundreds of applications, hearing back from only a handful, often after weeks of silence. The promise of faster decisions resonated strongly.

Scheduling convenience. The ability to complete an interview on your own schedule, without coordination hassles or taking time off work, appealed to many respondents, especially those currently employed or with caregiving responsibilities.

Consistency and fairness potential. Some candidates actually liked the idea of standardized evaluation. They've experienced phone screens where recruiters seemed disengaged or inconsistent, and wondered if AI might be more objective.

Better than the alternative. This theme emerged repeatedly: many candidates would rather be interviewed by AI than never get past automated resume screening systems. They'd rather have a chance to demonstrate their skills than be filtered out based on keyword matching alone.

The division isn't really about loving or hating AI. It's about whether the AI interview experience would be better or worse than what they're experiencing now. And with only 7% truly undecided, most candidates have already formed their opinion, they just need the right value proposition to shift it.

The Game-Changing Finding: It's Not AI vs. Human - It's Speed vs. Ghosting

This is where the data gets really interesting.

We posed a direct trade-off question: "Would you prefer an AI interview that gives you results in 48 hours OR a human interview where you wait 2-3 weeks for feedback?"

The results completely reframe the conversation:

• 47.9% chose AI with fast results

• 39.4% chose human with longer wait

• 12.7% said "it depends"

Nearly half of all candidates actively prefer AI interviews over human interviews when AI delivers speed.

This is the insight that changes everything. Candidates aren't evaluating AI interviews in isolation. They're comparing them to their actual experience with traditional recruiting, and that experience is terrible.

The current recruiting reality:

• Average time to hear back after applying: 2-4 weeks (if you hear back at all)

• 75% of applications receive no response whatsoever

• Candidates spend an average of 11 hours per application for roles requiring multiple rounds

• Even after final interviews, 40% of candidates report being ghosted

When you're competing against that baseline, AI interviews with guaranteed fast feedback suddenly look very appealing.

And here's the kicker: among candidates with a clear preference (excluding "it depends"), AI wins decisively. When you force the choice between speed and human interaction, more candidates choose speed.

When forced to choose between speed and human touch, nearly half choose speed

The Dream Job Test: When It Matters, Pragmatism Wins

Here's perhaps the most revealing question: "If an AI interview was the ONLY way to apply for your dream job, would you do it?"

The results:

• 53.5% said "Yes, definitely"

• 19.7% said "Yes, reluctantly"

• 7% were unsure

• 19.7% said no

That's 73.2% willing to do an AI interview when the stakes are high enough.

But here's the real headline: Only 19.7% - less than one in five - would pass on their dream job because of an AI interview. Even among the initial skeptics, most become pragmatists when opportunity knocks.

This tells us something crucial: resistance to AI interviews isn't about principles—it's about risk-benefit calculation. When the opportunity is important enough, nearly three-quarters of candidates are willing to adapt to the process.

The 19.7% who said "yes, reluctantly" are particularly telling. They don't love AI interviews, but they're not willing to give up a dream opportunity because of the interview format. They're pragmatists, not ideologues.

And the 19.7% hard "no"? They're the principled minority. Most candidates will do what it takes when the stakes matter.

When stakes are high, most candidates will adapt to AI interviews

What Actually Changes Minds: The Value-Add Effect

We tested a specific scenario: What if AI interviews provided candidates with valuable feedback - resume tips, skill recommendations, interview performance analysis -regardless of whether they got the job?

This was designed to test whether adding tangible value could shift opinions.

The results showed movement:

• 31.9% said "probably yes—seems valuable"

• 20.3% said "definitely yes—game changer"

• 14.5% remained in "maybe—depends on quality"

• 33.3% remained skeptical

What's interesting here is the direction of movement. While the shift isn't massive (willingness increased from 46.4% to 52.2%), the enthusiasm increased. More candidates moved to "definitely yes" when you add value beyond just the hiring decision.

The insight: It's not about AI or no AI. It's about what candidates get in return for their time and vulnerability.

Right now, most candidates invest significant effort in applications and interviews, then receive nothing back—not feedback, not guidance, often not even a rejection email. They're left wondering what went wrong and how to improve.

If AI interviews can solve that problem—providing fast, actionable feedback that helps candidates improve regardless of the outcome—resistance will crumble.

How fast feedback changes candidate opinions on AI interviews

What Candidates Actually Need: The Top 5 Solutions

Based on the data, here's what makes candidates more willing to accept AI interviews:

1. Transparency About How the AI Works (60.6%)

This was the single most important factor. Candidates want to understand:

• What is the AI evaluating in their responses?

• How are they being scored?

• What criteria determine success?

• What data is being collected and who sees it?

The black box problem is real. When candidates don't understand how AI works, anxiety fills the gap with worst-case assumptions: biased algorithms, unfair scoring, invasive analysis.

But transparency builds trust. When companies clearly explain their evaluation criteria, candidates feel more comfortable engaging with the process.

The irony here is sharp: AI interviews can actually be MORE transparent than human interviews. Most hiring managers struggle to articulate exactly what they're looking for or how they evaluate candidates. At least AI can explicitly state its criteria.

2. Fast Feedback and Results (54.9%)

Speed isn't just about convenience—it's about respect and reducing anxiety. When candidates complete an interview and then wait weeks in limbo, it's psychologically draining.

Fast feedback serves multiple purposes:

• Reduces anxiety and uncertainty

• Allows candidates to move forward with their job search

• Provides closure and learning opportunities

• Demonstrates that the company respects candidates' time

Notably, this factor ranked even higher than having a human review the AI's decision (46.5%). Candidates would rather have fast AI feedback than slow human review.

3. Human Review of AI Decisions (46.5%)

While candidates are willing to be initially screened by AI, many want to know that a human ultimately reviews the decision before they're eliminated from consideration.

This isn't about doubting AI accuracy—it's about feeling like they're not being dismissed by an algorithm without any human consideration of their candidacy.

The ideal system, according to this data, combines AI efficiency with human oversight: AI handles initial screening to save time and increase consistency, but humans make final decisions where judgment and nuance matter.

4. Option to Speak with a Human Later (42.3%)

Even candidates who are comfortable with AI screening want to know they'll eventually talk to a real person if they advance. AI can get you to the short list, but humans close the deal.

This suggests candidates view AI interviews as acceptable for initial screening but insufficient as the only evaluation method. They want AI to supplement human judgment, not replace it entirely.

5. Ability to Redo or Clarify Answers (40.8%)

This addresses the fear of being misunderstood. Candidates worry that if they stumble on a question or explain something poorly, they have no chance to clarify or try again.

The ability to redo or clarify answers makes AI interviews feel less rigid and more forgiving—more like a conversation than a one-shot test.

This is actually easier to implement with AI than with human interviews, where scheduling multiple attempts would be impractical.

The factors that make candidates willing to try AI interviews

The Ghosting Crisis: Why This Matters More Than the Technology

Let's address the issue that dominated open-ended responses: ghosting.

Candidates aren't just frustrated by it. They're exhausted by it. Demoralized by it. And they're making hiring decisions based on avoiding it.

Multiple respondents described being ghosted not just after applications, but after phone screens, after time-consuming take-home assignments, even after final interviews where they were explicitly told they'd hear back within days.

One pattern emerged with crystal clarity: Candidates don't hate AI interviews. They hate being disrespected, ignored, and left in limbo.

If AI interviews can solve the ghosting problem—providing fast, clear communication about decisions and next steps—many candidates will actively choose that over traditional processes, even if they'd theoretically prefer talking to a human.

The comparison isn't AI vs. ideal human interaction. It's AI with respect and communication vs. human process with ghosting and silence.

When you frame it that way, AI wins. Every time.

The Bias Question: Complex but Not the Top Concern

AI bias is a legitimate concern, but the survey revealed something unexpected: It ranked lower than concerns about human connection and being misunderstood.

Only 28.2% cited AI bias as a major concern—significant, but not the primary barrier to adoption.

This doesn't mean bias isn't important. It means candidates are weighing multiple factors, and the human element matters more than many assume.

Several open-ended responses noted that human interviewers are biased too. We know from extensive research:

• Candidates with "white-sounding" names get 50% more callbacks than identical resumes with "Black-sounding" names

• Physical attractiveness influences perceived competence

• Interviewers favor candidates from similar backgrounds

• Gender affects how assertiveness and leadership are evaluated

• Unconscious bias affects every hiring decision

The key difference: AI bias can potentially be measured, audited, and systematically corrected. Human bias is often invisible and unacknowledged.

Some respondents expressed hope that with AI, there's at least accountability if bias is detected—something nearly impossible to achieve with human decision-making.

This doesn't mean AI interviews are automatically fair. It means the bar is lower than we think. The question isn't whether AI is perfectly unbiased. It's whether AI, when properly designed and audited, can be less biased than the current system.

What This Means for Companies Building or Using AI Interviews

If you're considering AI interviews for your hiring process, here's what this data tells you to do right now:

1. Lead With Speed and Communication, Not Technology

Don't sell your candidate experience around having innovative AI. Sell it around solving real problems: the ghosting problem, the waiting problem, the transparency problem.

Weak messaging: "We use advanced AI technology to screen candidates efficiently."

Strong messaging: "Every candidate receives detailed feedback within 48 hours, regardless of outcome."

Candidates don't care about your tech stack. They care about being treated with respect and getting timely communication.

2. Transparency Is Non-Negotiable

60.6% of candidates said transparency about how AI works would make them more willing to participate. This was the single highest-ranked factor. Not nice to have—required.

You don't need to reveal proprietary algorithms, but you absolutely must explain:

• What you're evaluating (relevant experience, communication clarity, specific skills)

• How scoring works (relevance to role requirements, depth of examples provided)

• What you're NOT analyzing (no facial expression analysis, no demographic data)

• Who reviews the results (AI screening + human review for final decisions)

Example of good transparency: "Our AI interview asks 5 questions about your experience with [specific skills]. We evaluate your responses based on relevance to the role, depth of experience, and clarity of communication. We don't analyze facial expressions, tone of voice, or any demographic information. All AI-screened candidates are reviewed by our recruiting team before final decisions."

That's clear, specific, and reassuring—and it probably took 30 seconds to write.

3. Fast Feedback Isn't Optional, It's Your Value Proposition

47.9% of candidates prefer AI interviews with fast results over human interviews with long waits. Speed isn't just nice to have—it's your competitive advantage.

If you implement AI interviews but still make candidates wait 2-3 weeks for responses, you've completely missed the point. You've automated the process without improving the experience.

Commit to 48-72 hour maximum response times. Not "we'll be in touch soon." Not "within the next few weeks." Within 48-72 hours, every candidate should know their status.

And the feedback needs to be substantive. "We're moving forward with other candidates" isn't feedback. "We were looking for 5+ years of experience with Python and Django; you demonstrated 2 years with Python and basic Django knowledge" is feedback.

4. Combine AI Screening with Human Decision-Making

The data shows candidates want both: AI efficiency and human judgment.

The optimal system according to this survey:

• AI handles initial screening: Saves time, increases consistency, ensures everyone gets evaluated

• Humans review borderline cases: Exercise judgment where nuance matters

• Humans conduct later-stage interviews: Assess cultural fit, soft skills, team dynamics

• Humans make final hiring decisions: AI informs but doesn't decide

This hybrid approach addresses most concerns while capturing the benefits of both AI (speed, consistency) and humans (judgment, nuance, relationship building).

5. Make It Easy to Showcase Skills, Not Just Talk About Them

One frustration that emerged: candidates want to SHOW what they can do, not just describe it.

If possible, structure AI interviews to include:

• Technical assessments where relevant (live coding, portfolio reviews)

• Scenario-based questions that demonstrate problem-solving

• Examples they can reference from their work

• Clear opportunities to highlight specific skills the role requires

The more concrete candidates can be, the better they feel about the evaluation.

The Real Competition: Not Human Interviews, But Resume Screeners

Here's an insight that surprised me: Candidates view AI interviews completely differently than AI resume screening.

Resume screeners are widely disliked—seen as arbitrary, unfair filters that eliminate people for superficial reasons like keyword density, formatting, or employment gaps.

AI interviews, by contrast, are viewed as opportunities—chances to prove yourself beyond a piece of paper.

Why the stark difference? Filters vs. opportunities.

Resume screening is purely eliminative. It's designed to reduce candidate pools using criteria that often feel arbitrary.

AI interviews give candidates a chance to showcase their capabilities, explain their background, and make their case. Even if they don't advance, they got to try.

This distinction is critical for product positioning. Candidates will accept—even prefer—AI in the hiring process if it gives them MORE opportunities to prove themselves, not fewer chances.

If your AI interview is just another filter designed to quickly eliminate people, expect resistance. If it's a genuine opportunity for candidates to demonstrate their value, expect acceptance.

The Path Forward: What Good AI Interviews Look Like

Based on this data, here's the blueprint for AI interviews that candidates will actually accept:

The Must-Haves:

Speed: Maximum 48-72 hours for initial feedback. Make this a guarantee, not an aspiration.

Transparency: Clear explanation of what's being evaluated, how scoring works, and what happens to data.

Real feedback: Specific, actionable information candidates can use to improve—regardless of whether they get the job.

Human oversight: AI screens for efficiency, humans review for judgment and make final decisions.

Respect: Acknowledge candidates' time and effort. Treat the interview seriously even if it's automated.

The Competitive Advantages:

Convenience: Let candidates complete interviews on their schedule, accommodating work hours and personal responsibilities.

Second chances: Allow candidates to redo or clarify responses if needed.

Skill demonstration: Focus on showing abilities, not just describing them.

Value beyond hiring: Provide feedback and guidance useful for any job search, not just this specific role.

The Bottom Line: Candidates Are Pragmatists, Not Ideologues

Here's the fundamental insight from this survey: Candidates don't care about AI interviews as a philosophical concept. They care about whether it improves their experience.

The data shows candidates will choose AI interviews if they deliver:

• ✅ Faster feedback instead of weeks of ghosting (47.9% prefer AI with speed)

• ✅ Transparent evaluation instead of mysterious decision-making (60.6% demand this)

• ✅ Fair opportunities to showcase skills instead of resume keyword filtering

• ✅ Convenient scheduling instead of complicated coordination

• ✅ Actual feedback they can learn from instead of generic rejections

But they'll resist—hard—if AI interviews mean:

• ❌ Opaque algorithms with no explanation (lack of transparency is the top concern)

• ❌ Impersonal experiences that miss their full story (49.3% concern)

• ❌ Risk of being misunderstood with no recourse (46.5% concern)

• ❌ Yet another filter eliminating people rather than giving them chances

The technology itself isn't the issue. The experience created by that technology determines acceptance.

And here's the proof: 73% of candidates would do an AI interview for their dream job. When it actually matters, they adapt. The resistance isn't about principles—it's about whether you're delivering value or just automating rejection.

What We're Building at Shortlistd

This survey fundamentally shaped our product strategy at shortlistd.io.

We're building AI interview technology based on what these 71 candidates told us they actually want:

✅ 48-hour feedback guarantee: Every single candidate receives detailed, actionable feedback within 2 days. Zero ghosting. Zero black holes.

✅ Radical transparency: Candidates know exactly what we're evaluating, how scoring works, and what criteria matter. No mystery algorithms.

✅ Opportunity, not filtering: Our AI interviews are designed to give candidates meaningful chances to demonstrate capabilities—not function as another resume screener.

✅ Human-AI collaboration: AI handles initial screening for speed and consistency; humans make final decisions where judgment and cultural fit matter.

✅ Feedback that helps: Whether candidates get the job or not, they receive specific guidance they can use for any application.

We're not trying to replace human judgment. We're trying to fix the genuinely broken parts of recruiting: the ghosting, the opacity, the inefficiency, and the lack of respect for candidates' time and effort.

If you're a company struggling to fill critical roles—or a candidate exhausted by the current hiring process—we'd welcome the conversation.

Join the Conversation and Shape the Future

This survey captured 71 perspectives, but the conversation is just beginning.

If you're a job seeker: What's your experience with AI interviews? What would make you more comfortable with the technology? Your perspective matters—take our ongoing survey or share your thoughts in the comments.

If you're a hiring manager or recruiter: How are you approaching AI in your recruiting process? What concerns are you navigating? What results have you seen? Let's talk—DM me or reach out here.

If you're a company looking to fill roles faster: We're helping companies reduce time-to-hire from months to days while improving candidate experience. Book a demo to see how shortlistd.io can transform your recruiting outcomes.

The future of recruiting isn't AI versus humans. It's leveraging AI to make recruiting more human—with faster feedback, greater transparency, and fairer opportunities for everyone.

The data shows exactly what candidates want. Now let's build it.

About the Author: Adil is the founder of Shortlistd, an AI-powered recruiting platform focused on candidate experience and fair hiring. This article is based on original survey research with 71 job seekers conducted in October 2025.

Methodology Note: This survey was distributed via LinkedIn and online communities, reaching job seekers across industries and experience levels. 71 responses were collected over a 2-week period in October 2025. Respondents were 80.3% in tech/software, with experience levels ranging from 0-2 years (14.1%) to 16+ years (25.4%).

Share this article: If this resonated with you, share it with your network. The more companies understand what candidates actually want, the better recruiting becomes for everyone.

If you're a company looking to fill roles faster: We're helping companies reduce time-to-hire from months to days while improving candidate experience. Book a demo to see how shortlistd.io can transform your recruiting outcomes.