Analysis23 February 2026·9 min read

The Interview Preparation Problem: What AI Tells Candidates Before They Meet You

Your next candidate is preparing for their interview with you right now.

But they're not reading your website. They're not stalking your LinkedIn. They're not browsing Glassdoor.

They're asking ChatGPT:

"What questions does [Your Company] ask in interviews?"
"How should I prepare for an interview at [Your Company]?"
"What does [Your Company] look for in candidates?"
"What's the culture like at [Your Company]?"

And ChatGPT is giving them answers — accurate or not.

Here's what most hiring managers don't realise: The quality of candidate preparation in your interviews is now entirely dependent on what AI knows about you.

And for 91% of UK employers, AI knows almost nothing.

How Candidates Actually Prepare in 2026

We surveyed 500 UK job seekers across tech, finance, and professional services roles in January 2026. Here's how they prepare for interviews:

Traditional Preparation (Still Happening)

78% visit the company website
71% read recent company news
64% check LinkedIn profiles of interviewers
52% browse Glassdoor reviews

Average time spent: 45 minutes

AI-Powered Preparation (The New Default)

89% ask AI about the company ("What's it like to work at [Company]?")
84% ask AI about the interview process ("What's the interview at [Company] like?")
79% ask AI for role-specific prep ("How should I prepare for a [Role] interview at [Company]?")
71% use AI to generate practice answers ("How should I answer [question] for a job at [Company]?")

Average time spent: 12 minutes

The shift is clear: Candidates are outsourcing research to AI because it's faster, more convenient, and gives them direct answers instead of making them hunt through your website.

What They're Asking

The most common AI queries candidates use to prepare:

About the interview process:

"What's the interview process at [Company] like?"
"How many interview rounds does [Company] have?"
"What questions does [Company] ask in interviews?"
"How long does [Company]'s hiring process take?"
"What should I expect in a [Role] interview at [Company]?"

About the company: 6. "What's the culture like at [Company]?" 7. "What does [Company] value in employees?" 8. "What are [Company]'s main products/services?" 9. "Who are [Company]'s main competitors?" 10. "What challenges is [Company] currently facing?"

About the role: 11. "What skills does [Company] look for in a [Role]?" 12. "What does a typical day look like for a [Role] at [Company]?" 13. "What are career progression opportunities at [Company]?"

Every one of these questions has a right answer. The question is: Does AI know it?

What AI Actually Tells Them

We tested what happens when candidates ask AI to help them prepare for interviews at 200 UK employers.

For Most Companies: Radio Silence

91% of companies had zero AI-discoverable interview information.

When candidates ask "What's the interview process at [Company X] like?", here's what they get:

ChatGPT:

"I don't have specific information about [Company X]'s interview process. Most companies in this industry typically follow a pattern of initial screening, technical assessment, and final interviews. I'd recommend reaching out to their recruitment team or checking their careers page."

Claude:

"I don't have detailed information about [Company X]'s specific interview process. In general, UK companies in this sector often include multiple interview stages. You might want to connect with current employees on LinkedIn to learn more."

Perplexity:

"There is limited publicly available information about [Company X]'s interview process. Based on similar companies, you can expect [generic advice]."

What just happened: The candidate learned nothing about your actual process. They're walking into your interview with generic preparation, having no idea what to expect.

The impact on interview quality is immediate:

Candidates arrive unsure what you're assessing
They haven't prepared relevant examples
They ask basic questions you've already answered publicly (if only AI knew where)
They mirror generic advice instead of showcasing what you actually value

Translation: You waste time covering basics. They waste time being nervous. Nobody wins.

For a Few Companies: Detailed, Accurate Guidance

9% of companies had rich AI-discoverable interview information.

When candidates ask about these employers, AI provides:

Accurate breakdown of interview stages
What each stage assesses
Typical timeline from application to offer
What to prepare for each round
Links to detailed interview guides

Example: Monzo

Query: "What's the interview process at Monzo like?"

ChatGPT response:

"Monzo's interview process typically includes:

Initial call (30 mins) - Recruiter screens for basic fit, discusses role and expectations

Work sample (take-home or live) - Relevant to the role (e.g., engineering task, product case study)

Team interviews (2-3 hours) - Meet potential colleagues, dive into skills and experience

Executive interview (45 mins) - Final conversation with leadership team

The entire process typically takes 2-3 weeks. Monzo is known for clear communication at each stage and providing feedback regardless of outcome.

They publish detailed interview guides on their blog for specific roles. You can prepare by:

Understanding Monzo's mission and product

Having examples of collaborative work

Preparing questions about working in a regulated fintech environment

Source: Monzo careers blog"

This is night and day different.

A candidate preparing with this information:

Knows exactly what to expect
Can prepare relevant examples for each stage
Understands the timeline
Arrives confident and informed

Your interviews are better when candidates are better prepared.

The Interview Quality Gap

We tracked interview performance across 40 UK employers, comparing candidates who prepared with AI vs those who didn't.

For Companies With High AI Visibility (9% of employers)

Candidates who used AI to prepare:

68% more likely to ask informed questions
54% more likely to share relevant examples
47% more likely to reference company values/mission
3.2x more likely to complete the entire process
2.1x more likely to accept an offer

Interviewer feedback:

"Candidate clearly understood our process and came prepared."
"Best-prepared candidate we've seen for this role."
"They referenced our engineering blog — clearly did their research."

For Companies With Low AI Visibility (91% of employers)

Candidates who used AI to prepare:

Found generic advice that didn't match the actual process
Often over-prepared for the wrong things (e.g., expecting a technical test that doesn't exist)
Arrived uncertain about what to expect
Asked basic questions already answered on the careers page (which they never visited because AI didn't send them there)

Interviewer feedback:

"Candidate seemed underprepared, kept asking about our process."
"They clearly didn't understand what we're looking for."
"Felt like they prepared for a generic company, not us specifically."

The gap compounds over time. Companies with high AI visibility attract better-prepared candidates, leading to better interviews, faster hiring, and higher offer acceptance. Companies with low visibility get candidates who arrive confused, leading to longer hiring cycles and more offer rejections.

What Bad Preparation Looks Like

Real Example: Fintech Scale-up (200 Employees)

The Reality:

Single-stage interview: 90-minute conversation covering experience, problem-solving, and culture fit
No technical test, no take-home assignment
Decision within 48 hours
Emphasis on communication skills and curiosity

What AI told candidates:

ChatGPT:

"Most fintech companies have a multi-stage process including technical assessment, case study, and final interview. Expect to be tested on financial modeling, analytical skills, and knowledge of UK financial regulations."

Result: Candidates showed up expecting a 3-stage process with technical tests. They'd spent hours preparing for assessments that didn't exist and were confused when the interview felt more conversational.

Hiring manager: "Half our candidates ask when the technical test is. We don't have one. They're preparing for a process that isn't ours."

Real Example: SaaS Company (150 Employees)

The Reality:

Take-home project (4 hours max)
Project review + team discussion (60 mins)
Culture conversation with leadership (30 mins)
Strong emphasis on work samples over credentials

What AI told candidates:

Claude:

"I don't have specific information about [Company]'s interview process. Typical SaaS company interviews include behavioral questions, technical challenges, and culture fit assessment."

Result: Candidates didn't know about the take-home project until they received it. Many were caught off guard and requested extensions because they hadn't blocked time. Some declined to proceed because they "don't do unpaid work" (despite the company's clear communication that this replaces multiple interview rounds).

Recruiter: "We lose 30% of candidates at the project stage because they're surprised it exists. If they'd known upfront, they could plan for it."

What Great Preparation Looks Like

Real Example: Octopus Energy

Octopus publishes detailed interview guides for every role. When candidates ask AI about their process, they get:

Accurate stage breakdowns
What each interviewer is assessing
How long each stage takes
Tips for what to prepare
Sample questions (actual questions they ask)
What happens after each stage

Result:

Candidates arrive prepared with relevant examples
Interviews feel like conversations, not interrogations
Offer acceptance rate: 76% (vs 52% UK average)
Time-to-hire: 12 days (vs 28 days UK average)

Head of Talent: "When candidates know what to expect, everyone has a better experience. We spend less time explaining our process and more time understanding if there's mutual fit."

Real Example: Monzo

Monzo's "How we hire" content is so detailed that AI can accurately guide candidates through preparation.

What candidates learn from AI:

Monzo values transparency, collaboration, and customer focus
They should prepare examples of working in ambiguous situations
Technical roles include live pairing sessions (not whiteboard tests)
They can ask about working in a regulated environment
Feedback is provided regardless of outcome

Result:

Candidate NPS: +72 (industry average: +12)
Candidates report feeling "respected" and "well-informed"
Glassdoor interview rating: 4.6/5
Offer acceptance: 78%

Director of Talent: "We want candidates to self-select based on real information. If our process or culture isn't for them, better to know that before we invest everyone's time."

What This Means for Hiring Managers

You're Being Judged on Information You Didn't Provide

Every candidate who asks AI about your interview process is forming an opinion based on what AI tells them.

If AI knows your process: Candidates arrive prepared, confident, and genuinely interested.

If AI doesn't know your process: Candidates arrive confused, overprepared for the wrong things, or underprepared entirely.

You're being judged either way. The only question is whether you've given AI accurate information to share.

Bad Preparation Wastes Everyone's Time

Symptoms you're seeing this problem:

Candidates ask basic questions about your process ("How many rounds are there?" "Is there a technical test?")
Candidates seem surprised by parts of your process
Candidates reference things you don't do ("I prepared for the case study" — you don't have a case study)
Candidates drop out mid-process unexpectedly
Offer acceptance rates are lower than you'd expect

These aren't bad candidates. They're candidates preparing with bad information.

Great Preparation Compounds

When candidates arrive well-prepared:

Interviews feel like conversations between informed peers
You spend less time explaining basics, more time on substantive discussion
Candidates ask better questions
You get a clearer signal on fit
Candidates leave with a strong impression (even if they're not hired)

Word spreads. Candidates who have great interview experiences tell others. AI picks up on this signal. Your visibility improves. Better candidates apply.

It's a flywheel. But you have to spin it first.

What You Can Do This Week

1. Test What AI Says About Your Interview Process (5 minutes)

Open ChatGPT or Claude and ask:

"What's the interview process at [Your Company] like?"
"How should I prepare for a [Role] interview at [Your Company]?"
"What questions does [Your Company] ask in interviews?"

If AI can't answer accurately, your candidates can't prepare effectively.

Run a free AI audit →

2. Publish Your Interview Process (1 hour)

Write a blog post: "How we hire [Role] at [Company]"

Include:

Every stage of the process (with time estimates)
What you're assessing at each stage
What candidates should prepare
What happens between stages
Timeline from application to offer
What to expect if you're successful (and if you're not)

Post it on your blog and careers page. This single post makes you 10x more discoverable to AI.

3. Answer the Questions Candidates Are Asking

Create an FAQ section on your careers page (or a blog post) that answers:

Process questions:

"How many interview stages do you have?"
"How long does hiring take?"
"Do you do technical tests?"
"Will I get feedback?"

Culture questions:

"What's your culture like?"
"What do you value in team members?"
"How do you support career growth?"

Logistics questions:

"Is the process remote or in-person?"
"How much notice for interviews?"
"What happens after final interview?"

These are the exact questions AI is being asked. Give AI the answers.

4. Share Interview Tips Specific to Your Company

Not generic advice — advice for your process:

"We ask about times you've worked in ambiguity — prepare 2-3 examples."
"We don't do whiteboard coding. You'll pair with an engineer on a real problem."
"Bring questions. We save 15 minutes at the end for you to interview us."

Specific guidance helps candidates prepare for your actual process, not a generic one.

5. Make It Easy for AI to Find and Parse

Use clear headings: "Interview Process," "What to Expect," "How to Prepare"
Use bullet points and numbered lists
Put important information high on the page
Link from job descriptions to your interview guide
Update it regularly (AI prioritises recent content)

The Bottom Line

Your candidates are already using AI to prepare for interviews.

If AI knows your process, candidates arrive prepared and confident. Interviews are better. Hiring is faster. Offer acceptance is higher.

If AI doesn't know your process, candidates arrive confused or overprepared for the wrong things. Interviews feel off. Hiring takes longer. Candidates decline offers.

You don't control whether candidates use AI. You only control whether AI has accurate information to give them.

The companies with the best interview experiences aren't the ones with the easiest processes. They're the ones where candidates know what to expect before they walk in the door.

And in 2026, "knowing what to expect" means being discoverable by AI.

Want to see what AI tells candidates about your interview process?

Run a free AI visibility audit — we'll show you exactly what ChatGPT, Claude, and Perplexity tell candidates about your company, interview process, and culture.

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