Welcome to The Hero 🗞️. This is approximately a 3-minute read.

Check it out 👉 https://superrecruiter.io/

AI voice interview bots have already conducted millions of interviews.

In fact, 78% of candidates chose AI over human interviewers when given the option 🤯

Companies cut time-to-hire by ~33%.

But…

Here’s the catch:

Elite candidates are hanging up.

Here's the breakdown 👇

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One study tested an AI interviewer on 70,000 real applicants.

Candidates moved faster, and 78% of candidates are choosing AI over a humans.

While AI screening is nowhere near perfect today, the trajectory is clear -

Initial candidate vetting will be fully automated within the next few years.

Here are some of the best links I’ve found since last time I emailed you: 

Hiring Managers Confirmed These Salary Negotiation Strategies Always Work (link)

5 Ways to Increase Your Job Offer Acceptance Rates Among Gen Z (link)

A Proactive Talent Pipeline: How to Master Talent Pipeline Development (link)

What Is a Talent Pipeline? 101 Guide To Building a Robust Pipeline (link) 

How to Use AI Recruitment Tools to Source Passive Candidates (link)

7 Ways to Engage Passive Candidates on Social Media (link)

Brands like UPS, 7-Eleven, Sephora use AI to fill roles in 3-5 days instead of 30-45.

Why?

Speed and scale.

AI handles thousands of screens simultaneously.

1. Speed: AI interviews cut time-to-hire by 33% - 24/7 availability

2. Consistency: Reports of perceived gender discrimination dropped 50% when AI led interviews.

3. Better Outcomes: Candidates interviewed by AI were 12% more likely to get offers and 17% more likely to stay 30+ days.

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1. Lack of Human Judgment: 44% of people prefer the human touch in hiring.

2. Candidate Drop-Off: 66% of Americans would avoid applying to jobs using AI in hiring decisions.

3. Black Box Scoring: Candidates don't know why the AI rejected them, eroding trust.

4. Bias Still Exists: If trained on biased data, AI replicates that bias.

NYC Local Law 144: Requires annual bias audits, public results, 10-day candidate notice.

Bottom line: Audit your AI.

Don't just flip a switch.

Run a 30-day pilot on one high-volume role.

Customer service reps, retail associates, warehouse workers, SDRs/BDRs, entry-level support roles.

Why they work: High applicant volume, clear knockout criteria, candidates expect fast processes.

Mid-level ICs, junior engineers, account managers.

Why caution: Mixed candidate expectations. Always offer a human alternative.

Senior engineers, directors/VPs, executive roles, specialized/niche experts.

Why not: These candidates have options.

A bot-first process will tank your employer brand and kill acceptance rates.

Week 1: Pick one high-volume role.

Set up a trial.

Go through the AI interview yourself.

Write candidate-friendly disclosure language.

Week 2: Split applicants: 50% AI, 50% human screen.

Track completion rates, time-to-schedule, drop-off.

Week 3: Survey candidates from both groups.

Get hiring manager feedback on quality.

Week 4: Run demographic analysis (any bias patterns?).

Calculate time/cost savings.

The future is clear -

AI will handle the bulk of initial screening whether you’re ready for it or not.

Deploying it recklessly will cost you elite candidates + could land you in legal hot water.

Try it.

Test it.

But adopt it slowly.

AI interview bots excel at speed, scale, and consistency. 

Just be smart with the way you roll it out…

There are a few ways:

Or you can just reply to this email.

I reply to absolutely everyone who writes me back 🙂