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AI Made Every Candidate Look Good. Now What? · Edan Haddock - Total Talent

0:51
SPEAKER_00: Welcome back to Eden Haddock Total Talent.
0:55
SPEAKER_00: I am your host, Eden Haddock, Head of Talent and People Experience at Movember.
1:02
SPEAKER_00: And welcome to day four of 30 days, thirty episodes, one mission.
1:10
SPEAKER_00: Every day this month, I'm releasing a brand new episode to raise money and awareness for Movember and men's health.
1:19
SPEAKER_00: If you're enjoying the series, please donate if you can.
1:23
SPEAKER_00: But also share it.
1:26
SPEAKER_00: Because getting this conversation beyond my own network is how we're going to make this thing really count.
1:35
SPEAKER_00: Right.
1:37
SPEAKER_00: Let's talk about AI again.
1:41
SPEAKER_00: But I want to come at it from a completely different direction today.
1:47
SPEAKER_00: Because we've spent the last couple of years being told that AI is going to make recruiters dramatically more productive.
1:57
SPEAKER_00: It's going to write our ads, source our candidates, screen applications, rank resumes, automate outreach, write emails, take notes, summarize interviews, schedule meetings, do all the administrative crap we don't want to do.
2:25
SPEAKER_00: Fantastic.
2:28
SPEAKER_00: Except I've got a question.
2:32
SPEAKER_00: What if AI has actually made some parts of recruitment less productive?
2:40
SPEAKER_00: Because there's one fairly significant flaw in the story we've been telling ourselves.
2:49
SPEAKER_00: Recruiters aren't the only people with AI, right?
2:54
SPEAKER_00: Candidates have it too.
2:57
SPEAKER_00: And that changes everything.
3:01
SPEAKER_00: The productivity paradox.
3:05
SPEAKER_00: As part of this Movember series, I recently sat down with Glenn Perry from Recruit Wizard.
3:15
SPEAKER_00: Glenn has been around recruitment for about thirty years.
3:19
SPEAKER_00: He's also a fellow Campbelltown boy.
3:23
SPEAKER_00: His professional background is actually accounting and management consulting.
3:29
SPEAKER_00: And he spent years working inside recruitment businesses looking at processes, systems, and productivity.
3:38
SPEAKER_00: Eventually, that journey led to Recruit Wizard.
3:43
SPEAKER_00: And during our conversation, Glenn made a claim that immediately grabbed me.
3:50
SPEAKER_00: His view is that the productivity of the recruitment resourcing function has actually gone backwards since the arrival of generative AI.
4:04
SPEAKER_00: Not forwards, backwards.
4:08
SPEAKER_00: Now that's interesting.
4:11
SPEAKER_00: Because it runs directly against the dominant narrative.
4:17
SPEAKER_00: More technology should equal more productivity.
4:22
SPEAKER_00: More automation should equal more productivity.
4:27
SPEAKER_00: AI should absolutely equal more productivity.
4:33
SPEAKER_00: But what if we're measuring only one side of the equation?
4:39
SPEAKER_00: The candidate's got AI too.
4:43
SPEAKER_00: Think about what applying for a job used to require.
4:49
SPEAKER_00: Find the job.
4:51
SPEAKER_00: Read the advertisement.
4:54
SPEAKER_00: Update your resume.
4:56
SPEAKER_00: Potentially write a cover letter, more often than not.
5:00
SPEAKER_00: Complete an application, submit it.
5:04
SPEAKER_00: And then do it again.
5:07
SPEAKER_00: And again.
5:09
SPEAKER_00: And again.
5:11
SPEAKER_00: There was friction.
5:14
SPEAKER_00: Now AI can help identify jobs now.
5:20
SPEAKER_00: It can compare your resume against the job description.
5:25
SPEAKER_00: It can rewrite the resume.
5:28
SPEAKER_00: It can generate the cover letter.
5:32
SPEAKER_00: It can answer application questions.
5:36
SPEAKER_00: And increasingly, tools can automate more of the application process itself.
5:45
SPEAKER_00: From the candidate's perspective, that's incredible.
5:52
SPEAKER_00: The cost of applying for another job has collapsed.
5:57
SPEAKER_00: But what happens at the other end?
6:01
SPEAKER_00: Recruitment gets the volume.
6:06
SPEAKER_00: Instead of a hundred applications, maybe you get hundreds, and volume isn't even the most interesting part.
6:15
SPEAKER_00: Because those applications can also look better.
6:22
SPEAKER_00: Everybody looks like a match.
6:26
SPEAKER_00: This is where Glenn made a point.
6:27
SPEAKER_00: I think every talent professional needs to think about.
6:32
SPEAKER_00: Historically, only a relatively small number of candidates would painstakingly tailor their resume for every application.
6:42
SPEAKER_00: And if somebody had really taken the time to understand the role, reposition their experience, and carefully present the relevant information, then that told you something.
6:57
SPEAKER_00: There was intent in it, care, attention, effort.
7:05
SPEAKER_00: Today, anyone can do that in seconds.
7:10
SPEAKER_00: Copy job description, upload resume, ask AI, rewrite my resume to make me look like a stronger match for this role.
7:22
SPEAKER_00: And that's done.
7:25
SPEAKER_00: And I'm not criticizing candidates for doing that.
7:29
SPEAKER_00: Of course they're going to use the tools available to them.
7:33
SPEAKER_00: Recruiters certainly are.
7:50
SPEAKER_00: Against the job description, the resume was optimized against.
7:56
SPEAKER_00: What do we think is going to happen?
8:00
SPEAKER_00: Glenn used a brilliant analogy.
8:03
SPEAKER_00: It's like giving students the answers to a test.
8:07
SPEAKER_00: And then being surprised when everybody gets an A.
8:13
SPEAKER_00: Of course the match score is high.
8:16
SPEAKER_00: We've potentially created an optimization loop.
8:21
SPEAKER_00: AI optimizes the application.
8:25
SPEAKER_00: AI evaluates the optimization.
8:29
SPEAKER_00: And the recruiter receives a beautifully ranked list of candidates who all look fantastic until you speak to them.
8:44
SPEAKER_00: The screening call from hell.
8:48
SPEAKER_00: I think most recruiters have experienced some version of this already.
8:53
SPEAKER_00: You open the resume, looks good.
8:57
SPEAKER_00: Skills line up.
8:59
SPEAKER_00: Experience looks relevant.
9:01
SPEAKER_00: Keywords are there.
9:04
SPEAKER_00: Maybe the application is beautifully written.
9:07
SPEAKER_00: Great.
9:08
SPEAKER_00: Pick up the phone.
9:11
SPEAKER_00: So tell me about your experience using Java.
9:15
SPEAKER_00: Silence.
9:16
SPEAKER_00: I don't have Java experience.
9:20
SPEAKER_00: But it's on your resume.
9:24
SPEAKER_00: Or you move into the interview and suddenly the depth that appeared to exist on paper isn't there.
9:34
SPEAKER_00: Or worse, you're conducting the interview and watching someone's eyes move towards another screen while an AI tool helps construct the answer they're about to give you.
9:49
SPEAKER_00: And now the recruiter has another job.
9:53
SPEAKER_00: We're no longer simply assessing candidates.
9:57
SPEAKER_00: We're trying to establish what's real.
10:02
SPEAKER_00: That's the productivity paradox.
10:06
SPEAKER_00: AI made it easier to create the information.
10:11
SPEAKER_00: AI made it easier to distribute the information.
10:16
SPEAKER_00: AI made it easier to evaluate the information.
10:20
SPEAKER_00: But if trust in the information fails, humans have to spend more time validating it.
10:31
SPEAKER_00: We've created AI pollution.
10:34
SPEAKER_00: Glenn calls this AI pollution, and I like that phrase.
10:40
SPEAKER_00: Because we're drowning in content, emails, messages, outreach, applications, CVs, profiles, automatically generated communication.
10:58
SPEAKER_00: Everyone can create more.
11:05
SPEAKER_00: Everyone can apply more.
11:08
SPEAKER_00: Everyone can personalize more.
11:13
SPEAKER_00: But more isn't automatically better.
11:18
SPEAKER_00: In fact, when everybody can create infinite amounts of apparently personalized content, the value of the content itself starts to fail.
11:31
SPEAKER_00: Look at your inbox.
11:33
SPEAKER_00: How many beautifully written sales emails do you delete every morning without even properly reading them, right?
11:42
SPEAKER_00: They're probably grammatically perfect.
11:46
SPEAKER_00: They probably mention your company, your job title, something you posted on LinkedIn.
11:54
SPEAKER_00: Maybe they congratulate you on something.
11:58
SPEAKER_00: And you can still smell the automation from twenty meters away.
12:05
SPEAKER_00: For me, delete, delete, delete, delete.
12:11
SPEAKER_00: AI solved the problem of creating communication at scale, then created a completely new problem.
12:21
SPEAKER_00: Nobody wants to read it.
12:25
SPEAKER_00: Recruitment applications could be heading in exactly the same direction.
12:32
SPEAKER_00: So the CV is becoming less trustworthy.
12:37
SPEAKER_00: And I think this creates a much bigger talent question.
12:42
SPEAKER_00: What is a resume actually worth in an AI world?
12:48
SPEAKER_00: I've talked previously on this podcast about validating experience, about whether candidates can bluff their way through recruitment processes, about authenticity.
13:05
SPEAKER_00: This feels like another evolution of that conversation.
13:10
SPEAKER_00: Because the resume has historically been treated as evidence.
13:15
SPEAKER_00: The candidate says, I did this, I know this, I achieved this, I worked here, I have these capabilities.
13:27
SPEAKER_00: And we use that self-reported information to determine whether they're worth investigating.
13:35
SPEAKER_00: But now that information can be restructured, reframed, expanded, optimized almost instantly.
13:49
SPEAKER_00: Again, AI isn't necessarily inventing experience.
13:54
SPEAKER_00: Used appropriately, it may simply help someone communicate their genuine experience much better.
14:03
SPEAKER_00: That's completely legitimate.
14:06
SPEAKER_00: But it does mean the recruiter needs additional signals.
14:11
SPEAKER_00: Because the document alone is becoming less useful as evidence.
14:18
SPEAKER_00: And that's where Glenn and Recruit Wizard went somewhere I found really interesting.
14:26
SPEAKER_00: What does your organization already know?
14:31
SPEAKER_00: Recruit Wizard has built something it calls the talent index.
14:37
SPEAKER_00: At a high level, it's an AI evaluation engine.
14:43
SPEAKER_00: And there's nothing particularly revolutionary about that statement.
14:48
SPEAKER_00: Lots of platforms can evaluate a candidate against a job.
14:53
SPEAKER_00: But the bit I found interesting is what Recruit Wizard puts into that evaluation.
15:00
SPEAKER_00: Glenn explained it to me roughly as two components.
15:06
SPEAKER_00: Around seventy percent relates to the candidate information and how that aligns with the requirements of the role.
15:15
SPEAKER_00: Then there's another component.
15:18
SPEAKER_00: What Recruit Wizard calls organizational intelligence.
15:25
SPEAKER_00: In other words, what does your organization already know about this human?
15:34
SPEAKER_00: Have you spoken to them before?
15:37
SPEAKER_00: Have you shortlisted them?
15:41
SPEAKER_00: Have you previously submitted them to a hiring manager or a client?
15:46
SPEAKER_00: Have they been interviewed?
15:49
SPEAKER_00: Have you placed or hired them before?
15:53
SPEAKER_00: What notes exist?
15:55
SPEAKER_00: What conversations have happened?
15:59
SPEAKER_00: What email history exists?
16:03
SPEAKER_00: What previous signals has your organization gathered?
16:08
SPEAKER_00: None of those things individually prove somebody is a great candidate, and Glenn was very clear about that.
16:17
SPEAKER_00: They're indicators.
16:19
SPEAKER_00: But think about the difference.
16:22
SPEAKER_00: I've got two regimes.
16:25
SPEAKER_00: On paper, they're both excellent.
16:28
SPEAKER_00: AI tells me they are both strong matches.
16:32
SPEAKER_00: Candidate A has never interacted with my organization before.
16:38
SPEAKER_00: Candidate B has previously been shortlisted three times, interviewed twice, and successfully placed once.
16:48
SPEAKER_00: They might be my talent community.
16:52
SPEAKER_00: So who might I want to investigate first?
16:55
SPEAKER_00: Simple.
16:57
SPEAKER_00: Probably candidate B.
16:59
SPEAKER_00: Not automatically hire them, not automatically progress them, but perhaps look at them first.
17:09
SPEAKER_00: That's a very different use of AI.
17:14
SPEAKER_00: Your database knows more than you think.
17:19
SPEAKER_00: This gets into another enormous recruitment problem.
17:24
SPEAKER_00: The dead database.
17:27
SPEAKER_00: Every recruiter knows this one.
17:30
SPEAKER_00: You build a database, thousands of candidates, tens of thousands, hundreds of thousands, maybe millions.
17:41
SPEAKER_00: Now that looks impressive on a PowerPoint slide.
17:44
SPEAKER_00: Our talent database contains four hundred thousand candidates.
17:48
SPEAKER_00: Great.
17:51
SPEAKER_00: How many can you actually recruit today?
17:57
SPEAKER_00: Because candidate data ages ridiculously quickly.
18:02
SPEAKER_00: Someone applies five years ago as a help desk analyst.
18:07
SPEAKER_00: Today they're a project manager.
18:10
SPEAKER_00: But your database still thinks they're on the help desk.
18:14
SPEAKER_00: So when you search for project managers, they don't exist.
18:18
SPEAKER_00: They're in there, but effectively invisible.
18:23
SPEAKER_00: And then we often do something slightly ridiculous.
18:28
SPEAKER_00: And in some ways, no matter how we source, we do.
18:32
SPEAKER_00: We pay to find them again.
18:37
SPEAKER_00: We keep buying the same candidates.
18:39
SPEAKER_00: Think about this.
18:41
SPEAKER_00: Someone applies to your organization, you capture their details, maybe interview them, maybe nearly hire them.
18:52
SPEAKER_00: Maybe they're fantastic, but somebody else was marginally better.
18:59
SPEAKER_00: Two years later, you've got another perfect role for them.
19:04
SPEAKER_00: But your database is stale.
19:07
SPEAKER_00: So what do you do?
19:09
SPEAKER_00: Advertise.
19:11
SPEAKER_00: Pay the job board.
19:13
SPEAKER_00: Run sourcing campaigns.
19:16
SPEAKER_00: Maybe pay LinkedIn.
19:18
SPEAKER_00: Maybe engage an agency.
19:21
SPEAKER_00: Maybe spend recruiter hours searching externally.
19:26
SPEAKER_00: And eventually the same bloody person applies again.
19:32
SPEAKER_00: We've effectively paid to reacquire a candidate we already know.
19:37
SPEAKER_00: That's insane.
19:40
SPEAKER_00: And yet it happens constantly.
19:44
SPEAKER_00: Glenn's original obsession when building the technology that eventually became Recruit Wizard was essentially this problem.
19:54
SPEAKER_00: Recruiters spend enormous amounts of time sourcing.
19:59
SPEAKER_00: Recruitment businesses spend enormous amounts of money on advertising.
20:05
SPEAKER_00: So if you can make sourcing materially more productive, you attack both costs.
20:13
SPEAKER_00: And that's smart.
20:17
SPEAKER_00: The candidate exchange, and this is where Recruit Wizard has an unusual piece of technology sitting underneath it.
20:25
SPEAKER_00: The candidate exchange.
20:29
SPEAKER_00: The principle Glenn described is essentially collaborative candidate data.
20:35
SPEAKER_00: Across Recruit Wizard customers, candidate information can be aggregated so that where newer information about an existing candidate becomes available through participating organizations, the central candidate profile can reflect more current information.
20:58
SPEAKER_00: So imagine I interacted with you years ago.
21:02
SPEAKER_00: My information is stale.
21:05
SPEAKER_00: Another participating organization has interacted with you more recently.
21:12
SPEAKER_00: The candidate exchange can help surface the more current candidate information.
21:19
SPEAKER_00: Now, there's an important philosophical trade-off here.
21:24
SPEAKER_00: Glenn openly acknowledges that you're contributing data into an ecosystem your competitors may benefit from.
21:33
SPEAKER_00: But they're contributing to.
21:37
SPEAKER_00: His description was effectively put one in, get three or four back.
21:44
SPEAKER_00: The objective is that activity across the wider market helps keep candidate information alive rather than every individual database slowly decaying in isolation.
22:00
SPEAKER_00: Wow, it's a fascinating idea.
22:04
SPEAKER_00: And obviously, for any organization looking at a model involving candidate data sharing, I'd want to properly understand the privacy, consent, governance, and data handling arrangements before adopting it.
22:21
SPEAKER_00: That's important, right?
22:23
SPEAKER_00: But conceptually, there's something interesting here.
22:29
SPEAKER_00: Because we're talking endlessly about AI finding candidates.
22:36
SPEAKER_00: Maybe we should first ask why our existing technology forgot them in the first place.
22:46
SPEAKER_00: Your database shouldn't be a graveyard.
22:50
SPEAKER_00: Glenn described the ambition as turning the database from a graveyard into a living, breathing entity.
23:01
SPEAKER_00: I love that.
23:05
SPEAKER_00: Because we've spent years accepting database decay as inevitable.
23:11
SPEAKER_00: Candidates come in.
23:13
SPEAKER_00: We use them for the immediate recruitment process.
23:19
SPEAKER_00: Then most disappear into the ATS abyss.
23:24
SPEAKER_00: And six months later, stale.
23:28
SPEAKER_00: Twelve months, staler.
23:31
SPEAKER_00: Three years, it's an artifact.
23:35
SPEAKER_00: Archaeological artifact.
23:38
SPEAKER_00: Then we go back out to the external market and start again.
23:45
SPEAKER_00: That's not really talent intelligence.
23:48
SPEAKER_00: It's transactional recruitment with storage.
23:53
SPEAKER_00: A genuinely intelligent talent system should get more valuable as you use it.
24:02
SPEAKER_00: Think about that.
24:04
SPEAKER_00: Every interview, every short list, every candidate conversation, every hiring manager interaction, every placement, every hire, every note, every outcome, that should increase your organizational intelligence.
24:30
SPEAKER_00: Instead, in many organizations, enormous amounts of that information either aren't captured or they're captured and never meaningfully used again.
24:47
SPEAKER_00: The path of least resistance.
24:50
SPEAKER_00: This was another part of the recruit wizard conversation that I really liked.
24:57
SPEAKER_00: Glenn told me about a customer who had struggled for years to get recruiters to keep their CRM properly updated.
25:06
SPEAKER_00: Anyone who's led a recruitment team knows this battle.
25:10
SPEAKER_00: Please update the ATS.
25:13
SPEAKER_00: Please add your notes.
25:15
SPEAKER_00: Please move the candidate.
25:17
SPEAKER_00: Please recall record the interview.
25:20
SPEAKER_00: Please log the call.
25:22
SPEAKER_00: Please update the status.
25:26
SPEAKER_00: And eventually managers start blaming recruiters for poor system compliance.
25:33
SPEAKER_00: But Glenn's philosophy is recruiters will take the path of least resistance.
25:40
SPEAKER_00: I completely agree.
25:43
SPEAKER_00: If doing something outside the system is easier, they'll do it outside the system.
25:51
SPEAKER_00: Then you're asking them to duplicate the work by coming back later and documenting it.
25:58
SPEAKER_00: Of course, compliance is shit.
26:01
SPEAKER_00: You've designed a shit workflow.
26:04
SPEAKER_00: If booking an interview inside the platform automatically sends invitations, updates the candidate stage, and captures the activity, then using the system becomes the easiest way to do the job.
26:22
SPEAKER_00: Add AI note-taking that can record, transcribe, and summarize meetings into the workflow.
26:30
SPEAKER_00: And you're not asking the recruiter to become more administratively disciplined.
26:37
SPEAKER_00: You're removing the reason they avoided the system in the first place.
26:42
SPEAKER_00: That's good technology design.
26:48
SPEAKER_00: So AI versus automation.
26:51
SPEAKER_00: Glenn also made another distinction.
26:54
SPEAKER_00: I think we desperately need in HR technology.
26:58
SPEAKER_00: Not everything is AI, right?
27:02
SPEAKER_00: Some things are just automation.
27:05
SPEAKER_00: And that's okay.
27:07
SPEAKER_00: Automation is bloody useful.
27:10
SPEAKER_00: A system automatically moving a candidate to interview stage after you schedule an interview isn't necessarily some breathtaking artificial intelligence breakthrough.
27:22
SPEAKER_00: It's just simply good workflow automation.
27:27
SPEAKER_00: And we should stop pretending technology only has value if we stick AI on the box.
27:36
SPEAKER_00: I think the market has become slightly addicted to the label.
27:41
SPEAKER_00: AI powered, AI enabled, AI first, AI native.
27:49
SPEAKER_00: Great.
27:52
SPEAKER_00: But what does it actually do?
27:55
SPEAKER_00: What problem disappears?
27:59
SPEAKER_00: What becomes faster?
28:01
SPEAKER_00: What becomes better?
28:04
SPEAKER_00: What decision improves?
28:08
SPEAKER_00: What manual work goes away?
28:10
SPEAKER_00: That's what I care about.
28:13
SPEAKER_00: I don't care whether the answer is AI, automation, workflow design, or a really well designed button.
28:23
SPEAKER_00: Solve the problem.
28:27
SPEAKER_00: So is it one platform or a hundred add-ons?
28:31
SPEAKER_00: Recruit Wizards' broader proposition is a web-based CRM, an ATS, built specifically around recruitment.
28:42
SPEAKER_00: It began with candidate sourcing and eventually expanded into the broader recruitment workflow.
28:51
SPEAKER_00: Today that includes things like requisition management for internal teams, approval workflows, agency vendor management, interview scheduling, AI note-taking, digital reference checks, and a range of other recruitment functionality.
29:13
SPEAKER_00: Glenn's philosophy is to build as much of that capability natively into the platform as practical.
29:22
SPEAKER_00: Because there is another problem emerging in HR Tech, and that's tool sprawl.
29:29
SPEAKER_00: You've got your ATS, then sourcing, then scheduling, then reference checking, then interview intelligence, then note taking, then automation, then assessment, then another AI tool, then another dashboard connecting all the tools.
29:50
SPEAKER_00: Eventually the recruiter needs a map just to remember where they're supposed to work.
29:55
SPEAKER_00: Integrations absolutely have a place.
29:59
SPEAKER_00: Best of breed technology absolutely has a place.
30:04
SPEAKER_00: But there's also value in asking whether adding another platform genuinely improves the recruiter experience.
30:14
SPEAKER_00: Because every new tool creates another workflow, another login, another data relationship, another integration, another cost, another potential place for information to disappear.
30:32
SPEAKER_00: Sometimes is valuable too.
30:37
SPEAKER_00: So here's where I land after spending time with Glenn and looking under the bonnet of Recruit Wizard.
30:46
SPEAKER_00: The thing that interested me most wasn't actually the ATS functionality.
30:52
SPEAKER_00: It was the philosophy around data.
30:56
SPEAKER_00: Because recruitment has spent an enormous amount of time obsessing over acquiring more candidates, more applications, more sourcing, more outreach, more traffic.
31:12
SPEAKER_00: But perhaps one of the biggest productivity opportunities is sitting inside the information we've already collected.
31:22
SPEAKER_00: The candidate we spoke to two years ago.
31:25
SPEAKER_00: The silver medalist from the last process.
31:29
SPEAKER_00: The person a hiring manager loved but couldn't hire.
31:53
SPEAKER_00: That's organizational intelligence.
31:57
SPEAKER_00: And as AI makes self-reported candidate information easier to manufacture, optimize, and distribute, I think historical organizational knowledge becomes more valuable.
32:14
SPEAKER_00: Not because history should determine someone's future, it absolutely shouldn't.
32:20
SPEAKER_00: But because context gives us another signal.
32:26
SPEAKER_00: And recruitment is ultimately about combining signals to make better decisions.
32:35
SPEAKER_00: Human intelligence might be the next big thing.
32:39
SPEAKER_00: Here's the irony.
32:41
SPEAKER_00: We've spent billions trying to build artificial intelligence.
32:45
SPEAKER_00: We are spending billions.
32:47
SPEAKER_00: It continues.
32:50
SPEAKER_00: While enormous amounts of human intelligence are already sitting unused inside our organizations.
33:00
SPEAKER_00: Recruiters have spoken to these people.
33:04
SPEAKER_00: Hiring managers have met them.
33:06
SPEAKER_00: Teams have interviewed them.
33:09
SPEAKER_00: Someone wrote notes.
33:11
SPEAKER_00: Someone formed an opinion.
33:13
SPEAKER_00: Someone made a decision.
33:16
SPEAKER_00: Someone hired them.
33:18
SPEAKER_00: Someone worked with them.
33:21
SPEAKER_00: Then we buried all of that inside a database.
33:25
SPEAKER_00: And we went back to LinkedIn.
33:28
SPEAKER_00: Maybe the next breakthrough isn't generating more information.
33:32
SPEAKER_00: Maybe it's actually remembering what we already know.
33:37
SPEAKER_00: Because we're entering a world where generating information is almost free.
33:44
SPEAKER_00: The scarce commodity becomes trust, evidence, context, history, human judgment, and truth.
33:57
SPEAKER_00: So what now?
33:59
SPEAKER_00: AI isn't going away, nor should it.
34:02
SPEAKER_00: I'm using it, you're using it.
34:04
SPEAKER_00: Candidates are using it, recruit wizard is using it, everybody is using it.
34:09
SPEAKER_00: The question isn't whether AI belongs in recruitment.
34:13
SPEAKER_00: That argument is finished.
34:15
SPEAKER_00: The more interesting question is: what happens when everybody has it?
34:21
SPEAKER_00: When every candidate can produce a beautiful, brilliant resume, then what becomes valuable?
34:29
SPEAKER_00: When everyone can send personalized outreach, what creates cut through?
34:36
SPEAKER_00: When everyone can generate an answer, how do we establish understanding?
34:42
SPEAKER_00: When AI can evaluate AI-generated content, what other evidence do we need?
34:51
SPEAKER_00: Maybe recruitment's next competitive advantage isn't more artificial intelligence.
34:57
SPEAKER_00: Maybe it's better organizational intelligence.
35:01
SPEAKER_00: And perhaps something even considerably more older.
35:06
SPEAKER_00: Human intelligence.
35:09
SPEAKER_00: Knowing people, remembering conversations, understanding context, using judgment, and actually knowing what the hell is inside the database you've spent 20 years building.
35:25
SPEAKER_00: A huge thank you to Glenn Perry for giving me such an open look at Recruit Wizard, and more importantly, challenging some of my thinking about AI and recruitment productivity.
35:39
SPEAKER_00: Recruit Wizard hasn't paid to be featured.
35:41
SPEAKER_00: This isn't sponsored content.
35:43
SPEAKER_00: Glenn gave me his time, showed me the thinking behind the platform, and trusted me to take it away and form my own view.
35:53
SPEAKER_00: And that's exactly what this 30-day series is about.
35:56
SPEAKER_00: So four episodes down, 26 to go.
36:01
SPEAKER_00: If this episode made you rethink how you're using AI, your ATS, or that enormous candidate database sitting inside your organization, do something with it.
36:13
SPEAKER_00: Share the episode with your talent team.
36:16
SPEAKER_00: Share it with a recruiter.
36:18
SPEAKER_00: Share it with somebody currently shopping for their 17th AI recruitment tool.
36:24
SPEAKER_00: And while you're there, please support November.
36:27
SPEAKER_00: Donate if you can.
36:29
SPEAKER_00: Then ask someone else to donate too.
36:32
SPEAKER_00: Because the success of this campaign isn't going to be measured by how many episodes I can record.
36:40
SPEAKER_00: I've already committed to 30.
36:43
SPEAKER_00: It's going to be measured by what this community can do with them.
36:47
SPEAKER_00: 30 days, 30 episodes, one mission.
36:52
SPEAKER_00: I'm Eden Haddock.
36:54
SPEAKER_00: This is Eden Haddock Total Talent.
36:57
SPEAKER_00: And tomorrow we go again.