Dispelling the myths: How job seekers are actually using AI

[00:00:13] Welcome to Episode 81 of the Inside Job Boards and Recruitment Marketplaces podcast. I am Stephen Rothberg, I am one of the co-hosts and I'm flying solo today. Peter's Unavailable for today's show unfortunately but should be back in the next episode or two.

[00:00:29] Today we are going to be talking about artificial intelligence, AI for the cool kids with our guests Tom Wood from The Hub.

[00:00:39] Tom, before we dive into the conversation maybe tell people a little bit about who you are, where you live, the hub.

[00:00:47] I know you've got about 48 different company names going so maybe like tell us kind of how those all fit together too.

[00:00:53] Yeah, no, I'm going to be here and I'm really pleased to be talking about this. It says it's a long topic.

[00:00:59] So I mean the UK, I've just north of London, I've been in Recruitment for 23, 24 years.

[00:01:06] They're working a group in companies, X-Tid Recruitment Companies, my own business is our people's businesses.

[00:01:11] We've pivoted my wife and I in 22 we saw the challenges, the job searches, we saw the challenges for hiring companies.

[00:01:20] And often many years of being in Recruitment we felt it was time to try and improve some of the processes.

[00:01:26] And that coincided with AI. So there's some of the companies you're seeing, the hub is our job search port platform.

[00:01:33] It's an intelligent AI platform that combines real people, real guidance, real knowledge alongside intelligent AI.

[00:01:41] So that's our job search platform. We think of Recruitment Companies that are still kind of running EDC or those EDGs to Tom Wood coaching.

[00:01:48] There's some kind of old businesses that will kind of just Peter away if you like.

[00:01:53] The focus brush right now is the hub, ED Hub which is the pair of company.

[00:01:58] And ultimately our goal is to enable job searches to get hired quicker and easier over-combo challenges, utilize AI the right way.

[00:02:07] And then along the journey we'll start to help hire in companies, AHE to accept it. We want to improve the processes.

[00:02:12] So it sounds like a lot of sort of the main business if you will is focused on helping the job seeker.

[00:02:19] Like that's your primary focus, it's primarily candidate focus. So are the job seekers, your clients then?

[00:02:26] Do they get a peer-use for a sit-pins tour?

[00:02:28] It's all in 22 was this shift in the job market where suddenly job searches were struggling to get hired.

[00:02:35] And yeah, I think that the pivotal moment for that was co-list, the pivotal moment for that was remote working

[00:02:40] and then on the side of the town of Paul's became much bigger. And the choice was much bigger.

[00:02:44] So if you look at the USP if you like to wear I am, I mean London or not a London.

[00:02:49] I would typically apply for a job that is a commutable distance to wear on located.

[00:02:54] That was going to part my USP. You know, I was suddenly the best person within a commutable distance.

[00:03:00] You open that up to nationwide. I'm not that attractive anymore. I'm not the best person in that region.

[00:03:05] You're way for a disagreement. She would say you are very attractive.

[00:03:09] You might not.

[00:03:11] It's like we've been getting on that all the way to Paul's attention.

[00:03:15] And that's the problem. So suddenly, the USP has gone from an iron company's perspective. That's made it harder because the choice is so wide.

[00:03:23] So challenges came in. 22 we saw this and we saw this increase of time to get hired.

[00:03:27] I think post-COVID it went from four weeks, I was sort of three-covid stories. Post-COVID it went two about three months.

[00:03:34] We're now skating at about nine months on average globally for people to get hired.

[00:03:39] And it's climbing. So we saw this and we went right, we need to fix this.

[00:03:44] And there's a knock on effect to that. You know, mental health, there's our T-s, there's drug addiction, our addiction, homelessness, suicide, all of this is on the up.

[00:03:53] Yeah, absolutely.

[00:03:54] So one point of clarification, and then I want definitely want to dig in more into the AI piece of it. What you're seeing, what you're telling,

[00:04:04] and it's employers whatever.

[00:04:05] When you said that it went from, I think he said like, or weeks to a couple of months, is that from the start of when somebody says,

[00:04:13] I'm going to look for a new job until they actually start with rare exceptions.

[00:04:19] I don't think I've ever heard of it in employer taking nine months from the date of receiving an application of testosterone.

[00:04:25] It's here's a security clearance or you're hiring a CFO, sure.

[00:04:30] But if you're hiring somebody to like make sandwiches, that's measured in days or weeks.

[00:04:36] We're talking about the job search, generally. So we're not talking about a specific hiring company's journey.

[00:04:41] So we're talking about the job search.

[00:04:42] So from the job search, just saying, I'm going to now go and get a job or from somebody being made redundant.

[00:04:49] Yeah. That line for them to secure a new role is now globally.

[00:04:56] The average is, is nine months plus.

[00:04:58] And that's quite a fright in statistics because lots of people, they can't afford to be unemployed, it's about love.

[00:05:05] Yeah, even at all, when most people quite literally are leading, living paycheck to paycheck,

[00:05:10] and they're only a couple of paychecks away from being homeless, you ask somebody to take nine months.

[00:05:16] It's devastating.

[00:05:18] So if that's a really frightening story, people losing their homes, people losing their families.

[00:05:23] One lady that I was talking to was living in her car in California.

[00:05:29] We're in this period now, I think, where people haven't paid enough attention to this growing problem.

[00:05:36] And it's still growing. I mean, it's used in context before we go into some of the specifics.

[00:05:41] In the US, for example, the US has about 30-80 to 40 million people that are open to work at any one time.

[00:05:50] Sure.

[00:05:51] Unlinked in, so, only 10 is about 30-80, 40 million people open to work at any one time.

[00:05:55] There's five million open vacancies in America, only 10.

[00:06:00] So you look at that and you kind of go, there's just not enough jobs for the amount of people that are now out of work.

[00:06:06] But the UK is very similar to the UK. There's five million people open to work.

[00:06:11] There's 900,000 jobs on LinkedIn.

[00:06:15] So you only have to look at that as one platform to go, there's a problem here.

[00:06:19] You know, about the occasion in the levels and now anywhere between 500 and 1,000 jobs.

[00:06:24] So this huge problems and those problems, you can overcome them. Those problems are fixable.

[00:06:30] But it's about education because the job searcher typically is still operating the same as they did pre-COVID.

[00:06:39] They're still applying to jobs, they're still uploading the resumes, they're still hitting easier by things that would have worked pre-COVID on working now.

[00:06:49] Yeah, or even in that year or so coming out of COVID, right when employers couldn't hire quickly enough.

[00:06:55] So you mentioned the hundreds of applications per job.

[00:06:58] How much of that time is attributable to AI?

[00:07:03] Because what we see in the media, what we hear from employers, what some John boards definitely talk about,

[00:07:11] is that there's a massive number of job applications being generated through bots.

[00:07:18] Some of which are AI, some of which are not.

[00:07:21] But I think people sort of generalize and say it's all AI.

[00:07:24] But whether it's AI, whether it's bots, what are you seeing?

[00:07:28] Is there a lot of applications being generated by AI?

[00:07:34] But it's still kind of unusual.

[00:07:36] Like the vast majority of them are manual or do you think a lot of the increased numbers like the majority?

[00:07:42] That's AI.

[00:07:43] Like, where do you think we're at today?

[00:07:46] If we think about the application process, you've got two avenues.

[00:07:49] You've got the real person who is applying.

[00:07:54] You also think that AI systems that are applying on people's behalf.

[00:07:59] Now, yeah, both of those, the increases the cause of AI.

[00:08:04] So if we take the real person and we take the link to it as an example,

[00:08:09] link to the creative, easier apply.

[00:08:12] Now, all you need to do is a very, very basic application structure.

[00:08:17] Because all it does is it will provide a job.

[00:08:20] The easier play element will take your details, take your link to in profile.

[00:08:25] You've probably uploaded a studio at some point in your history.

[00:08:28] The link to the lighting create one from your link to and you just press a button off it goes.

[00:08:32] Yeah.

[00:08:32] That's an element of AI in terms of it simplifying that process.

[00:08:37] So that's become really easy for people to do.

[00:08:41] And I talk about this a lot.

[00:08:43] People go home in an evening, finish work or whatever.

[00:08:46] And then you're done, kids are gone to bed, glass to wine, olive beer and they sit in town.

[00:08:51] And in some cases they could do 300, 400, 500, 500, it's an easy.

[00:08:55] But is that an outlier or is that the norm?

[00:08:58] That has now become the norm because people have this mentality of hits there.

[00:09:05] It's easy.

[00:09:06] War is better than less.

[00:09:07] Constitutes better than quality.

[00:09:09] So that's the people part.

[00:09:11] So you've got an increased volume because of how easy it is to apply to these jobs.

[00:09:16] You then go over to some of these platforms out there and I saw one recently.

[00:09:21] And part of their promotion to the market was we can apply to 30,000 jobs a month on your behalf.

[00:09:31] What that's doing is it's kind of data scraping.

[00:09:35] It's linking into legalism.

[00:09:36] It's open AI.

[00:09:37] It's putting in loads of jobs, it's scraping as a jobs in.

[00:09:39] It's doing a really basic keyword match.

[00:09:43] And that one is like keyword matches.

[00:09:44] We're talking about maybe one or two words that we're in your resume.

[00:09:47] And then that came to a job.

[00:09:49] So for example, let's talk about talent acquisition.

[00:09:52] You know somebody might be hiring a talent acquisition role and the word that matches in your CD is acquisition.

[00:09:59] But acquisition, as we all know, means that you're purchasing something you're buying something.

[00:10:04] So like the purchasing assistant ahead by it.

[00:10:08] Yeah, I assisted in the acquisition of lumber for our hardware store exactly.

[00:10:13] But because of the keyword match, this matches the job.

[00:10:15] So what these companies are doing and it's really basic AI is kept in between really is then matching your team worth to a job.

[00:10:22] And then this, by coming your profile out to 30,000 jobs.

[00:10:26] So you've got this huge level of applications that are going out to all these jobs.

[00:10:32] What's happening is you're creating this bottleneck essentially because so much is going in.

[00:10:38] It can't get through the tech musicians team to recruit us and go so well in the volume.

[00:10:44] So I think towards your question there's two parts.

[00:10:46] There's the systems that are fetch a purpose and they're not what I would call it our intelligent AI, they're basically AI.

[00:10:54] They're spamming the market.

[00:10:55] The applications are real people, but they're not relevant to the job.

[00:11:01] They're just wrong and it's bad matching pull back to better spamming the market.

[00:11:05] And then you've got people that are sitting at home going, run just going to do easier apply.

[00:11:09] It's there. It's only a team that must be critical. They're banging out easier apply.

[00:11:14] And again, LinkedIn has got a really basic matching capability.

[00:11:17] They don't have an intelligent matching. They just got a key word.

[00:11:21] So LinkedIn, you have an approach on 60 skills.

[00:11:23] We're going to have 50 skills. We're just adding in any skills I can think of that might have.

[00:11:28] And that makes you do to jobs. So you then start easier flying to those jobs.

[00:11:32] So there's two things going on. One is the people are trying to quickly sort possible second part, AI spamming out.

[00:11:38] And it's just creating these huge volumes in the job market.

[00:11:42] We've got about one minute left.

[00:11:44] So the audience, the people who are listening to this podcast are primarily leaders of job boards or

[00:11:51] marketplaces. You know, others that are very interested in industry.

[00:11:55] Pull at your crystal ball. Two years from now. What would you like to see job boards recruitment market places?

[00:12:02] Whether it's a LinkedIn and indeed a total jobs, a college or career whatever.

[00:12:07] What would you like to see us be doing differently with respect to the job application process?

[00:12:14] The easy applies the AI assistance.

[00:12:16] We're going down the AI route. So I think for us to say that we're not going to go or continue down that route being

[00:12:22] I think there has to be intelligent AI.

[00:12:27] So I think a lot of the what I would call basic AI systems that are out there needs to be removed.

[00:12:34] We need to bring in intelligent AI.

[00:12:37] Intelligent AI that is programs to think like a human and make a sanctions and make assessments as a human would.

[00:12:46] I think the bar in terms of the AI has to be high.

[00:12:51] So if we're talking about job matching, you know, we've got to have a high bar of job matching and the intelligent AI that I'm talking about is job matching that doesn't just look at keywords.

[00:13:02] It looks and pennies. It looks at industries. It looks accepted. It looks at career development.

[00:13:07] It looks at how long have they been in that role 10 years success.

[00:13:10] And it makes an intelligent assumption based on on that job matching.

[00:13:15] And the technologies there, technology we're using it on the hub. We have that technology.

[00:13:20] But it's more expensive.

[00:13:22] You know, it's more detailed. It's more brilliant.

[00:13:24] By using that technology, the results are more accurate and they're less.

[00:13:29] So you remove this ameloment from the market.

[00:13:32] So I think where I want to see the market in a few years.

[00:13:34] And we're not that far away from it.

[00:13:36] I want to see everybody using intelligent AI reducing the volume, focusing more on quality.

[00:13:41] Better matching, better assessments, you know, better alignment and the quality needs to go up.

[00:13:47] If we can do that, people are going to get more success.

[00:13:50] His company's only got more successes.

[00:13:52] You know, people will get less volume. They'll get more quality.

[00:13:57] So we're bringing back kind of the USP's of people.

[00:13:59] We're removing this volume, this quantity element because it's better alignment.

[00:14:04] It's closer matching. You know, it's looking at the intricacies of people.

[00:14:08] You know, look at people's soft skills.

[00:14:10] Look at their hobbies. Look at their backgrounds.

[00:14:12] Let's make some intelligent assumptions based on the canorator.

[00:14:15] You can incorporate it in one of the things we're doing is we're able to start to read people's language

[00:14:20] and actually analyze them.

[00:14:22] And almost a bit of a sort of symmetrical assessment at the person based on the language they're using.

[00:14:26] So you can actually go with this person's own ameloment person.

[00:14:28] It's person and then let's call this person to drive up.

[00:14:31] So you can create that kind of an analysis just from their documents.

[00:14:34] Let's be small.

[00:14:36] You know, an IIs there. Let's use it properly.

[00:14:38] Yeah, awesome. Well, it took us about 15, 16 minutes to get to the keyword quality.

[00:14:44] But I'm glad we did. So speaking of which, thank you for a quality time here.

[00:14:49] It'd been a pleasure talking with you.

[00:14:51] And thank you for sharing some of your insights and what you guys are helping job seekers better understand

[00:14:56] and be better quality.

[00:14:58] I think that's the key word. It's an awesome.

[00:15:01] Cheers Tom. It's been super. Thanks, Dave. We're going to appreciate it. Bye bye.