Harnessing AI for Better Recruiting: Balancing Efficiency and the Human Touch

Chad Delligatti, CEO and owner of InnoSource, along with Brett Johnson and Carol Ventresca, explores the world of artificial intelligence (AI) in recruiting.

We cover the journey of recruitment technologies, the significance and challenges posed by AI, and how to balance technology with the crucial human element within the hiring process.

Reflecting on his last 25 years at InnoSource, Chad says it's clear that recruiting has transformed dramatically. When he started in the industry, resumes arrived by fax machine; job postings were placed in classified ads.

Over time, technology sped up processes: websites, email, and digital applicant tracking systems (ATS) entered the scene. However, never before have we experienced changes at the pace we see today, largely driven by AI 05:06.

AI’s impact on recruiting is evident in both everyday workflows and at the organizational strategy level. InnoSource's recruiters who use AI are seeing significant improvements in efficiency, accuracy, and capacity.

The ATS has evolved from a resume sorting tool into a powerful data-processing engine powered by AI. Previously, recruiters had to manually sift through hundreds or thousands of resumes—a process both time-consuming and error-prone.

Now, AI-enhanced ATS systems quickly process vast numbers of applications, touching every candidate within 24 hours and reducing the time to offer dramatically (from over 20 days to about 9 days in our case) 13:49.

These tools free up recruiters to focus on building relationships, rather than being bogged down solely by administration.

If you like this episode, please let us know. We appreciate the feed back, and your support of offset costs of producing the podcast!

There's a misconception that AI—and ATS systems in particular—remove the human element from recruiting. That’s not the case with InnoSource's approach. AI augments the recruiters’ capacity, ensuring high efficiency, but every crucial hiring decision remains in human hands 16:10.

Job seekers should focus on authentically presenting themselves. While it's tempting to let AI generate resumes and cover letters, your individuality can be lost—and employers are getting better at spotting artificially generated or fraudulent material 38:30.

For employers, the primary advice is to take it slow and plan: define your goals with AI, get leadership buy-in, prepare your data, and ensure your processes are clearly defined before implementing any tools.

FAQ

How is AI changing the recruiting process?

Chad Delligatti explains that AI has greatly increased speed and efficiency in recruiting by automating initial resume screening, improving candidate engagement, and allowing recruiters to process significantly more applications with accuracy. However, human oversight ensures that final decisions still consider personal fit and judgment. See details at 07:14 and 13:36.

Does using AI in recruiting mean less human interaction for job seekers?

No. According to Chad Delligatti, AI frees up recruiters’ time from administrative tasks so they can focus more on building relationships with candidates and clients. The human element remains essential for final hiring decisions and ensuring a good match. Learn more at 15:25 and 33:24.

How can job seekers be more successful when applying to jobs with AI systems?

Job seekers should ensure their applications and resumes are accurate, original, and tailored to each job description. Chad Delligatti emphasizes that fundamentals and integrity matter, and warns against scams or unethical shortcuts such as using AI-generated fake credentials. He also recommends carefully following instructions in online forms. Get advice at 38:20 and 51:06.

We would love to hear from you.

Give us your feedback, or suggest a topic, by leaving us a voice message.

Email us at [email protected].

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And of course, everything can be found on our website, Looking Forward Our Way.

Recorded in Studio C at 511 Studios. A production of Circle 270 Media® Podcast Consultants.

https://creativecommons.org/licenses/by-nd/4.0/

Copyright 2026 Carol Ventresca and Brett Johnson

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Listener Disclaimer

The views and opinions expressed by the experts interviewed on this podcast are their own and do not necessarily reflect the views of the podcast hosts or any affiliated organizations. The information provided in these interviews is for general informational purposes only and should not be considered as professional advice. Listeners are encouraged to consult with qualified professionals for specific advice or information related to their individual circumstances. The podcast host and producers do not endorse or guarantee the accuracy, completeness, or reliability of any information provided by the experts interviewed. Listener discretion is advised.

We are Looking Forward Our Way. Hi, this is Brett. We cannot avoid hearing more about artificial intelligence in every aspect of our lives. We may not understand it and likely do not want to learn more about than just Siri. What was that song? But, you know, for those searching through a vast number of job postings looking for great employment opportunities, it is critical to understand what's happening. Our expert guest is Chad Delligatti, CEO and owner of InnoSource, a human resource staffing and data agency. Chad's going to provide us with the issues and challenges of AI in recruiting today's workforce. Chad, thanks for joining us today.

We've known each other for, I'm going to say decades now.

I think two decades, Brett, probably.

And finally got him in the studio.

Well, I'm thrilled to be here.

It is so good to see you.

Yeah, great to see you too, Carol.

You know, we've been good friends for a long time, but we've been after you to come on our podcast for a while and we finally. I think I didn't give you a choice when I said I'm doing this based on something that was posted on your website.

Well, that's very sweet of you and Brett, and I'm honored and thrilled to be here and thank you for continuing to push me to get down here.

We knew we'd get you one.

Oh, yeah. Oh, yeah, absolutely.

And it has been great to know each of you over the past two decades and watch everything you've done for our communities and where we first originally met through employment for seniors.

Yeah, exactly.

And let's give a shout out to someone else on employment for seniors back in the day to us. Rocky.

Rocky.

Hello. Hope you're listening today to the podcast.

Exactly. And if not, we're going to just keep sending you the link. But you know, too, we also, Brett and I have watched InnoSource and the growth and the accomplishments that you have reached, and I really want to give a shout out to all of your team. They are wonderful. They were very good to us at Employment for Seniors and supportive and always with a smile on their face, regardless of what my request was.

Well, that means a lot. And the team really cared about employment for seniors, and the team at innosource is what makes us special. That's what drives the engine at innosource. That's what gives back to the community. That's what gives the results. So there's nothing more I love to hear than a compliment about the team. I'm just setting the tone for the team. But at the end of the day, they're the special ones that do all the work.

Yeah, they are. They are there. Exactly.

Yeah. Because, you know, every time I've gone in during that time period, it felt very genuine that they cared, you know, because there are tons of non profits that I'm sure knocking at your door.

Right.

That say, hey, can you support us? Can you support us? And. And we were very always appreciative of that. We got the time to talk to you. Well, I appreciate, you know, and in your continued support, even though you're off the board, a lot of people don't. It's like, I'm done with that. I'm, you know, the next thing. I always thought it was genuine, so. And I know it was genuine.

Well, thank you.

Yeah.

And employment for seniors always had a special place in my heart. And you mentioned coming into innosource, you felt welcome and warm, and that's something we really strive to do every day. And. And you think of all the different environments you go into where you're maybe nervous, you're uncomfortable. And when you think of innosource, we're changing lives every day by hopefully giving them that career opportunity, helping philanthropic organization or giving back philanthropically or helping nonprofits. And so we really try to make everyone comfortable when they come in. So I appreciate that feedback. And as you mentioned, always had a soft place in my heart for employment for seniors.

We will all be seniors in our life. We will all have that need that we used to talk about and having a good, comfortable place for seniors to go when they have that need, need counseling or need help to get a job. I think there's always a special place for that in society. And so thank you both for all you did with employment for seniors over the years.

We really had the same mission, different populations that we worked with, but the same mission and goals.

Definitely.

And it doesn't matter whether it was when I started at employment for seniors in the middle of the recession, the 20089 recession, or in today's very different workplace environment, all people need to have the opportunity for a good position, an opportunity to really use their skills. And that was basically Julian Marcus belief. Everybody deserved the grace and ability to use their skills.

And Julian was the founder of employment for seniors. And if I recall, he worked in the clothing department at Lazarus when he founded employment for seniors.

Exactly.

It's a neat story.

Yeah, it was a great story.

Neat story.

In talking about innosource, you all are 25 years old now. Yes. This is Incredible, the growth of this organization. Tell us how you got through this journey of your own career path and

innosource got going well, Carol, I appreciate the kind words and once again I just want to thank both of you again for having me in today. One of the things I want to start with was one of the things we spoke about at Employment for Seniors years ago. And one of the things we spoke about was technology back 20 years ago and how some seniors weren't comfortable with that. And what we would talk about is technology will never move as slow as it does today into the future. And I remember we really were working with people around typing and just the computer skills. So when you think of recruiting and where the world's going today in today's podcast topic of artificial intelligence, it's really not changing, right? It's a new technology, it's making people uncomfortable. But my advice is lean in and start to embrace it now. So when you look at our 25 years journey at Innosource, it's been amazing.

It's nothing I thought I would have, but when I first started, we would place classified ads, you know, people would call in on the phone, we had manual fax machines. If you sent in a resume and we got 100 resumes faxed a day, that paper was spitting out everywhere. When we would do drug screens, we had a printer that print the results live in the office early on, website early on. Monster.com big so when you think about that, as I look back, technology has always been advancing in our 25, 26 year history at Innosource, but never at the speed we see today. So as we look to the future and talk about what Inner Source has done, we originally founded as a traditional staffing workforce specializing in really customer interfacing work, partnering with organizations that need long term talent. We've never been in the temporary field. We don't place temporary people. We partner with organizations from day one that need that long term permanent talent and lean on us for our expertise to find that.

When you look at the industries we serviced over the last 26 years, we've done a lot in utilities, manufacturing, logistics, customer operations, health care, and a lot in the government side. And so firsthand in all of those different environments, we have seen how recruiting has constantly changed. And with this recent big boom around AI, what we are finding is our recruiters that are adopting it, and they all are doing a phenomenal job at adopting it, are still keeping the human element in the decision making on the back end. But what they're finding is they can do a lot more quicker, more efficiently and more accurately. So one of the analogies we use at innosource is riding a bike versus driving a car. And when you think of your daily work pre AI was at the pace of riding a bike, where now what we say is if you don't want to embrace AI, that's your decision. But people are going to be doing work quicker and getting to that result quicker than you, and so they're going to be driving the car. So what we recommend is get involved, get going early, pick one workflow or pick one thing within your company around that AI and start to work on it.

But our evolution has been amazing. We started from, as I said, fax machine resumes, phone screens, live interviews, to pivoting through Covid, going all virtual to now really seeing the power of an AI engine, partnering with a recruiter and seeing how much more work they can get done while still at the end of the day controlling those final decisions on their own.

Tell me if I'm correct in my beliefs here. When you started innosource, it wasn't really just a matching process yet you got the resumes and you sent them to your client who needed somebody. You were really also looking at making sure people were trained, they had the skills they needed, they were going to be good job applicants. And right now that you're just carrying that on.

Yes, yes. So one of the things we've always talked about, we're changing lives every day. And at innosource, we didn't believe in just putting warm bodies in jobs for a quick fit. As you mentioned, Carol, when someone came into innosource, we invested in them and wanted to find them the right career opportunity. So we always have had training opportunities. Our recruiters have always worked with individuals on resume building, skills testing. We have hundreds and hundreds of of skills testing and training available at innosource and in all of our regions across the country. And something else that really shows the passion around how much we care about our associates and not only just getting them jobs, but helping them train, helping them understand how to look for a job, helping them understand how to report day one and operate in that new job.

We're big believers in upskilling and Dr. John Comer from Otterbein partnered with us, the Coalition for the Common Good with Antioch. And we now have some certificate programs with Otterbein and Antioch so that we can take individuals in, put them in a one to two week upskilling environment, train them for the Skills they need to be successful in that job and then launch them in a career placement. And what we're finding is retention is up double digits. Associate productivity coming out of training is twice as high. But in that upskilling, we're giving them the chance to get better prepared for that job where they otherwise would be learning on the job and maybe falling behind a little bit. So at innosource, we. We really care about the human beings, but we also understand what the customers and the clients expect.

And they want a good candidate that's gonna do the job, and that's when they lean on us.

So, you know, Chad, I have this one upsmanship. I play with Brett, and as an Otterbein grad, I'm way ahead of him. And now you've just given me another little.

I love it. I love it.

Check mark on my side. I love it.

I've just given up. I don't even try anymore.

We just can't get those Miami grads or folks to come up here. That's all there is to it. So. So we'll shout out to Dr. Comerford, who's a great guy, great guy. And it's a wonderful program. So thank you.

Yes.

So when we hear the term artificial intelligence, we each have our own interpretation. In the human resources arena, it's grown from a simple need to tame the number of jobs posted and resumes received. Can you give us a quick look at the historical significance of the dreaded Applicant Tracking System as it's now kind of had a. Has a negative connotation anymore? Yeah.

So ATS Applicant Tracking System has had a huge growth, development, evolution over the 26 years I've been in recruiting. And when you think about it earlier, early on, as I mentioned earlier, these resumes came in in one standard format, whether it was through a fax machine, dropped off in the office, or a phone call. And what has transpired with these ATS and the online systems now is now an individual can apply to hundreds of jobs at night between AI and these applicant tracking systems. So that now, as the employer of record or the recruiting firm, the amount of resumes we get in the volume is mind boggling. And AI combining with that ATS is giving organizations that chance to continue to be very successful and get through all the data and information and make the best decision on. Whereas pre AI applicant tracking, you got a thousand resumes. You had to have your recruiters go through all thousand resumes in every line on that resume. Now, with the AI, you can make sure everyone's getting touched within 24 hours, all the information's being digested.

And now that recruiter is much more equipped to make the best decision quicker than before. So what a recruiter may have done in a week before they're doing in a day. And when we look at innosource and we look at that applicant tracking system, traditionally before all of our interviews and phone screens and applications were between 8 and 5, 7 and 6, you know, some west coast time we'd go a little later. Now what we're finding over the last 12 months, 56% of our total applicant flow and application are coming in after business hours. When we look at that applicant tracking system, another issue was whether it came through the fax machine or through the phone or email. We had to connect with that candidate to set the interview and hold the interview. We've cut that first time connect down 100%. So we've gone from about 9.62, I don't remember the exact numbers to about 4 something.

Then when you look at time to offer follow up, follow through was getting creeping in the high 20 days with the AI, you know, working with that applicant tracking system, we've cut that down to nine days. So we've seen a 200% improvement on time, are on off time to offer 100% improvement on first time to connect. And we're touching 56% of our applicants now after hours. Within a traditional applicant tracking system, we would not been able to do that. But by combining that AI with it, it gives us the ability to process a lot more information a lot quicker. But we still keep that human touch on the recruiters on the back end to make that final decision.

And that should be thinking of it from the applicant point of view. That should be a positive thing.

Very positive.

It's not just do it faster, more efficient, but it's actually maybe better for the applicant because it's matching it better. The ATS is now smarter.

Yes. And let's another example is time. So before our recruiters were just trying to manage the workflow, the applications, they didn't focus on the relationships from the recruiter side. Now they are able to focus on the relationships with the candidates and the clients to ensure that fits that much better. Where before they were just doing everything they could in time management to get through the resumes and handle that workforce flow, where now they actually have time. Where we are pushing our recruiters to work on developing relationships with the candidate, develop relationships with the client. And through this efficiency of AI and, and continuing to build out the ATS to talk with the AI, Great things are happening. And one of the things I tell our team often is technology is great, but you make it come to life, you make it magical.

You get out of it what you want. So the more we can get our recruiters to have time to work on those relationships while still doing good, quality work, that's a win.

Because I felt there was a short amount of time, and this is just outsider looking in, though, that it felt like this ATS thing was. Was going to be the end all, be all it takes. It felt like it was going to take the human element out of it. It had that perception and people kind of. I thought they were kind of talking about this. I just put it through the ats. It'll spit out the perfect person and we offer the job. It didn't work, did it? You know, I mean, you need the

human element on the back end. Right. And what you say is the speed of that application started moving faster than the speed of the human response.

Yeah.

And that was becoming an issue. But now with the AI, you know, they have that ability to work through it. And what we're finding at the end, that human being still needs to make that big decision.

Right.

And this AI is just equipping them with the data to make that right decision. But if you just trust the AI all the way through, it's going to miss a human element piece. But, Brett, what we believe in is equipping our recruiters and our team with the AI to do their work more efficiently, quicker, and at higher volumes, while keeping them empowered to make ultimately that decision. So what we're striving to do at Inner Source is create more capacity at a higher level of results output and not really replacing the human beings.

Yeah.

So all of these systems have an incredible impact on both job seekers and employers. The employers. It's making it more efficient, more effective, and getting through the process quicker. Because bottom line is recruiting is expensive and you need to get a new person into the seat in your office as fast as you can.

Yes.

On the flip side of that, as things are getting more efficient on the employer side, is it better on the job seeker side, or are people just getting pushed out of the pipeline as quickly as they are putting their applications in?

I think probably a little bit of both. That is a great question. So one of the things we always say is AI itself is not the issue, it's the design and the governance that are. So what we believe is a good AI tool, a good process set up to use AI should improve the responsiveness, the precision and the engagement. Poor AI can damage the candidate and the company's reputation very quickly.

Right.

So on the front end, before you just take an AI tool off the shelf and think it's the end all, be all, apply it to recruiting or HR and it's going to solve all of your problems. Slow down. First, I believe you must have leadership buy in. If your leaders aren't bought in, your users aren't going to buy in. And secondly, you've got to have that data prepared. The AI tool or the large language model will only be as good as the data put in. So if you don't have your data prepared and you don't have leadership on board, Carol, back to your question. You could create a train wreck and you could have a bad candidate experience as well as from the employer side, you could hurt that brand.

However, if you think it through on that front end and your team is trained, the model's built the right way, the data is clean and accurate, you have domain experts in there constantly testing and training the model to make sure it's doing what it should, ultimately both ends should get better. That candidate experience should be quicker and be able to develop more of a relationship and talk where the employer should ultimately be able to feel. Those statistics we talked about earlier touch every candidate, get better candidates and do a larger amount of work quicker. That would have taken a lot of time before. So at the end of the day, if it's set up right, the data and governance are built right, the team has trained and believed in it and the leaders are on board, it's going to be a win win across the board because candidates can do more quicker, have more time to meet with recruiters and companies can get higher quality hires. But if it's not set up on that front end, you could have some issues on both sides.

I had an interesting situation happen when I was at Ohio State working with undergraduates and we did a lot of work with the state of Ohio and particularly getting students in things like summer internships and and special programs. But they had to go through the tracking system that the state had. And what no one knew is that there was a box with a question at the very end of the application process that the students had to fill out correctly or the system would spit out their application. Because even though they filled out that box at the end, it was the first thing the system looked at. And so at the end, when they were sick of this application that was very long and they put C resume in that box, then the system kicked them out. So this recruiter came in and said, I got a tip for you and told students what to do in that box. And basically they had to literally put everything in that box that showed they had the skills required in that job. So that's what, that's what happens.

As I mentioned to you when we were talking around the table before we started taping, if you ask a question, it's like a survey. If you don't ask the right question, you're not going to get the right information. So what you're saying is building these AI systems is more than just clicking it together.

Agree. And one of the things I like to talk about are what are some of the benefits, but what's the counterbalance on the negative there? So as I mentioned earlier, the AI should create more human connection, not less. But with that, the benefits are immediate candidate engagement, faster resume review, more consistent evaluation, reduced recruiter administrative burden, faster movement of qualified candidates, and then an improved communication speed. But to your point, if that is not done right and you build a weak system on the front end, take something off the shelf. Don't have your data prepared or your team trained. Absolutely. The AI can reject good people incorrectly, and then bad data will create bad outcomes for people. So that front end is very, very important.

And don't try to boil the ocean with AI up front. Let's boil the frog. Let's start one thing at a time, let's master it, and let's move on to the next one. But we got to make sure that data is prepared, the people buy in. And I think at the top, you've got to set what is the culture for that AI? As you mentioned, everyone's a little scared about AI. Everyone's a little uncertain. What's the impact? To me, I'm being told it's going to take my job. Well, if we lean in and think back to the last 40, 50 years, with all the technology advancements, from the PC to the laptop, to the cell phones to social media, to the applicant tracking systems to AI, they all had an impact, but they have not eliminated human beings.

And we will see some element of automation. It inevitably will happen over the next few years, but for everything that's automated, we will create another opportunity in the marketplace to support that. So I think the important thing is don't fight it. Be open to it. Get in the game quick. You don't need to rush it. Be thoughtful, but get the team on board. Get your leadership, know your strategy, know your AI culture, get your data team involved and then get going and go one workflow at a time.

And at the end of the day, what we say is most AI failures are not technology failures. They are process, data and leadership failures.

Right, that makes sense. So let's jump off that answer on the employer aspect of, you know, utilizing an AI product quality tested. I mean, it looks like it needs to be along with information database that's accurate when hiring, when building that hiring system, talk more about the steps an employer should take as they utilize AI, whether they're building their own or purchasing a system.

Yeah, so that's a great question. Can go many different ways. Indeed. So I think the first thing to do is first really understand as a company or as a leadership team, what are you trying to accomplish with AI? And one of the things we start early on with any customers or internally at innosource when we talk to an individual is if you could take one task out of your day to automate or take away that you don't like doing or really bogs you down, what is that? And we think that's a great starting point because now you're getting the end user to buy in up front and you're solving the thing that they don't want to do the most day in and day out. So I think starting slow to go fast is very critical, but it's really the planning on the front end versus jumping in, getting a tool you don't know, and then trying to reverse engineer that tool back to you. Well, now your data's not ready. You're trying to clean your data, you're telling your leaders the value, but they're not on board yet. So what I would say is you want to have clean data.

You definitely want to make sure your workflows are all defined. You've got to have those defined, and that's complex to get done as well. You've got to have good hiring discipline to know, you know, how are you hiring, how are you using that ats? You got to have the human oversight, right? You got to constant have that human oversight. And what we're finding more and more is these domain experts are critical. You know, you have that reinforcement learning from the, from the human feedback. And that's something we're finding is very critical. And once companies are utilizing the AI, having those experts in there to constantly train and reinforce those models is critical. And then you got to have ethical governance to make sure, you know, it stays compliant and it's doing the right things.

I'm really liking your answers. And it's eye opening to me this, in this realm, again, it's outsider looking in that you are really implanting that human factor. Human factor, human factor, human factor. There is no, let it do this on its own and see what comes back. That's reassuring to me.

Is it good?

I appreciate that, you know, honestly, because coming from a forefront company as you are, and you have all this ton of influence in this industry to showcase how you're doing it and you're doing it right and it's working, and it's working. The percentages are in your favor that you're saying we're doing this and this, we're doing this and this, but we still that human touch in there. And it's vital that the human touch is in there.

And when you look at hundreds of thousands of candidates over the last couple of years coming through our AI and you back that in, that's hundreds of thousands of manual hours that the AI took care of. But it empowered our recruiters, as we said, to have better communication, more time for relationships, making a better hiring decision. And the statistics on the back end are showing turnover is down about double digits using the AI tool because I think we're getting through a broader group of candidates on the front end to hire the right one on the back. So another thing I always say, organizations should not ask how to automate recruiting. They should ask how to improve decision quality in candidate experience at scale. Because if you can do both of those at scale, your candidates win, your recruiter wins, and ultimately your customers or your hiring manager wins because they're getting the best talent at the right time quickly to do the job the right way.

I like this too. As Brett said, bringing in the personal contact. But it's not just the placement, it is the retention.

You got it? That's the key. Yeah, you can do all the placements in the world, but if they don't stick, that was not a quality recruiting process. And you didn't really understand the role the person was going into and the skills and personality and characteristics that individual had.

Because that's money in the bank. That's money in the bank right there.

And that's the match. You've got to have the match. And when you think of it, one of the things we, we are financially aligned with all of our customers are when we recruit someone and place them in a client, we are financially vested with them for at least the first 90 days because of the recruit to order, the customized behavioral interview, the skills testing that we Put them through the same process that our clients would. Anyone that turns over quick, we lose money. So we're financially vested. So we want ultimately for everyone we hire to ultimately become employees of our client companies. Unless it's an on site, outsourced area, we're operating over time. And we want them to become very successful because the ultimate for us is watching them move up in the organization and knowing where they came from, where we identified that entry level talent.

When I was going through all of the steps on your website regarding AI, I started sort of laughing because as a career counselor, many, many years, way before all of these systems started, and this poor little senior is putting out their resume and they go, well, but I never hear anything. I say, okay, well you do your follow up and then call them again in a week. And as I'm telling them this, I'm thinking to myself, that poor recruiter, because God knows they have a stack of what are those little message notes that post it notes? Yes, post it notes. Call this person, call that person. So the whole process here is trying to make sure that AI systems can do, they can create an engagement connection between that recruiter and the applicant. The downside of this is, yes, they're hearing from something, somebody right away when they send their resume in, but it's not really a person. So how do you move past that initial connection of not talking to a fake person?

Love this question. So for 24 years pre, we started using AI, I'm going to say in 23, 24, I think 2023, one of the common things we heard was candidates would apply and never hear back.

Exactly, yes.

Now in people, corporations, defense, when you think of indeed, monster career builder, zip recruiter, these huge enterprises have many different recruiting channels or application channels to come in and they may get 40,000 applicants a day, a week or a month. It's virtually impossible without technology to get through 40,000 resumes the right way. So we at innosource the last 20 plus years, one of the things we always said was anyone that applies to us will get a response within 24 hours. That was very difficult. And Carol, the reason it was difficult was at times when we would have a huge influx of traditional applications that Brett, you and I spoke about earlier, we would have recruiters working late, coming in the morning, we'd be hiring extra recruiters and there was probably a few resumes we didn't get through. But now what is happening is the AI is dramatically improving that responsiveness. But you have to be careful because as you said they just don't want a bot to talk to. They still want a human being.

So what we have found is we are using the AI on that front end more. I'm going to say 20, 30, 40%. So the first thing that happens is now when they apply and this is happening at the large organizations across the board, immediate acknowledgment. So now I at least am getting some satisfaction. I at least know I'm in the system. And right there you think back to the old black hole. You never even knew did I send it in right? Did I hit enter? Maybe my T1 line or maybe my 14.4 Frognet dial up from Athens county isn't connecting.

Daw, you know, or the US mail didn't get right.

Exactly.

So now with the AI, we at least have that immediate acknowledgment. Secondly, one of the things we're really finding is they want updated. These candidates want updated. And even though it's through automation, it makes them know that we care about you, we're keeping you posted, we're thinking about you. So we think the AI can help a little bit on that. Updates the next one. As I mentioned earlier, faster scheduling, that's huge. We've had 100% improvement in first time connect, 200%.

So if you think we're now connecting in four days and we're giving offer in 9.62 days, that's gargantuous.

So let's be kind of a little more specific on when you're saying scheduling. Schedule for an initial interview, which could be over the Internet or it could be in person.

You got it.

And the issue was you could call and try to get ahold of somebody two or three times before you ever really connected with them to get them in the schedule.

And we've all heard voicemail box full, yes, what do I do now? And in their defense, someone could have left a 20 minute message or not. So now I can't leave a voicemail. I could fax again, I won't know for sure. I could try to email or even

text, but you're never sure what's going on.

Exactly. So now what we do is on that front end, have the immediate connection connect with that candidate, let them know what's going on and then we give them the opportunity through the technology to pick when they want to schedule with one of our live recruiters. So it's not scheduling, more automation, it's scheduling for that live piece. And then that's where now our recruiters have that much more Time available to build that relationship, work with that candidate. We're big believers in a proprietary behavioral interview process to really make sure the match is right. And then ultimately that recruiter makes that hiring decision and hands them off to the account manager who gets them started in that new job. But the black hole is slowly going away. However, the only way it completely goes away or it goes away in a positive fashion is to ensure you're giving the candidate the attention they need, the responsiveness they need, and not just relying on technology to handle it all.

Knowing your process, knowing when the technology's going to touch, know when the human's going to touch and who's going to make that final hiring decision. And we let the humans do that at innosource.

And it would say seem too that if the initial contact sets up a pattern so the individual applicant knows that pattern, knows, okay, I can expect to get an email or I can expect to get whatever as opposed to think, well, are they going to email me, are they going to call me? That kind of thing. So it makes an easier transition through the process.

Right. We never want them to feel like it's a fake, fake interaction. We want it to be that they think it's intelligent engagement and it's respecting their time.

Right.

That's the most important thing.

That's interesting. Yes.

We really want to make sure of that. And because.

Because a job applicant would not assume that you really care about their time.

Right. And we do.

Yeah.

And we're vested. And the more successful they are, the more successful we are. And when our clients see quality hires, quality results, quality on site outsourcing results, they'll come back for more.

Right.

So we've got to make sure that our ATS spread our AI. Carol is doing exactly what we need it to do, the way we need it to do by helping our recruiters, making them better, to ultimately give them power to make that great decision.

Right.

Yeah. Now, you earlier had mentioned something about, and I'm intrigued. I want to dig into this a little bit deeper. Ethical practices so AI can be misused. We see it in the news every day. What do you tell employers regarding ethical practices when they're developing an AI drill driven recruitment system? And do you have recommendations on how AI should be maybe better regulated?

Yeah. So one of the things we always talk about is ethical AI will become a competitive differentiator. And the human accountability is very, very important and still matters a ton. So AI does not eliminate employment law obligations. However, what we say is AI should enhance the human judgment not replace accountability. So those are some complex words there. But what we're really saying at the end of the day is it's here to help, but it's not going to replace that human side. And you've got to make sure you build it the right way on the front end, or you could have a complete disaster on that back.

Well, and I.

And they hear hallucinations, right?

Yeah.

Because I don't even like to say that because. Yeah, you. You don't even want to get anywhere near an AI hallucination. Right. But they can happen. They do. But you want to avoid that as well.

Well, and I could see an AI being completely blind to race sex because it doesn't know that Mary is a female name or male name unless you program it to be that way. So.

Great. So what you have to avoid, to your point, is hidden bias in your training data.

Yeah.

You can't have that. You can't have a lack of transparency. You can't over automate. That's when those issues happen. You can't have poor governance and you can't have inconsistent, consistent decision logic. Those will all add up to a disaster. And remember, your EEO standards still apply and employers should create governance now before the regulation forces it.

Yeah.

So that's one of the things we're really working on in Innosource. We want to get in front of it. So then as it comes out, if we have to tweak one or two, we will. But we want to be on the front end, not the back end. Being reactive.

Exactly.

Well, and that still goes all the way back to the notion of good hire, good retention. If you've got the right person in there and they, you know, without crazy judgments that happen.

Yep.

Then you're going to have.

I'm gonna go one step further. Good process. Right. Because at the end of the day, if the organization cannot explain how that hiring decision was made with this new technology, that becomes then ultimately a business risk. So you really have to know your hiring process and the decision making throughout that as well, and then ultimately get to that.

Right. Okay. So the flip side on ethics is, you know, employers need to be ethical, but so do job applicants. And needless to say, it's way too easy to ask what's that Guy Claude or ChatGPT to please? Here's where I've been and what I've done and give me spit out a resume. I can sit back and remember looking at. There were some counseling groups in town who would work with clients and help them do their resumes. And we suddenly would, at employment for seniors, get 10 resumes in that day. And they all looked alike and they all said the same thing because this group of people had gone to the same workshop.

And it's too easy to have somebody else do your cover letters and your resumes and your job applications. Give us some advice to job seekers to ensure that they are being ethical during their job search, but also how tips on how they can even be more successful by understanding these systems.

Yeah, so that's a great, that's, that's a great question, Carol. And I'm going to break it into two pieces, the employer and the job seeker. So right now we are actually dealing with a lot of fraudulent resumes coming through due to the new technology. So people are trying to take advantage of the system, whether it's someone else doing the interview, It's a fake resume, it's a fake interaction. And so employers actually right now with this quick AI boom, must worry about ensuring the candidate they're hiring is the individual that came through the hiring process and having your checks and balances in there equally. The job seeker gets worried. Is this a scam? Is this a bot? What information do they need? $10 for your application? Well, I don't know any job that ever charged $10 to apply. So that's where you really on that front end want to give that confidence, as you said, to the job seeker to know they're not getting scammed or taking advantage of.

So the fundamentals still matter. AI, what we say is it changes the tactics of how we operate, but it doesn't change our integrity. We're going to do everything the same way. We're just going to use this AI to make us a little better and a little quicker. But how are we going to show that through the technology back to the job seeker that they can feel it, hear it, see it. And some of the things I mentioned earlier, with the constant communication, the follow up, the human element coming in and whenever we do do a virtual interview, we want him on screen. We are pushing very hard to get all of our interviews back on site. And what we're finding is our recruiters are starting to travel around the country and doing more live hiring and interviewing again, which is outstanding.

So I think it really ties back to that process, making sure that your technology is in sync with your people and your people know what the technology is doing. And at the end the people are making that decision. And that should then rub off or come across to the job seeker that they do care. And if you ever are uncertain or being asked for information you're not sure of, stop immediately. You do not need to take that risk. There's many ways to just go out and even Google that company and see there always should be a phone number to call. There should be a lot of other information. So if you're ever a job seeker and something feels off and you can't find any information on the world wide web to support it, it probably is a scam.

And get out.

All right, so it's crystal ball time. What do you see coming in the future? Formation of AI systems and recruiting and retention of employees.

Yeah, so I think the next phase is really orchestration and intelligent coordination. So we're moving towards systems that can coordinate workflows, decisions and communication across the enterprise, not simply just answer questions. So when we think about this, the different areas that will be impacted. And it's coming quick, Brett, that it's coming quick on top of everything else we talked about, but workforce forecasting, we're seeing a lot better results there. And looking at that forecast and forecasting

within the company or like in a region.

Yeah, within the company.

Within the company.

Within a company, within a division, within

a group, based on outside forces telling

them historical information, all of that, we tie that all in. Secondly, candidate matching. Right. We continue to get better now. Better. This AI is so intelligent. And think of thousands and thousands of resumes and people we've hired on an annual basis over 25 years, hundreds of thousands of people that historically, now AI can scrub and get smarter to really make that candidate match on the front end even better. Skills gap analysis.

Right. That's something people talk about a lot. So if the AI tools built right, you can still identify that a little bit quicker. And now that's also the future people are figuring out. How do you validate that through AI versus traditional skills testing. But it can all be tied in, you know, automating, onboarding, coordination. So something else we're seeing is not only that recruiter function on the front end, but now when that recruiter hands off that hire to the account manager and they begin to onboard them, where does that get more efficient and more accurate versus the hundred forms in the past? And how can you populate that quick? So the future advantage will not come from simply just having the AI. Everyone will have AI.

It's at our fingertips. Today you can go online chat, gbt. It's right there. Your advantage and every other person's advantage will come from how intelligently they in the organization they work for, integrate that AI into their operations. And so I hope my message is coming across that I love AI. It's good. I don't think it's going to replace all human beings. Don't panic.

But it's going to make all of us better and quicker. But it's just not going to happen by just saying, I use AI now. You got to lean in, you got to understand it, you got to invest in it. You got to make sure on the front end you're prepared, your team's prepared, the data's prepared, and then pick a workflow. Like I said that earlier on. Pick something people don't want to do, pick something that's a pain for them every day to do and start there and get that employee buy in and then work one flow at a time. And then you have to find the right large language model and tool that fits you as well.

There's a company, I forget what company is, it's local. Here in Columbus, they're a janitorial system. Okay. Big name. And if I remember the name and the person's name owns it, I know you both know who it would be. But she mentioned something about this in an interview I heard on a podcast that I helped record. Talking about that pain point you're talking about that they created this robot and a monitoring system in industrial buildings that will efficiently clean the building because AI is sensing how dirty the area is and the robots go to it because no one wanted to do it or they couldn't get to it or it could be done after hours. Then it's back to work that it's very clean, especially in these buildings that have to be super, super clean, superconductor kind of stuff, that sort of thing.

And it was just amazing here going, that's cool. And it didn't necessarily eliminate anybody's position. It just did something nobody did really want to do anyway. You did it very well and. And it created opportunities. It was mind boggling.

Yeah. What a great use. Right? So something they didn't want to do. Something that was critical to be done.

Yes.

And something that technology could come in and get as good or better result and make human beings happy about it.

And they're at test levels that are industry standard that they know everything's clean to where it needs to be. Especially in those very sensitive super superconductor kind of building. That aspect of it. That was the coolest thing kind of going to that fact.

One of the things that as I was putting the script together, I kept thinking to myself, for decades, we've all complained about the human resources process, the hiring process. And so instead of now complaining about AI in that hiring process, here we have a tool to make that process better and hopefully people will work on it. One of the things that I was hoping that we would talk about today and we haven't hit it, but I'm going to ask anyway. An issue that many employers, particularly smaller employers, don't do well is creating job descriptions. And I'm trying to figure out, how does that fit into this process? How can AI make an employment employer stronger in their recruiting and retention because they've had to think better about?

So great question. That is one thing many employers don't realize, the importance of a very accurate job description.

Oh, exactly.

And one of the things we found and we actually worked on over the years is you can lose a lot of great candidates by not having a good job description. And over time, many people got complacent and just kept putting that same job description up and over the years. But the role actually did dramatically change. So it is very important on that front end to have an accurate job description. Clearly defining the role, the technology, the expectations, the background you're looking for, all those key details, how does that tie in? Beautifully complex, but it should be done. So when you're thinking of our AI tool, it's called Mini Recruiting, and Mini is the name of our dog. I don't know why the marketing team picked it, but I love it. So Mini is our mini recruiting tool.

And when you think of all of the people that come through Mini recruiting on the front end, ultimately, if that job description is not built right, that data's not built right. So then what is our Mini recruiting evaluating that individual off? So over time, I think those job descriptions will be tied in more. But right now on the front end, that goes back to the data, the cleanliness of the data and having it organized and knowing what you're looking for. So that if that job description is very clear and it's put in the AI, that AI is working right around that. But if you have a job description that's not real accurate, has errors, right. That's where you begin to have some of those issues we talked about earlier where maybe the AI tool isn't accurately recruiting because you didn't put the data in on the front end or you took the human decision making away. So I think job descriptions are critical. I think they constantly need to be updated and I think they should be tied into that AI recruiting because that's A key data point in anything you're recruiting for is having a very good, clear job description.

Well, junk in, junk out.

You got it.

Ultimately.

But the AI system isn't going to pop a, a job description out of thin air. The employer still has to do some very concrete.

So our recruiters write every job description and then they go to our head of HR and then our marketing team even gets involved. So we do not have AI automate or generate our job descriptions yet. The human beings are developing them now. Are we running them through AI to make them cleaner, better, and maybe additional data that we didn't have? Of course. But to your great question there, a great comment. We still let the humans, because they have to be involved with that because they're the ones ultimately talking with the customers, getting the feedback on how is the role changing? Where are they going with it? How does AI impact them in their role now where three years ago that customer, maybe it did not impact them.

Well, I would think employers would take that information if they do, and they should do an exit interview with this person that's listening. If it's a good leave, you know, a happy leave and exit interview going, okay, what did you do in this position? What would you tell the next per, you know, talk about great information that could be part of the job description. Again, depending on, on the, on the exit situation, what you know, and I know tons of employers don't do that. I mean, it's just one of those, okay, you're moving on, goodbye, don't let the door hit the, you know, hit your butt on the way out kind of thing. It's like, no, take advantage of one more hour with that person before they leave because you might be able to get a better person that just left.

You know, we're big surveyors as well at dental source, so we like to survey new, new hires, active clients, and then definitely on the exit, you get a lot of great feedback on the exit and you got to be able to look in the mirror sometimes. Maybe there is an issue, maybe the technology wasn't right, maybe you whiffed on something. But that's where you get stronger and better and you need to have that human feedback loop on there. Yeah.

So I always complain that our time with our guests goes way too quickly. And the last question is always, you know, your words of wisdom. But I'm going to put in a tip from me to job seekers in our audience before we ask Chad for his last words of wisdom. And I learned over time working with a lot of job seekers, literally 18 to 80 that don't shortchange yourself and your applicant candidacy by not doing your own good work to build that candidacy, the better your resume is. You're doing it yourself. You can have people help you, but you're really thinking through it will make you a better interview. It will make you a better, better candidate for that job and more likely to get the job you are looking for. But you have to do the work.

So that's my little bit of advice to our job seekers. So now your turn. What are the last words of wisdom that you have for our audience and any suggestions?

Yeah. So thank you again for today. Outstanding. Enjoyed this. A couple things come to mind. So the first one I would say is AI is not the future of recruiting. Human centered AI is right once again, human centered AI. So when I think to the future, my kind of closing wisdom is recruiting organizations or organizations in general that succeed with AI will be the ones that remember recruiting is still a people business and technology can improve the speed and insight.

But at the end of the day the relationships, the trust, the judgment are still determining that long term success. So I think what we need to do is lean in and understand AI is going to be critical. But recruiting is still recruiting and speed matters, right? It matters and that's what AI is making us quicker. But at the end of the day a culture fit and leadership still matter more and we need to make sure we don't lose that human touch. And I think if everyone can lean in with their organizations and understand that balance between the human and the speed of AI and then on the front end getting it built right, getting that data right and going slow to go fast, I think we all can be successful, can grow from AI and give our customers better service, our clients, our internal people and at the end of the day still keep human decision making as a huge component but lean on that AI to do it quicker and more efficiently and more accurately.

Wonderful.

Yeah.

Thank you so much. It was one.

Thank you for having me in. I love, I'd love to come back sometime if you ever want me. And I enjoyed the conversation and if you have any follow ups, anyone that listens has follow ups, please let me know anytime.

Well and you know we should put a little plug in for the blog that is on your website.

Great.

That's how I found this topic. Perfect. And so for those folks who are looking for more information not just about innosource but about recruiting in general, lots of great information.

So innosource.com blog some social media feeds, send an email anytime or check it out.

Wonderful. Thank you again.

Thank you Carol and Brett. I appreciate it.

Many thanks to our expert guest, Chad Delligatti, CEO and owner of InnoSource, a leading human resource staffing and data agency, for joining us.