WEBVTT 00:04.537 --> 00:07.201 [SPEAKER_00]: Welcome to the show, I'm your host Nadia Atwal. 00:07.721 --> 00:13.069 [SPEAKER_00]: Today we have a fascinating specialist in AI who's bringing it into the offices. 00:13.409 --> 00:15.872 [SPEAKER_00]: Welcome to the show, John Sorsese. 00:16.173 --> 00:16.633 [SPEAKER_01]: Thank you. 00:16.854 --> 00:19.557 [SPEAKER_01]: And having my name pronounced correctly is amazing as well. 00:19.998 --> 00:20.579 [SPEAKER_01]: I appreciate it. 00:20.999 --> 00:27.388 [SPEAKER_00]: John, tell us a little bit about your company and what motivated you to found it. 00:27.622 --> 00:29.185 [SPEAKER_01]: Absolutely. 00:29.245 --> 00:33.011 [SPEAKER_01]: And where it was, where it came from, where it's becoming today. 00:33.572 --> 00:36.857 [SPEAKER_01]: So about 21 years ago, I went to India for the first time. 00:37.197 --> 00:39.822 [SPEAKER_01]: And I was in the HR outsourcing business. 00:40.002 --> 00:43.427 [SPEAKER_01]: And we decided to hire a vendor and do business there. 00:43.447 --> 00:45.090 [SPEAKER_01]: And I've been going for a long time. 00:45.070 --> 00:52.884 [SPEAKER_01]: The business I was in here in the States was that HR service provider or professional employer organization where we do everything for small business. 00:52.964 --> 00:56.831 [SPEAKER_01]: So run their payroll, take give them benefits, pay their taxes, you name it. 00:58.614 --> 00:59.796 [SPEAKER_01]: That company got sold. 01:00.577 --> 01:03.062 [SPEAKER_01]: I kept the people that I had been trying it for five years. 01:03.202 --> 01:07.129 [SPEAKER_01]: I used them with my money, got some friends, and the way we get them, we have a company. 01:07.109 --> 01:33.522 [SPEAKER_01]: It's a day that company employs 600 people around the globe, and we specialize in helping HR service companies or bureaus, whether they be 01:33.721 --> 01:37.960 [SPEAKER_00]: So how is it impacting the productivity and companies? 01:38.075 --> 01:48.731 [SPEAKER_01]: Very much so, you know, I went to AI4 recently in Las Vegas, and the fact that it was thrown out to me was it only 10% of companies are using AI, they're all talking about it. 01:48.751 --> 01:52.977 [SPEAKER_01]: One of the things I wanted to cognate of the deal is, let's be ahead, let's not sit around and wait. 01:54.039 --> 02:04.234 [SPEAKER_01]: The traditional business of business process, Al-Sore, seeing as that, somebody else does the same work for you elsewhere in the world, business process, management, where we're going into the application of the course software. 02:04.872 --> 02:06.234 [SPEAKER_01]: So I'll give you an example. 02:06.714 --> 02:11.500 [SPEAKER_01]: We have a partner that does software implementation for HR system. 02:12.021 --> 02:15.846 [SPEAKER_01]: At the end of the day, everybody goes, oh, I forgot all that paper that's in there. 02:16.006 --> 02:22.434 [SPEAKER_01]: My PDFs, my paystubs, my forums, my INIs, everything I did all these years is in there and I got to move it. 02:22.874 --> 02:24.576 [SPEAKER_01]: In the past, human beings moved them. 02:24.837 --> 02:26.959 [SPEAKER_01]: They took a document, moved to here to there. 02:27.520 --> 02:28.801 [SPEAKER_01]: And we were in that business. 02:29.683 --> 02:33.327 [SPEAKER_01]: Today, through the use of robotics, more so than AI right now. 02:33.307 --> 02:36.994 [SPEAKER_01]: We are able to move large amounts of that data in timeframes. 02:37.054 --> 02:38.677 [SPEAKER_01]: It just wasn't possible before. 02:39.118 --> 02:39.639 [SPEAKER_00]: Interesting. 02:40.160 --> 02:44.829 [SPEAKER_00]: So, I becomes one better now on HR systems. 02:45.030 --> 02:52.885 [SPEAKER_00]: And so, how can these tools ensure that they're being used responsibly? 02:53.050 --> 02:55.296 [SPEAKER_01]: You bring him put him my big points. 02:55.376 --> 02:56.699 [SPEAKER_01]: I try to make him security. 02:57.281 --> 03:04.579 [SPEAKER_01]: We are dealing with bank accounts, so security numbers, information that not necessarily you want running around chat, keep it. 03:05.501 --> 03:08.308 [SPEAKER_01]: What I find with large language models is that. 03:08.288 --> 03:12.274 [SPEAKER_01]: we want to believe they won't hallucinate or do bad things, they might. 03:12.634 --> 03:20.646 [SPEAKER_01]: So we have to draw a real cautious line of what kind of data that is protected and what's touching it, what technology is touching. 03:21.266 --> 03:23.189 [SPEAKER_01]: Robotics doesn't kill it. 03:23.209 --> 03:25.332 [SPEAKER_01]: So it's a little bit clearer in that path. 03:25.432 --> 03:27.876 [SPEAKER_01]: I think the HR industry is struggling with that. 03:28.837 --> 03:31.461 [SPEAKER_01]: In that, you know, the data we have is protected by 03:31.441 --> 03:35.471 [SPEAKER_01]: every government in the world for a bunch of max and laws. 03:36.133 --> 03:39.280 [SPEAKER_01]: I had to comply with that yet because of it at the same time. 03:39.601 --> 03:45.315 [SPEAKER_00]: So what do you see for the future and this technology and how should businesses prepare for it? 03:45.582 --> 04:02.528 [SPEAKER_01]: I think what kind of like gaps are we used to call a gap once I was involved in a KTR data integration company there's the gaps are getting tighter, there's a gap or a person has to be within, that's going to remain, but how much does the technology grab along the way? 04:02.508 --> 04:08.817 [SPEAKER_01]: We're experimenting now with our own AI, and we find that we give it a task, it does it great. 04:09.218 --> 04:10.820 [SPEAKER_01]: We do it the same task a week later. 04:10.841 --> 04:12.783 [SPEAKER_01]: I do it a little different because it's a party. 04:13.204 --> 04:16.970 [SPEAKER_01]: What people don't understand is that, okay, now I didn't do it right because it tried to be clover. 04:18.011 --> 04:19.854 [SPEAKER_01]: These are the things you have people watching. 04:20.715 --> 04:25.583 [SPEAKER_01]: I think a lot of the transaction HR fasts look great, a new guy. 04:25.823 --> 04:27.746 [SPEAKER_01]: You know, hire somebody to fill out a bunch of gold for her. 04:28.227 --> 04:31.131 [SPEAKER_01]: I put him in payroll, I do everything I'm supposed to do. 04:31.111 --> 04:32.173 [SPEAKER_01]: That would be good automated. 04:32.273 --> 04:34.176 [SPEAKER_01]: There's no doubt at all. 04:34.196 --> 04:40.785 [SPEAKER_01]: However, even being is probably going to be in the audit side of it, making sure that they actually get paid on time, they get paid right if not. 04:41.727 --> 04:46.454 [SPEAKER_01]: But it will take away what traditionally PPO's were in the past but become automated. 04:46.874 --> 04:57.490 [SPEAKER_00]: So I would conclude from that then that companies that are not using or implementing this kind of technology will in the end not be as competitive. 04:57.655 --> 04:58.377 [SPEAKER_01]: Absolutely. 04:59.138 --> 05:03.167 [SPEAKER_01]: My father always said, be a head now behind, and that's what I've told my group here. 05:03.487 --> 05:06.333 [SPEAKER_01]: We're getting into the AI business, whether you all like it or not. 05:07.295 --> 05:09.801 [SPEAKER_01]: It might be a little terrifying to my employees as well. 05:10.582 --> 05:14.230 [SPEAKER_01]: But I tell them, imagine we have the same number of employees that we do twice the work.