Name: jeff kuzmich - Migrate_Transforming_HR_AI_07102024_4440329
Uploaded: 2026-02-26T06:25:48.641Z
Duration: 50 min 29 s
Description: jeff kuzmich - Migrate_Transforming_HR_AI_07102024_4440329

Transcript for "jeff kuzmich - Migrate_Transforming_HR_AI_07102024_4440329": Hello everyone and welcome to our Business Growth and Efficiency Series. My name is Rob Parsons and I'm your moderator focusing on transforming HR, the role of technology and AI. So before we get started, I just want to go through a few housekeeping notes. The first thing is all your audio is going be coming through your computer. So we've got some, information here on screen on how to make sure that's going to work correctly. Now I'm going take you through some other important features here. You can download and print a copy of today's content for future reference. We have some additional resources for you to refer to. It's all in the files and resources window, top right of your console. Also, you have any questions or comments during today's webinar, you can send them via the ask us a question window or the ask us widget at the bottom of your console screen. So just enter your question and then, click submit and we'll try to get to these at the end. But we have a lot of content to use, we'll try to fit as many in as we can. Also, note this presentation doesn't constitute legal advice. This is for informational purposes only. And now, I'd like to introduce you to our speaker, Ormat Vance. Ormat Vance is the Senior Vice President of Data, Analytics and AI here at Paychex, where he is responsible for developing and executing the data strategy, including the use of business intelligence, advanced analytics, and AI driven automation to drive both business performance and enhanced customer value. Ormat has a proven track record of driving change and delivering solutions that automate and optimize data to unlock the value of assets, including working at West Hat Management, TD Ameritrade, Fidelity, Sun Microsystems, and Vicor Restaurants. Vance earned a bachelor's degree from Wake Forest University. Beaumont, welcome. Why don't you start by giving us an overview of what we'll be covering today? Okay, thank you very much for the nice introduction, Rob. First off, what I'd like to say is there is a lot of hype about AI right now and has been for the past couple of years. For this presentation, I'd like to just ignore that hype because we're going be focusing on what's practical for our business and especially for human resources. AI really will make HR actions and decisions faster, easier, and more accurate. And we will need to balance tech fueled efficiency improvements with the human touch, and we will be discussing that today. In addition, what we will cover is tech's impact on HR, AI integration plans into HR, anticipated benefits of AI, opportunities and threats, and finally, my favorite part, actionable steps to integrate AI. Then we'll wrap up with a little bit of Q and A and address any questions that you have shared. But first, just a couple of notes. Paychex is not here to promote the use of AI nor are we trying to sell you the use of AI or influence how you use it. We're here just to share information that we've learned and provide some thought starters with relevance to your business. But most importantly, at Paychex we are really focused on our customers and what our customers' needs are. And we don't know what those are unless you tell us. So please share your comments today during this presentation. We will not get to all the questions I'm sure at the end. However, we will read through everything that you submit to us so that we can understand where you're coming from. All right, AI usage and adoption. Welcome to the newest wave of transformative change. And I say that because we have already been through a few. We're still recovering from the transformative change of remote work driven by COVID and Zoom meetings instead of in person meetings. But we've been through a few before that. Prior to that, there was the mobile revolution. And of course, really the big one that is still changing, changing business as we know it, the internet, when it came through that changed how we got information and AI, it looks to be maybe an even larger disruptive technology to business. Now through these big changes, things are almost always chaotic. And so right now AI is very much like the wild west, completely untamed and nobody quite knows what it's going to look like in five years. To that end, there are plenty of people who would like to project what it is going to look like and throw out really big numbers like $7,000,000,000,000 I have no idea if this is too low or too high. But what I can tell you is that AI actually isn't really new. I have been working in the AI field since at least 2009 and it predated me by quite a few years. What has happened recently is ChatGPT and CoPilots have come out and they're much better trained models. They have a much better use case, better usage for the lay person and the press has gone completely nuts about it. So we've seen this huge explosion in the awareness of AI, but we haven't really seen huge changes in the abilities of AI. Those have actually been going on for five or six years right now. One thing I do know is that AI is definitely here to stay. AI has been on a progression for all those years of getting better and better, stronger and stronger and being used in more and more ways. So ChatGPT and Copilot are being used widely in the workplace, very often without any governance or guardrails. And this does pose some risks. AI platforms can leak information. There was a case early in ChatGPT days when coders at Samsung were actually trying to write code using a ChatGPT. And what they didn't realize was that when they were uploading their proprietary code, the code that runs their devices, they were actually sharing that with the rest of the world and everyone else could access it. So we're still have some learning to do in terms of the safety and proper use of chat GPTs. AI however is delivering productivity and increasing employee engagement. There's a lot of excitement and a lot of employees are embracing it. AI technology allows HR professionals, for example, to streamline their work processes. You can reduce biases and improve decision making. So AI is going be around and it's going be a powerful tool for all of us. So how many of our attendees today are using AI? And Rob, can we conduct a poll here? Sure thing there, Beaumont. So we're going to have a quick poll is going to come up on your screen. Want you to hit your selection and then tell me, hit submit and then you can let us know how much you're using AI regularly for your business. Is it every day or you've already adopted it? You're dabbling, you're trying to see what's going on, but nothing consistent or you're just not into it yet at all. It's too risky. You're not ready to adopt it for your business. We'll give you just a minute and all right. So the number one answer here Beaumont is that I've dabbled, but nothing consistent. There's few people using it every day, a few people that are not using it at all. What do you think about those results? I think right now that the use cases are ill defined and what I've seen is a lot of employers haven't really gotten organized yet around defining the best ways to use it at work. I know a lot of people are using it in their personal lives. If we're really being technically accurate, every time you type a text and it predicts the next word that you should type, every time you use Google Maps, every time you're using Zoom and it kills the sound of a dog barking in the background, you're using AI. So whether you know it or not, it's actually a 100% of you are probably using AI. But I'm not surprised we're in the early curve with the adoption phase and I'm actually encouraged to see that so many people are starting to use it at least a little bit. So let's talk a little bit about the advantages of AI and why you should be using it. Well, number one, AI really is great at leveling the playing field. And you know, one of the great things about Paychex is that we really try to help small companies punch above their weight to compete with the larger companies. And AI is a perfect tool for this. So for example, there could be tasks that require 150 people to perform and only a large company could have a department of 150 people doing that task. But nowadays, that task might be able to be completed with AI with maybe 10 people or five or maybe even one in some instance, which means smaller companies can now compete with the big guys if they leverage AI properly. But I think in order to do this, the first thing we have to do is sort of reframe how we think about AI and about data. And this pivot is required in order to understand exactly what AI is and isn't. And the best analogy I can think of for this is this. Imagine that you have a librarian, very special library, let's call them magic librarian. And that librarian can read every single book in the entire library and remember not only everything that he read, but exactly where he read it. So for you, if you go to the library today, you might use a computer and you would search, do a word search and you might find some books or some documents that might have the answer. Then you'd have to go read them and see whether or not they had the answer. Very, very time consuming. But imagine if you could go ask this magic librarian any question you wanted and he could not only give you the answer from all the books he'd read in the library, but tell you exactly what the citation and quote was and where to find it. That's essentially what AI is. And if you think about it, this is a super, super powerful time saver. I mean, the librarian is a lot faster than doing the research yourself, but there's a downside to it. Let's assume also the librarian can read everything and memorize everything, but can't tell whether it's right or wrong. So if a lot of the books in the library are incorrect, then he's going to give you incorrect answers. And if half of the books are correct and half of the books are incorrect, he will give you a statistical mixture of right and wrong answers, which you will know as hallucinations. That's what an AI hallucination is. And a lot of the models that are trained today are sort of like that librarian who read the entire internet. And if you've ever spent time on the internet, you know, if it's 50% correct, then I'd be really happy. But there was a lot of bad information on it and AI is mixing that bad information with good and creating these hallucinations. But one thing to remember here is that there is a big change in what the AI is processing. Computers have processed data for a very long time, but when we thought of data, what we were thinking of was numbers. What AI is able to do that computers really weren't able to do until recently is process human language. And it's important, especially for the HR profession, because last I checked, don't communicate in numbers nor do they communicate in binary. We communicate in language. So in human professions and human interactions and in human organizations, the important thing is human language in the way we communicate. Therefore, human resources is very well poised to be involved in this big AI revolution that's undergoing we're undergoing right now. So let's dive in and see how leaders are currently using AI. So interesting to me on this survey is that it is smaller employers that really seem to be the ones who see a significant opportunity with AI. And as I said, that makes a lot of sense because AI really helps small companies punch above its weight. But also for larger companies like 50 to 99 or even in the hundreds of thousands, AI is very good at handling massive amounts of information and data and it is a great efficiency multiplier. About 85% of the business leaders we surveyed say their organizations are using AI and less than 10% are concerned with AI risk. Now this is a huge, huge switch. About five years ago those numbers would have been the other way around, but they're using AI to automate workflow, grow sales, manage business intelligence and analytics, screen resumes, which I'll talk about more later or applications and as a virtual assistant, which is I think the most common use you see, which is a chat bot or a chat GPT type of application. For the small companies in particular, they're looking at first to support customer service and experience, that's where chatbots come in. We're also using also for business intelligence, AI is great at spotting patterns and things, but the big one is they're looking to use it to screen candidate resumes. That way you don't have to hire an HR manager to do this and for anyone who has ever gotten three fifty resumes submitted for a job posting and had to read through all of them, you will greatly appreciate a machine that can go through all three fifty in a couple of seconds and not only screen them for appropriate fit, but also enter the data into the ATS system. So what about the specific benefits to HR besides that? Well, what we are being told by HR leaders is that AI is actually saving them about seven point five hours a week. So essentially one full workday a week, which I assume means everybody gets four day work weeks from now on. So three day weekends, hooray everyone. Or we could use the extra time for increased productivity. So on average, about 79 of leaders feel that AI also helps reduce bias. Now this is another surprising statistic to me. We'd asked the same group probably five years ago, it would have been something more like 1% believe that AI reduces bias and the rest thought that it increases bias. And this is a really, really important point on AI. Like if we go back to our library example, I said if the librarian read bad books, they would give you bad answers. Well, imagine if the librarian read a library of books that were all written in the eighteenth century. Do you think that the answers you got from that librarian might be biased? Well, they would be. They would be because the information that the librarian read was biased. The AI engine itself doesn't actually have opinions, right? But the real problem, and I think what people are starting to realize is humans do. It's hard to get bias out of humans. The best example I can think of is if you've ever run into somebody either in a work setting or in a personal setting and they remind you very, very much of a family member or an old friend or heaven forbid, they remind you of an ex. And when you're talking to them, you know, they're a different person, but they remind you in their mannerisms and look so much of somebody for whom you have very strong feelings that you just can't shake that feeling. And if it was a bad X, then you will not feel great, warm fuzzies about this person. But if it's something you may actually give them too much of a benefit of the doubt and be highly biased towards, you know, what your opinion is about them. The great thing about AI is AI has never had an axe. AI doesn't have family and it has never met anybody. AI can only read the information that is fed. And so therefore, if you put in unbiased information, you will get unbiased results. If you put in biased information, you will get biased results. And the beauty of AI in these circumstances as well too, especially in HR, is that you can train it and teach it to look at just the facts. So let's look at some AI uses in the HR processes. Even though AI has advantages, it's not going to replace the HR function. I just want to get that clear upfront. But it can add a lot of efficiency and help streamline routine processes. It's really interesting to see what HR leaders are using this for. Top one is automated candidate screening and recruitment. Again, this gets back to the idea of having to go through lots and lots of resumes, either searching through them on the web when you're doing an active search or going through the resumes that have been submitted in a more passive job board posting search or something like that. This can cut the time by, I mean, but by at least, you know, a 100 fold, it takes seconds for AI, but it takes days or maybe weeks for human beings to do. But it's also being used for employee communications such as AI Copilot, handle simple queries from employees. One really great use we're starting to see is handbook generation. Not only can AI platforms generate good compliant HR handbooks, but just like my librarian friend, they can not just read an entire library, they can read all of the state, local and federal regular regulations every single day. And if there's ever any change that impacts the handbook, they can actually flow those changes through rewrite the handbook and keep it continually fresh and updated so that you're always compliant. I think this is an amazing breakthrough. I think everybody's going to be using these within the next six months to a year. In terms of talent acquisition, AI has streamlined the processes, posting jobs and reviewing resumes. It cuts time in recruiting by automating all the manual tasks, including right now I've seen AI that does everything from creating the job descriptions, writing outreach, outreach texts, as well as emails. And it can also take the information that you get from resumes and enter those into ATS systems, which is absolutely phenomenal. Other ways AIB is being used include performance analysis and management, engagement surveys, payroll processing, and one of my favorites predictive analytics for talent management. There are new solutions coming as well too. I can't share details, but I can see on the horizon coming very soon, candidate search tool that contains the resumes of every single working adult in The United States. In fact, I know of some databases right now, there are currently 167,000,000 working Americans and I've seen databases that have over 200,000,000 working American resumes in them for search. The beautiful thing about AI is it doesn't just do word search, it can actually do a complex search that's looking all the skills, backgrounds, size of companies people have worked for, educational background, every single dimension you can think of can be contemplated and return highly qualified candidates literally within seconds, as opposed to posting a job and maybe waiting six weeks before you close the position and then reviewing the resumes. And these platforms can process all of the resumes and do all of the outreach, all at a touch of a button. So it's just AI end to end all the way up to the point where it's a human doing an interview with another human being. And this I think is going to be a radical change to the industry. Let's take a look for a second at the broader uses of AI across business. So businesses tend to be using AI in a few major areas. The most obvious one is automated workflow. RPA and, you know, robotic process automation has been going on for a long time. And this is essentially ways to automate manual tasks. AI has just turbocharged that. It's like a 1000X improvement in what RPA used to be able to do. So workflow processes like ingesting documents, entering data, listening to conversations and entering the data from the conversations into a CRM or an ATS is now being rolled out all over the place. It's also used to grow sales. AI can spot patterns, so it can not only spot patterns in terms of prospecting, but can also spot patterns in salespeople sales pitches and how they talk to clients. And you can take the patterns from highly successful salespeople, find out what the commonalities are in those with AI and then use that as a template to teach new salespeople or less successful salespeople. It's also being used in business intelligence and analytics. While AI is unique in that it can handle language, it also can really handle numbers well and it can spot patterns very well. So if you're looking for things like retention insights, turnover reports, or diversity and pay equity, AI is going to make it short work of being able to look at massive amounts of data and spot patterns that humans might miss. Business leaders plan to implement AI a lot over the next twelve months, largely using AI to support customer service and experience. This is a new area where we're seeing a lot more growth. That's going to come into the fore. And also a really great use for this is to strengthen operations and data security. Scammers and spammers were the first early adopters of AI. They are using it right now to make money by scamming people. And so you're fighting against a machine and the only way to beat a machine that's trying to scam you is with a machine. So new AI cybersecurity platforms are getting better and better and making our data more and more secure. Guess, but the question is, AI does the AI machine beat or replace humans? About 76% of HR leaders don't believe that AI will replace their roles within the next five years. I think that number is going to get higher as people get more comfortable and used to AI. And the reason is really very simple. Human beings, we are really feeling machines more than we like to admit. We make a lot of decisions based on feel, not data, even though we try to use data to keep our decisions correct. AI, however, is a thinking machine. AI cannot think feelings like love or sorrow or empathy. It just simply can't and realistically it's not even on the horizon that it ever will be able to. AI is really a tool to assist humans and not the other way around. So AI is not going to replace wisdom, intuition, expertise, experience, or certainly not empathy. How can it feel the way you feel when it doesn't feel at all? And AI will never be able to actually have empathy. What it could do is read about empathy and mimic it, but it'll never actually have it. And another really good example why AI cannot replace human, let's go back to our librarian for a second. Imagine our librarian was reading a musical library and he had ingested every single song and read every single book on musical composition, every single book on instruments. It would know a lot about music. That librarian could tell you a lot of things, but the librarian still can't play an instrument. So AI is great for regurgitating information and for organizing information and organizing data for you. But it doesn't mean that it can actually do the things that humans could do, like play an instrument. Knowing things isn't the same as being capable of doing things, but what it will do, AI will free up time for manual tasks to allow us to focus more on our culture, our people, and elevated strategic level of input into the business. It basically frees us up to do the things that we do best as human beings. So let's take a look at what should stay human led. Interesting numbers here. 11% of employees would like AI to be a little bit more transparent. And I think that is reasonable. And I think that AI has been increasingly transparent over the years. This next one's very interesting to me. 41% of employees want less AI involvement in HR decisions. Decisions is really important work here. AI cannot and should not, never should make decisions. Humans make decisions. What AI does is it provides the information and the input in order for the human to make decisions. And if we look at Google sort of as a template earlier, what Google did is it allowed us to find information we needed much quicker. We still had to sift through it. We still had to figure out what made sense. We had to figure out what was on point, but it got the information to us faster. So when we did make decisions, they were better informed, right? So looking at HR and our surveys, which aspects do employees think should stay human led instead of AI driven? Well, conflict resolution and employee relations for example, obviously makes absolute sense. Personalized employee counseling, again the empathy comes in here, AI will never be able to have empathy. And so counseling really has to be human to human. And then finally a higher level strategic planning and decision making. AI is not sophisticated really to do that type of thing right now. It can write lyrics in the tone, in the voice of James Baldwin very well, but it can't necessarily look strategically over multiple years and come up with good HR policy. So let's pause here for a second and get your participation in another poll. Thanks Beaumont. And once again, a poll is going to come up on your screens. And once again, just mark your response and hit submit. We want to learn now about the risks that you perceive. What is the greatest risk of AI and specifically in HR? I see a lot of questions coming in on different AI tools and different use cases. What do we see as the risks? Is it trust and transparency? Bias? Is it the replacing of jobs? Is it inaccuracies and misinformation? Security and privacy? We know that's a big deal with data in general. Or even copyright and legal issues. So just I'll give this one just a minute because there's a lot of options here. What is the biggest risk? So, I see trust and transparency at nine, bias at six, replacing jobs at 13. Inaccuracies and misinformation is 37, basically 38% Beaumont. Security and privacy at 30%. So, inaccuracy and privacy, two biggest issues showing up in our poll here. Actually, that's really heartening because this is the two that I would have chosen as well too. As I mentioned, a lot of the AI platforms that are out there have been trained on public information. They basically ingested everything they could find on the internet. And that means that a lot of what they've got is wrong. So hallucinations and accuracies are really rife on publicly trained AI. What we're starting to see is companies are training their own LLM large language models on their own data so that they have control over what the answers are and what the data is that goes into the AI. And with those, there's a lot less of this problem with inaccuracies. So like many things, it's garbage in garbage out. Security and privacy also really important. When I mentioned Samsung, when you're using public AI, public chat GPT or AI or large language models, you always have to be well aware of whether or not the platform that's using that is ingesting your data, making it part of the training set and then opening up that information to anyone else who asks questions. There have been a lot of examples of this. And again, that's why a lot of companies are going to their own models that they built on their own data that are tightly controlled within the confines of their business. And they still leverage the training that occurred on the internet in terms of understanding human language, but the data that they use and the responses that they give are all tightly controlled. And I would strongly suggest people start thinking about that. All right, so let's take a look at some of the risks and limitations of AI. Let me just throw out a couple of recent examples for you of real world legal issues. So number one, August 2023, the EEOC settled its first AI discrimination related lawsuit where an AI powered hiring selection tool automatically rejected women applicants 55 and all men 60. Another case, ACLU recently fired a clear warning shot to employers by asking the FTC to investigate a personality assessment test, a video interview tool, and a cognitive ability assessment screening device, all powered by AI because of alleged discrimination. So these are two different kinds of cases. The first one has to do with an AI model that I will almost guarantee you was fed data that did not have women 55 or men 60 as examples of successful candidates. Remember, if you put that information in, you'll get that information out. If you feed in, if you're teaching an AI to look for a successful candidate and you only give resumes for men, it is going to be highly biased against women. So it's very important that you put a representative sample in your training of the AI engine in order to get an unbiased result from the AI. You put in a non representative sample, you're going to have exactly this problem. We're probably going to see this come up again and again. The second one ACLU is really looking at things like personality tests, video interview, and cognitive ability assessment. I have no inside information on this one, but again, digging into it, what I would take a look at is how the model was trained when it's looking for cognitive ability, how is it defining what cognitive ability is and what use cases was it used to train them? Because AI itself, I'll say this over and over again, cannot be biased, but the training data, if it's biased, will give you an AI, a biased AI model. AI reads books with bad information, it's going to give you it's going to give you bad answers. It's really that simple. So always look at the data and the training that went into it and to understand whether or not the model is going to have bias or not. And here's a tip, don't look at the AI. Just don't look at the AI. Doesn't matter which AI platform it is. What really matters more than anything else is the data that the AI is referencing. Okay, now let's talk about how to choose AI tools. So first off, remember, AI is primarily a productivity tool. It automates things. And what I see, problem I see all the time is that people start with a tool and then go around looking for what problems it could solve. And Abraham Maslow, I had great insight into this long time ago. He said, all you have is a hammer, every problem begins to look like a nail. And he's absolutely right. You don't start solving problems by starting with a hammer and trying to figure out all the things you can do with a hammer. Clunk somebody on the head, build a birdhouse, I don't know, tear, knock boards apart. You do a lot of things with a hammer. The better way to go about it is you start with the problem you're trying to solve. I need to build a house. Then you say, what tools do I need to build a house? If you start with a problem, you will not be led astray. If you start with a tool, I guarantee you it's going to go off in a of bad directions quickly. So how do you do this? Well, first what I would suggest is you audit your company and look for any workflow processes where you see bottlenecks or slowdowns that are due to manual work. The classic one is that you've got a lot of systems that are processing data and they give you a report and then a person takes the report, does something with it and then manually enters data into some system, CRM, ATS, computer system, spreadsheet, anything. The process can only go as fast as its slowest component. So wherever you have a manual process, you probably also have somebody who's dissatisfied because most people do not like doing manual work, open repetitive work over and over again, but you're going to find a slowdown and you're going to see a great improvement in efficiency if you fix that by putting AI into that spot and having it handle that repetitive manual type task. Then after you've identified the tasks, then go looking for the tools that can solve that. I guarantee you there are probably tens, maybe hundreds of thousands of AI tools out there right now that do all kinds of different things that are all vastly different, Very hard to navigate that, but when you have a problem in hand and you say, hey, I'm looking for document ingestion. I want documents brought in, scanned, and the data put into my ATS. There are a ton of platforms that do that very well and then you can narrow the field very quickly. Then finally what I suggest too is developing an AI strategy and policy. One study found that 53% of workers haven't told their companies that they're using AI because they're afraid they're going to be replaced. And give you a personal anecdote, In the days prior to AI, this was back in about 2007, there was a young man who worked in finance, really smart guy, really junior. And he had used code to automate his entire job. Every report he had to do was fully 100% automated and he was doing so little work that he got very, very paranoid and worried. And he was concerned that his boss was in a firearm if he found out that he wasn't necessary because why have him when you just have code doing all the work, right? So he actually erased all the code and started doing things manually again. I found out about it. I hired him in my department, promoted him and put him in charge of automating all of our processes and he drove just crazy efficiency and this was before AI. But the real point of the story is his fear was real. The boss he had, if he had known that he had automated his job, that this young man had automated his job, he would have fired him for sure. And unfortunately there's still that sort of anxiety out there. So it is really, really important that your AI policy address this head on and that you're very, very clear about what's inbounds and what's out of bounds and what type of AI use you encourage. You want to be very clear on this. My second little big piece of advice is to be very pragmatic. When you're choosing AI, don't try to solve everything in the world. Do not try to boil the ocean. Focus on easily obtainable, easily solvable problems that you can solve with AI today and that you can deploy within a few months. Anything that's going take multiple years is going to be very difficult to sustain until you have a lot of success under your belt. So I'd say as you're beginning, look for small tasks where there's already an existing AI engine that's been well tested and proven that you can implement quickly and you can start to build a track record of AI success and you can also get some experience. All right, and let's go to the next slide, Rob. All right. So actionable steps. Technological innovations and advancements are accelerating at such a fast pace right now. It is getting really hard to keep up with them, but they are getting better and better literally by the month and you want to be in the right position to embrace them. So here's the things you can do to start right now. Number one, start the conversation with your IT department and with your data science people. These are the folks who are watching this industry and they understand what the tools are and what they're capable of. They're essentially sort of the library of solutions. They are the keepers of the tools, if you will. And they can tell you very quickly what is possible and what's not possible and what's available out in the market today. Secondly, for HR in particular, try to stay current on the tools for your industry or HR. And one of the best ways that I've done this over the years is if you go to a conference, walk the booths because all the small companies that got new breakthrough AI, new breakthrough solutions, things that you haven't heard about yet that the press isn't covering yet, they're going to be there and they're going to be willing to tell you about it. It's going to take some time, I understand. But if you walk through even one conference and go through all the booths, you will have a better understanding and lay of the landscape for all the solutions available to you today than almost anybody else, even people in the AI space. You really want to become experts at what the art of the possible is. You want understand what's coming, what you can do and what you can't do and then use those tools to be able to create the type of HR department that you want. And finally, and I'll say I'm going be saying this a lot, so please don't get tired of me saying It's all about data, data, data. AI tools are only as good as the data that you feed into them and that you train them on. So it is important that you start taking responsibility for understanding the data that is going into the tools that you use. Make sure it's correct and reliable. Make sure you have active data governance that you're not using data that you can or ought not use and that it's safe and secure. Make sure you have someone on your team designated who understands the regulatory restrictions around data. This is changing almost as fast as the pace of AI and you have to stay up on these in order to understand how to stay within the regs. And finally, make sure that this person is designated and that they are keeping an eye on how those laws are changing and can report back out to the rest of the group because employers are liable for the information that they rely on when they use AI. If you're feeding biased information into your AI engine, the employer is going to be responsible for the outcome of that. And biases in hiring are the big one that I always worry about. You want to make absolutely sure if you're training your AI to look for a good candidate, when you're describing what a good candidate is, make sure you're describing that candidate that is what you really want and that is within your DEI and your expectations for the HR policies. Alright, so start cleaning your data and manage your data right now because you are going to need it no matter where you go on the AI journey. Alright, so what we've covered today is a lot. First off, you have to balance the tech fueled efficiency improvements of AI with the human touch. And I really want to emphasize this. Even though we're using AI, just like when we're using the Internet or we're using computers or anything else, companies are made of people and human resources here are people specialists. So keep the human in human resources. Achieving success with AI really requires creating a work environment where employees feel positive and supported. So one of the best ways to do this is to be very clear and explicit in what the guidelines are, what's acceptable, what's encouraged and what's discouraged. Achieving success with AI requires, I'm sorry, transparency and guardrails absolutely essential for doing this. And remember, humans are making decisions, but AI can give you sort of superhuman or turbocharged abilities because it provides the information that you couldn't access before. Just like Google search did except for this is even more powerful. And finally, get started now in cleaning up your data so it's usable when you actually need it. And one final note here, as I said earlier, we really look to hearing from our customers in order to provide the solutions that best serve you. I particularly when I design software, I always start with the end user and what they need. And then I design the software backwards from that. So when we're designing AI solutions to help you, I'm really going to be looking at the comments and input that you're giving me from today. And that's going to directly inform what we're producing as we go forward with our AI roadmap. Fantastic. Thank you so much, Beaumont. That's a lot of great information. And it's funny, I was tracking the questions as they were coming through. You know, Joe Foxworth was asking about garbage in garbage out and you stressed the importance of data. And we had questions around, what are some specific applications and you got to show me examples of how to use them and don't CRMs already have it? You pointed out, there's a lot of tools out there. There's thousands of tools out there that already have AI built in. We can't show you how to use it. What we can do is give you that roadmap for how to approach AI in general. Be It's in everything that we're doing soon. So thank you for being on top of that. I do have a few specific ones that came in. This one was from Cameron, but also we had Kelly Shanahan also. Kelly asked specifically, will it replace recruiters and HR jobs? And Cameron just asked in general, how will AI impact jobs? Really good questions and this has been an area of increasing interest for me for the past, four or five years. I think first off, no, it's not going to replace recruiters because the decision maker, the person who still has to figure out who is the appropriate candidate at the end of the day still has to be a human being. What it's going to do is greatly speed up your ability to find candidates. And like I mentioned, there are some things coming on the horizon here where AI will be able to search through every available candidate quite literally in the world, certainly within The United States and find exactly the constellation of skills and background that a recruiter would want. But having done that, the recruiter still has to talk to the person. And as you all know, when you're hiring skills and qualifications and everything matter a lot, but cultural and personal fit, how they're going to work on the team, how they're going work with your own culture and environment. AI is never going to be able to suss that out. That's really going to be up to recruiters. I think what it's going to do is it's going to highlight the importance of good recruiters and people who want, who can read people well and who can perform interviews well and make good assessments. But what it's going do is cut down all of those interviews that you get three minutes into and realize it's just not gonna work because you had a word search and they happen to have something on the resume, but it's the wrong use of that thing. And so they're not gonna work. A couple other thoughts on that. In terms of impacting jobs, this is really for the past, I don't know, five, ten years maybe, the big concern has been, is this going to make everybody unemployed? Is AI going to replace jobs? And when I look at history, for example, if you look back at computers, computers have been around since the sixties and they've been doing business work for us. And what they're really good at doing is like accounting type work. They do edit addition subtraction, they organize data, they handle massive amounts of data And since the sixties, I mean computers have gotten crazy good. But right now there's a shortage of accountants. But computers never eliminated accountants. Accountants are still absolutely necessary, but what's happened is their profession has become much more about the art of accountancy and the decision making of accountancy and not all the manual work. I mean, there was a time, and I unfortunately remember this time, when people would sit there with a 10 key and they would run calculations and they would get a number and they would handwrite it into a spreadsheet and then hand tabulate it with their 10 key, right? We have made huge leaps and bounds since then, as I said, really what's happened is we haven't needed a lesser need for accountants, what has happened is there has been an explosion in the need of new jobs that we never thought would have existed, especially in the technology sector. I mean, you know, coders and web dev and mobile app designers, There's all these new professions that we never ever dreamed of. I mean, even going back three years, there were no prompt engineers. Right now, of the hottest jobs out there is prompt engineer, right? So how it's going to impact jobs? Somebody said it really well. They said, AI is not going to come and take your job. A person who knows how to use AI very well is going to come take your job. So it is both creating a little bit of pressure on employees to be able to learn these new skills, but it's opening up all these new career paths that they may not be aware of. And I think one of the great roles that HR can play is when they're counseling employees to sort of have them pick their head up and look a little bit more broadly at the new landscape and say, you know, hey, where are your propensities? What gives you joy? There's some new areas opening up in direction that you didn't know existed. Let's take a look over that way. So I think it's actually going to be very, very positive for employees kind of in the way the tech explosion was. I for one am very, very glad that there is such a thing as a senior vice president of data analytics and AI now. That is a position that did not exist five years ago. So personally career wise, it has been an absolute boon largely because I was just keeping my eyes open and seeing this thing blossom before me and preparing myself for the new world. And I would suggest that that's what we tell all of our employees. That's great. Yep, yep, we got another one here. This is from Rachel. I suspect it's because she's at a paychecks event, but Rachel wants to know, can AI help to make sure I'm paying my staff competitive rates? And we know that's just such a big deal right now, with the challenges around hiring and keeping good people. We know competitive pay is a big deal, don't we? No. Yeah, absolutely. The world's really changed, especially with New York law now where you have to publish pay bands when you're putting jobs out there. It was always to me always seems back in the old days when it was you get fired for telling people what you made and it was all a big secret. Would this seemed like it would be absolute chaos, but I think the world's going bring it to us whether we like it or So there's two real problems that you face when you're trying to figure out competitive pay. One is job bid. If you have two jobs with radically different titles and especially when you see this, it happens within companies. I've tried to ban jobs within companies and, I was sort of developing some early AI to do this back in the day. It was so hard when you had a person as a director in one group, but is considered ahead of in another group. Everyone's using different nomenclature and sometimes they're using different pay structures. But big time when you're trying to look across companies, a vice president in banking isn't the same as a vice president in manufacturing. They're very different levels. But because AI can process so much information, I have actually seen some AI platforms that now automatically do this job banding and have solved that problem because they've just ingested every single job and they've figured out the commonalities between them and they can just sort of auto ban them. So that way you at least know what you're comparing like with like. So that's problem number one. Problem number two is what is everybody else paying? And we used to do these job surveys, you know, of competitive companies. I never trusted that the data was right. They were very small sample of companies and a lot of it was self reported. So it wasn't actual data. I can tell you that there is a product coming on the horizon that has seven fifty million market data points and coupled with good job ending, you can query this system and it can actually tell you exactly where you stand and it can not only where you stand in the industry, but where you stand regionally in the industry and where you stand regionally in the sub industry of the industry so that you can start to understand that. And in some cases, these systems are actually proactive and can go out and do these searches for you all the time. And when you get a little bit out of whack, it will send you a note and say, hey, this person is under underpaid. Here's what the range is with your company, with your competition. And then it's up to you, the HR manager to decide what are we going to do about that. You may want to match it. You may not, but at least you're going have to be armed with the information to know exactly where you are and not get these surprises where high potential employees run out the door for incremental more pay that you would have matched had, you know, right? That's such a great example of as you mentioned, the heavy lifting, the manual work that AI can take care of. It really is. Impressive. I know we're over here, Beaumont. Hopefully you don't I've got one last question here from Jeff that I thought was really interesting. He wants to know how does AI help with career advancement? So from the employee side, where does AI come into play? I guess it probably a couple of ways. One is like I mentioned before, it is offering all kinds of new paths. Whatever career you're in, you start asking the question, how can I leverage these tools, the best practices with these tools to get better at what I do? Then it is going to give you a real advantage over folks who aren't doing that. And like my friend, his name was Will, by the way. Will, if you're listening, hope you're doing well, man. You're a genius. Will was learning a lot of new skills in coding that weren't common within financial profession. He was most financed guys are really just sticking to spreadsheets. He was also learning a lot of coding stuff. It gave him this double skill set that was very, very rare and made him a very, very valuable employee at a time when we were going through a lot of rapid change in our industry. And so I'd say like, a real opportunity for you here. The other way it can help you out is there are AI tools that look for jobs, look for opportunities and can search in much, much more nuanced ways than the word searches that we're used to in the past. And so if you're a career minded individual, you can start to do a scan the entire universe of all jobs, all things that could interest you. And you can start to see what is possible, what's happening, what new jobs are emerging in areas that I'm interested in. And so it puts a lot of the onus on the employee, but I think it's always been there. What's happening is you've got new tools that can sort of supercharge your ability to basically process all the information that's happening and do your job both more efficiently, make you more competitive as an employee but also can help you scan the horizon and find new career paths that you didn't know were opening up. Ones you may love, ones that may suit you much better. And so that you can, and you can take those and have your career growing out, you know, share a personal anecdote real quickly. I started off in insurance. I was a risk manager years ago when I saw AI coming on the horizon, I got into data science and there were all these new opportunities opening up. There were no chief data officers yet, no chief analytics officers, none of that, but you could see that the world was shifting and going that way. And so what I started doing is really learning all the techniques and learning the skills for this sort of new and emerging type of discipline. And especially when AI came, I just really poured a lot of my personal time into it. And that actually made all the difference in my career. The past fifteen years have been a wonderful ride and I'm happier than I've ever been because I've constantly been doing something new and challenging that I love and I've just been following my nose on all these absolutely new paths that never existed before. So I think it is a huge positive for anyone who's career minded. That's excellent. That's excellent Beaumont. We're at the end of time. Thank you so much for sharing your time and insights today. Just really great information Beaumont. Thanks again. Great. Thanks Robyn. Thank you everybody for attending today. And before we close, I do have one final poll for the audience. You know, as Beaumont mentioned, there is a human element to AI. If you'd like to talk with a paycheck sales representative about getting HR support for your business, get that advice on the human elements of AI. Our HR professionals are ready to help advise you on paths forward for getting good information, reducing bias, leveraging paycheck's technologies to get the most out of them. Go ahead and answer yes if you're interested in getting that kind of HR support for your business. And thank you everybody for your time and attention today. Now take a moment to complete the brief survey that's going to pop up when we close, helps us put on better events for you. And be sure to click the button on screen we've illustrated here if you'd like to review your HR needs with one of our professionals. Thanks again, and have a wonderful day.