Episode Transcript
[00:00:07] Speaker A: Okay, we're beginning to get ready for 2025. I hope you're having a nice holiday break. And I want to give you a couple things to think about. And you will hear a lot more about this in about two weeks when we launch our big new study on AI called the Rise of the Super Worker. And I would say there's three big things that are going to be happening next year. The first is these Intellig intelligent agents are going to be ubiquitous and we're all going to have agents like Galileo that will be there to support us and talk to us. By the way, I'm going to give you a demo how you can talk to Galileo in a minute. And these things are going to be incredibly useful, incredibly powerful. And you, and we, and most of us are going to spend time training them, putting our company policies into them, adding information about programs, onboarding, pricing, training, et cetera, into these agents to facilitate the productivity improvements and training and upskilling of our teams, both inside HR and outside of hr. And if you think about all of the HR issues that we have to deal with, from employee relations to regulatory issues, payroll compliance laws, legal issues, harassment, claims, diversity, on and on and on, many of them have regulatory or legal underpinnings. There are best practices and maturity models. There are vendors. And that information, which you learn over many, many years in HR is going to be available in tools like Galileo. That's certainly what we're doing. And you're going to build these things yourselves. You're not only going to, you know, license vendor products like ours, but you're going to build on top of them to build these increasingly intelligent systems for you as an HR professional and for your employees. I'm going to give you a demo of how you can talk to Galileo in a minute here. And it'll just give you a sense of how enormously big this is going to be next year.
Number two is we're going to be doing a lot of the same thing for our peers in the rest of the business. So all of the engineering organizations are going to be using AI to build code. All of the sales departments are going to have AI agents train salespeople and possibly improve customer and client interactions before the sale. Customer service organizations and call centers, of course, are going to have AI bots to front end the employee experience and of course train the agents themselves. Finance departments are going to be using AI to better analyze data about, you know, the relationship between profits and costs and various other activities going on in the company. And this is going to just be everywhere. Every single part of the company is going to be going through this. And what the implications will be is not only training people how to use these tools and managing the tools and doing the IT management around them, but changing the job roles and the job titles. So you're going to have this opportunity to participate in job redesign all over the company. Now we're starting to do research on job task redesign. We call it productivity design. Productivity work design. You'll see this in the report that's coming out in January. And I don't know if it's going to be something you can do mechanically, but the process that we've used and the process I think most companies can use is to literally sit down with your line leaders and your teams and map out on a whiteboard. And you're going to have to do this in person, I'm pretty sure. What are the steps that we go through to process a claim or take an order or close a deal or whatever it may be that the business team does? And then look at that visually and say, where can we apply the AI agents to streamline this? And then look at the agents that are coming off the shelf from vendors or the more open, you know, tools like ours or others, and then design a series of improvement practices into these AI platforms. Now, maybe three, five years from now, there'll be off the shelf platforms that have all this built in, sort of the way ERPs were originally developed, a little bit like that. But this isn't going to be like erp, because these are going to be programmable. And I would imagine that in 2025, we're going to get tools as easy as Excel to program these agents so we can teach them. You know, in our company, when somebody does this, we want to do that. And when we run into this condition, we do that. And when we run out of inventory, we want to do this. These will all be programmable, and you're not going to have to have software engineers do this. So that's going to be another big area of hr. The third is the organizational cultural dynamics around this. And you'll see this in, you know, a lot of our research all year. Last year, the dynamic organization research, the elevating equity research, the PAY research, the pay equity research we've done, and the L and D research is about to come out that we have to move people and change roles and rethink pay and rewards much more quickly now, because the minute an agent comes in and changes a job, you've just changed that particular person's role and potentially their salary or their ability to hire and their even their title. Now I'm becoming, becoming less and less enamored with job titles over time. I think they're important to have functional titles like you're a research analyst or you're a salesperson or you're an engineer or whatever. You know, there's sort of functional, but the specific title about what you do in that job probably needs to disappear because you actually may do different things in 2025 but in the same role that you did before. I think we have to kind of free ourselves from the functional definitions of jobs and then get more into the higher level and then we have to accept the fact, and this is certainly my opinion and some of the most prominent economists at MIT have come to the same conclusion that most of these roles are going to upgraded, not downgraded. More routine roles are going to go away and we'll all have to the ability to lever leverage rather the expertise of others with these agents. Now that is not to say that an agent will do the work of a human. I don't think that will happen. You can go to YouTube and watch a video on how to build a cabinet and you can buy an electric drill and a band saw and a router and all sorts of tools to make a cabinet. But that doesn't mean you can make a cabinet.
The building of the cabinet is, you know, the artisanal process of understanding how to use these things, these skills, rather these expertise areas in the particular problem you're trying to solve. So when I think about sales, financial analysis, research, customer service consulting, leadership management, the AI is going to make it easier to do that, but we're still going to have humans doing it. You know, these reasoning models are not that smart yet. If you look at what's been going on in the AI tech, you know, LLMs which are basically stochastic talking and speaking and generation machines don't know how to do logic. So there's another generation of tools which are called reasoning models. GPTO is one of them. And then there's stuff in Gemini from Google and others. Well, reasoning is very, very different from language modeling. So the reasoning engines are not very good yet. So this idea of taking a whole bunch of data say about your company. I've just been doing this in our company and looking at it and making conclusions about what's really going on and what we should do next. AI is not going to be able to do that. I mean the AI is not going to teach it's not going to close a deal if you're a salesperson. It's not going to resolve a case completely. Um, it's just not. I'm not saying it won't do that. Maybe sometime in the future. And even autonomous driving, which obviously we haven't quite achieved yet, is sort of a mechanical thing. It's going you from point A to point D. There isn't that much judgment required. There's a lot of strange use cases. So we're going to have humans, what I call superworkers, upgraded a lot in this coming year. And this all begs the question of two things. Number one, your familiarity and comfort with AI. And I'm telling you, you got to get your hands on tools like Galileo or whichever one you decide and really, really use them a lot. The research report that we published last month, this month, called the Hundred Use Cases on Galileo, I really urge you to read it. Forget about the Galileo part. It's a hundred comprehensive use cases for AI agents in hr. And they will give you great ideas on things you can do in your own company, your own business function, your own HR function. And the second thing that is critical to the next year or 2 is systemic HR. Because once we're into job redesign and organizational redesign and massive changes in productivity and superworkers, we can't operate HR as a bunch of COEs. The service delivery model or service delivery identity of HR is absolutely going to change. You're going to have to be more consultative and more integrated. So all the things we've been helping companies with on stitching together these various practices of HR are going to be critical. And then of course we're going to spend a lot of time on the tech stack of HR itself, which is changing very fast. All of the big vendors are trying to add agents on top of their tools. The medium sized vendors are trying to jockey for position, for specialization roles and learning and development, recruiting and comp and other areas. The data providers are becoming more and more important because without good data, these systems aren't that useful. And then the technology vendors are underlying this, looking for whether they should focus on HR or not. Most of the tech vendors aren't really focused on hr, they're just providing technology platforms. And then there's this kind of open question of will the agents be able to manage people, Will they give you developmental feedback? Will they serve as a coach? I think there's going to be really good applications of AI in training and education for sure. We're, we're actually planning on launching an AI version of our academy this year. But I don't know. And I think the jury is out on whether AI is going to be a management coach as if it was a human. But I think you'll be talking to it and asking it questions regardless because it's able to answer a lot of tactical questions and look things up and find things that you couldn't do before. More to come on this now. Let me take two minutes on Galileo. Galileo is doing extremely well. We have a whole bunch of new features coming out out in the next couple of months. The meeting assistant allows you to record calls and meetings for interviews and job candidates and all sorts of stuff like that. All that data goes into the LLM and so you can assess candidates, you can assess meetings, you can go back and look at information that was discussed that you may have forgotten about. Really big feature there. The mobile app for Galileo is coming out in Q1, so you'll be able to run it on your phone. You can talk to Galileo in voice. I'm going to show you that in a minute. There's new features for building custom assistance assistance. So if you take Galileo and you have an HR business partner role in a certain country and you want to put a whole bunch of country specific data into it, so the people in that country who are supporting, you know, the employees in that country have certain regulatory information that's unique to your company, you can put it in there and create a custom assistant, you can give it a new name, you can change the pre prompt, so you can basically give it personalities. And then there's a new reasoning capability in Galileo which allows you to do multitask parallel reasoning. So you could take 10 job candidates and put them into Galileo and say compare these 10 candidates against each other, analyze them all on the following criteria of skills and the following criteria of cultural attributes, and then compare them against each other and rank them for me based on this criteria, this criteria, this criteria, and it'll do that and do that in parallel. You can do that with financial data. So there's lots of cool things coming. We're also improving things like labeling. So we have several large competency models in Galileo and it can now immediately make sense of a large competency model and explain it to you and use it for recruiting or sourcing or leadership development or assessment. So we got tons of stuff coming there. I would say because the platform uses multiple LLMs, we get the benefit of using the best technology from OpenAI, Microsoft, Google or anybody else. Because the router under the covers of Galileo sends your query to a different LLM depending on what kind of query it is, and the corpus is integrated and protected. Okay, so that's a little bit to think about. I'm excited about the coming year. We're going to be all over the place doing all sorts of interesting things all over the world with you guys. Check out the Josh Person Academy and the AI courses in there. Come January, you're going to read about the rise of the Super Worker. There's going to be a JBA course on the Super Worker and lots of information understanding how to take advantage of the AI transformations in your companies as an HR professional. And let me give you a little sneak preview of how you can talk to Galileo Good morning Galileo.
[00:13:41] Speaker B: Hello. How can I assist you today?
[00:13:43] Speaker A: How would I design a behavioral interview for a Sales Representative to excel in.
[00:13:51] Speaker B: A behavioral interview for a Sales representative role, focus on the STR method, situation, task action and result. Prepare examples from your past experiences that showcase your skills in key areas such as communication, problem solving, meeting sales targets, handling rejections and teamwork. Be ready to discuss specific scenarios where you demonstrated these competencies and achieved positive outcomes. Would you like more detailed tips on any of these aspects?
[00:14:25] Speaker A: No. Thank you. Can you tell me the top skills needed in sales representatives?
[00:14:32] Speaker B: Certainly. Top skills for a sales representative include clear and persuasive communication to engage customers two Active listening, understanding customer needs and concerns Product knowledge in depth knowledge of the products or services being sold Negotiation Ability to reach mutually beneficial agreements 5. Time management, efficiently managing time and prioritizing tasks 6. Customer relationship management Proficiency with CRM software to track interactions Adaptability adjusting to different customer personnel thank you Galileo.
[00:15:11] Speaker A: Can you tell me what skills I should be looking for in a sales manager?
[00:15:16] Speaker B: Certainly in a sales manager, look for strong communication skills, leadership abilities, strategic thinking and the ability to analyze data. Also consider skills in coaching, motivating a team and customer relationship management.
[00:15:33] Speaker A: Thank you.
[00:15:34] Speaker B: You're welcome.
[00:15:35] Speaker A: Can you explain to me what a skills Taxonomy is?
[00:15:40] Speaker B: A skills Taxonomy is a structured framework that categorizes and organizes skills into groups or hierarchies. It helps in identifying, assessing and developing skills within an organization or industry. This system can be used for talent management, training and career development. Galileo, you're welcome.
[00:16:02] Speaker A: Who are some of the vendors that can help me manage a skills taxonomy?
[00:16:07] Speaker B: For managing a skills taxonomy, you can consider vendors like Cornerstone, on Demand, Degreed, LinkedIn Learning, and Skillsoft. These platforms offer comprehensive tools for creating, managing and updating skills frameworks. Would you like details on any specific vendor?
[00:16:26] Speaker A: Can you tell me about what Workday can do with my Skills Taxonomy Workday.
[00:16:32] Speaker B: Offers a comprehensive skills cloud that can help you manage your skills taxonomy. It uses machine learning to identify and categorize skills, provides insights into workforce capabilities and helps in aligning employee development with organizational goals. Workday can also integrate with other systems to provide a unified view of can.
[00:16:55] Speaker A: You tell me what techwolf does as a skills vendor?
[00:17:00] Speaker B: Tech Wolf specializes in AI powered skills management solutions. They help organizations build dynamic skills taxonomies by analyzing workforce data from various sources. Tech Wolf's platform provides insights into skill gaps, learning needs and workforce planning, enabling more informed talent development and management strategies. Would you like more details?
[00:17:25] Speaker A: No, but I'd like you to tell me what Lightcast does relative to skills.
[00:17:32] Speaker B: Lightcast, formerly known as MC Burning Glass, specializes in labor market analytics and provides insights into skills demand. They offer tools for building skills taxonomies, understanding workforce trends, and aligning educational programs with market needs. Lightcast helps organizations make data driven decisions about skills development and talent acquisition. Would you like more information on their services?
[00:18:01] Speaker A: No thank you, but I would like to ask about one more vendor. Can you tell me what Eightfold does relative to skills?
[00:18:08] Speaker B: Eightfold offers an AI powered talent intelligence platform that focuses on skills based talent management. It helps organizations build comprehensive skills taxonomies, identify skill gaps and match employees with relevant opportunities. Eightfold's platform leverages data from various sources to provide insights into workforce capabilities and future skill needs. Is there anything else you'd like to know about Eightfold?
[00:18:37] Speaker A: No, not right now, but I'd like to get back to this issue of hiring salespeople. If we want to hire a Salesperson in Toronto vs. Cincinnati, Ohio in the United States, what would be the differences in the hiring practices that we should.
[00:18:52] Speaker B: Consider when hiring in Toronto versus Cincinnati? Consider these differences. First, regulations and labor laws. Toronto in Ontario has different employment laws than Ohio. Be aware of variations in minimum wage benefits and termination practices. Second, talent pool. Toronto has a diverse multilingual workforce with strong tech and finance sectors. Cincinnati may offer lower competition for talent and a lower cost of living. Third, understand local business norms and expectations. Toronto's market is more cosmopolitan while Cincinnati may value traditional relationship building. Fourth, compensation adjust for cost of living differences. Toronto might require higher salaries and more robust benefits. Fifth, leverage local job boards and networks. Each city has preferred platforms and professional communities. Tailoring your approach to these factors can help attract the right sales talent in each location.
[00:20:01] Speaker A: You know. One more question, Galileo, I understand you know a lot about salaries. Can you tell me what the salary differences would be for a mid level salesperson selling enterprise software in Toronto versus.
[00:20:15] Speaker B: Cincinnati for a mid level salesperson selling enterprise software. Salaries can vary significantly between Toronto and Cincinnati. In Toronto, the average base salary might range from CAD 70,000 to CAD 90,000 plus commission. In Cincinnati could be USD 60,000 to USD 80,000. Toronto's high cost of living and competitive market can lead to higher salaries. However, these figures can fluctuate based on experience, company size and performance incentives.
[00:20:51] Speaker A: Galileo One more question is there if if you were to think about the one thing I could do to be a better HR professional, what would it be?
[00:20:59] Speaker B: Focus on developing strong communication. Being able to and convey information effectively can significantly impact all areas of HR from employee relations to strategic planning. It builds trust, resolves conflicts, and fosters a positive workplace culture.
[00:21:15] Speaker A: How do I improve my communication skills.
[00:21:18] Speaker B: To improve communication skills? First, active listening. Focus on truly understanding the speaker without interrupting clarity and conciseness. Be clear and to the point. Avoid jargon and over complicated language nonverbal cues. Pay attention to body language, eye contact and tone empathy. Understand and respect others perspectives and feelings.
Seek constructive feedback and work on areas of improvement. Practice Engage in conversations, public speaking or writing to refine your skills. Consistent practice and awareness can lead to significant improvement over time.
You're welcome.
