Episode Transcript
[00:00:00] Foreign Today I'm very excited to announce that we're launching the 2025 imperatives and predictions Report, which we call the Rise of the Super Worker. And this study, which has been going on for more than a year, describes the people, related strategies and issues we're going to face in 2025 as we redesign our companies, our business practices, our jobs and our culture around this massive new opportunity we have with AI. Now, as you all know, we've been dealing with AI for almost two years. This is a hugely transformational technology that we've all experienced in our own personal lives and our own jobs. It started with the Microsoft Copilot and OpenAI and it's now evolving into digital agents, multi step processing systems, digital twins, superintelligence systems, and eventually systems that are fully autonomous. In other words, things that we think of as an assistant today that might help us do step by step tasks in our job. Soon enough they will be chained together and they will ask us for support as they do work on our behalf. And this impacts all internal facing roles as well as customer facing jobs in sales, marketing, customer service. And I think we're just barely scratching the surface of the imagination and reinvention that's going to take place. Now, you may think that this is a technology initiative like digital transformation, where we have to hire a bunch of engineers and IT people and implement and build and train and integrate all these systems. And that of course is true. But the bigger challenge that companies face is the people side of this, because as I understand, you know, the world, and I've obviously been doing this for quite a while, we have built companies around people.
[00:02:09] We have designed job titles, job levels, the job families, the job architecture, the way we hire, the way we move people, the way we train people, the way we promote people. All around this idea that a company is a collection of people and the intelligence lies in the people and the systems are really used to increasingly automate the work that people do. AI is very, very different. It isn't only an automation technology, it's an intelligent technology. It can capture and consolidate vast amounts of information, far more than we can as humans, and find patterns and make decisions or give us advice on decisions that need to be made, and not only in a digital form, but in an audio or visual form to do work for us. And so, rather than thinking of our companies as large collections of human beings with all of the management issues, of course, that we have to deal with, we need to think about our companies as collections of digital agents and digital assistants with People operating as superworkers on top of this AI level of intelligence. Now, of course, nobody's there yet. Most of these AI platforms are very new, they're unproven, and a lot of them are not domain, industry or functional specific yet. So they're very off the shelf types of tools that we need to learn how to use and tweak and configure for the business processes in our company. And there are no generic business processes that all companies do the same. Even platforms like Salesforce or Workday or SAP, which may or may not be industry oriented, have to be configured and tuned and customized for our companies, because everybody does the same thing slightly differently. So these AI systems still have a long way to go. But there's no question now, given the rapid maturity and the huge amounts of investment that are going into this, that this is going to change the nature of every job in the company. And so, as you'll read about in the Rise of the Superworkers Report, there are essentially four things that we have to consider as AI enters the workforce. The assistant model of how AI might change, take a current job and make it a little bit easier to do. The augmentation model, where the AI might take a current job and replace a significant amount of the work with an automated agent. The productivity job, where the AI does multiple steps on behalf of people and integrates and becomes essentially an agent and we work around it. And then the autonomy job, where we manage the AI and the AI more or less runs by itself like a Waymo car. And all of those four scenarios are playing out at the same time. We're not actually doing this in a linear fashion. It's all being tested and evaluated and developed together. So we're going to be doing a lot of time, we as HR people and business people, thinking about what are the human impacts of all of these technologies. Now there's a range of things that people need to do. We have to design and implement the processes and the systems around which the AI fits in our companies. The AI doesn't know how we handle customers, or what our products are, or what our business looks like, or what countries we do business with, or what rules we follow and all that stuff. So we have a huge amount of work to customize and embed and train these systems on our company's practices. Oftentimes that's done through uploading documents into the system, configuring it, adding it to connect to current corpuses of information. And soon enough we're going to have development tools that will be done visually where we'll be able to tell the AI if this, then that, if this, then that, so forth. The second, of course, is rethinking the employee or customer experience. It's nice that an AI system might speed up something behind the scenes, but if the customer experience is poor or it makes incorrect decisions or it's too slow, I mean, the perfect example of this is the self checkout line in the supermarket, which is always, almost always, slower than the human line, even though the human lines are longer. So we deal with the AI because it's a little bit faster in the long run. These are not always easy to use for people. We're going to have to be doing a lot of design work on that. And then of course, what are the roles and jobs behind the scenes? Do we need the same routine or mundane or repeatable tasks to be done by people? And of course the answer is no. A lot of that's going to go away. But these are not just mundane jobs. Think about the person in the marketing department who's building marketing campaigns, who might sit down with a design tool to build a graphic or a video. It may be that we capture information from customers or the market or competitors. We feed that information into the AI. We teach the AI about our brand and our fonts and our messaging, and the AI generates the videos on our behalf to deal with the market changes. That's going to happen in every domain of hr recruiting, leadership development, coaching, training. All of these things that we consider to be human centric processes will be significantly aided and automated by AI. And so the idea of the Super Worker is that all over the company, we're going to be thinking about not only the process and work redesign which we need to be deeply involved in as HR professionals, but also the new jobs, the new skills, the new pay levels, the new cultural attributes or standards that we have to create to enable the company to embrace and adapt and use and leverage AI. Now, we're still early in this process. Obviously there are no AI companies out there. Every company is mostly filled with people. But there's lots and lots of experience we have with AI systems over the years, including in things like credit card processing. So, so there's a lot of embedded experience already that's taken place. What we know so far in this journey to the Super Worker is number one, we are not going to eliminate massive numbers of jobs. Even though there have been lots and lots of automation tools and AI systems implemented in the last five to 10 years, the workforce is already out of people we have an unemployment rate in the United States that remains around 4%, which is very low. Most developed countries have the same issue with shortages in frontline workers, retail workers, manufacturing, distribution, transportation, hospitality, a lot of customer facing, hand to hand jobs, and even in white collar work where there's growing uncertainty about the job stability of many people, there are shortages in it, shortages in data management, shortages in financial jobs, lots and lots of others. So these systems don't necessarily operate as human replacements, rather they operate as human empowerments. And that's the idea of the super worker. Don't think about AI as a way to lay off half your company and operate as a skeleton crew. You could do that and that may play out over time, but the ultimate scale here is the other way is to use the people. You have to double or triple the productivity and sales and revenue potential of your company by empowering them to do more and more and more. It may turn out, and I think this is starting to show itself, that the number and level of hiring that takes place as these systems are used will eventually go down or slow. Today there's so much job re engineering and IT work to do that I don't think that's going to happen. But it certainly may over time. And we will end up with what we call super worker companies. Companies that are largely made up of people that know how to use, develop, manage, train and customize these systems and can deliver literally orders of magnitude more output or higher quality or higher levels of creativity than they could before. And I honestly believe this is going to happen. And my best example of this is, is our company. We are a relatively small company of roughly 45 to 50 people, but our revenue scale and operational expertise is expanding at orders of magnitude because of our use of Galileo and the AI tools that we have built for ourselves. And we're not that big and we're not that sophisticated at technology. So I can see this happening in sales, in marketing, in operations, in finance, in hr, all over your company. By the way, it's not clear to me that there will be a corporate wide AI strategy just like there never really was a corporate wide digital strategy. There may be corporate standards for tools and technologies and data standards, but each functional area or each customer facing group will probably find different applications of AI that fit best and probably different vendors too in their domains. And so we're, we're basically going into what I consider to be a trillion dollar RE engineering effort all over the world, in every major industry. Now, as with every transformation that's ever taken place in my life. And I'm sure you've been through just as many of them as I have. Some companies move fast, some companies follow and some companies lag for a variety of reasons. Sometimes their company is stable and the business is doing great and they don't see a need to disrupt themselves. I think that's less and less true, but in some cases it's certainly true. Some companies just are risk averse because of the nature of the business they're in and they don't feel that they can for regulatory reasons or other, make too many changes too fast and others just don't may not have the change enablement, change readiness, you know, skills to transform fast enough and they find themselves left behind. Let me tell you though, in this particular case with AI, as we did find in digital transformation over the last 25 years, there will be winners and losers. I mean if most of you remember the beginnings of Amazon.com or the beginnings of Google or the beginnings of whatever your favorite E Commerce, Uber, whoever it may be, and how sketchy and odd and maybe weird those companies seem to be in their early days, well, their ability to innovate and iterate and learn faster than their competitors allowed them to radically compete and out compete their peers in the industry that they do business. And I think the same thing's going to happen again. The companies that learn how to use and harness and configure and customize these AI systems are going to rocket ahead by orders of magnitude their peers. Now it's not going to happen in the next year, but it will happen soon because the maturity is really of the technology is still coming. But there's no question in my mind that this is perhaps at least in my career, the most disruptive transformation technology and platform that I have ever seen. So I suggest you probably don't have a lot of choice. The second reason you don't have a lot of choice is that every person in your company is already using AI. They're using ChatGPT, they're using Perplexity, they're using Google, they're using Galileo, they're using whatever the one is that they like. They're finding that it's quite amazing at some things and it doesn't work at other things. And they're coming into work and they're finding the old clunky stuff that we have in the office workday, Oracle, SAP, whatever it may be. And they're saying, wow, how come this thing isn't as intelligent as this other thing that I'm using in my consumer life. So the demand, the expectations, the vision, the imagination for this is there. We now have to harness these tools and use our skills at re engineering change, skilling and job design to enable these applications to roll out and drive productivity and scale. Now, perhaps the most interesting research we did last year that led to many of the findings we have in this report was the research we called the Dynamic Organization. And if you've read that research, and I really encourage you to get it, what it really discovered was that the reason companies are struggling to move people from place to place or transform or evolve isn't because they don't understand the market around them, isn't because they don't understand the technology, isn't because they don't have the technology. Which by the way, is the same thing true in AI. It's because their people practices, their culture, their bureaucracy, their reward systems, their management teams are holding them back from making the changes that they need to make. And what dynamic companies know how to do in the level four of the dynamic organization model is they know how to embrace change and address change on a continuous basis. A lot of us were trained that changes take place episodically. We buy a new system, we spend two years implementing it, we hire a consulting firm or whoever and we turn it on and we are transformed. That is no longer true. We're in a world of continuous transformation, which means continuous reskilling, continuous changes in jobs and roles, continuous rethinking pay levels and continuously redefining the role of management supervision and leadership. And that sort of dynamic model for operating is six times more effective at predicting financial performance than the companies we call level one, the static companies. So this AI world of superhumans or superworkers that we are entering is going to force you to really get good at change, enablement, dynamic talent models, and embracing new the new worlds of leadership. Now, I won't go through all of the details of all the changes that we anticipate. You can read that report, read the rise of the superorca report, and join us on some of our webinars. Let me make a couple of final comments here. Number one, this report is a research study that really culminates more than a year of research last year, and we'll be continuing the super worker research throughout the year. You can get the detailed report by joining Galileo, joining the Josh Burson Academy, or joining our corporate membership. That's the way you get it. Number two, the transformations that we see taking place will affect hr. There's no question that we will be both consumers and designers of AI systems for the rest of the company. We have to embrace these tools internally, which means that your ability to experiment, learn how the tools work, understand the technology, and apply it to your own job will be essential in your consulting and advising with your clients or your employees on how they can make their jobs better. One of the best ways to do that is to use Galileo. And the reason we've priced Galileo so low is this. So you can get it, you can use it, and you can learn about its potential to leverage AI in the rest of the company. And part of the offering of Galileo is a report we announced in December called the 100 use cases for Galileo, which I encourage you to read, to just familiarize yourself with all of the potential ways that AI digital agents and assistants can help you make your job better. The third thing is really to maintain a positive and uplifting attitude about these changes. I am sure we're going to be flooded with stories from reporters and others about layoffs and job transformation and people that are looking for work and frustrations with AI and why AI is bad. I firmly believe that we have to take a different opinion. I have to take a different perspective. The perspective that we need to take is that by embracing the super worker model, all of the people in our company, and I mean all, can be reskilled or redeployed to take advantage of these systems to add scale, quality, customer service and creativity in ways they never could before. This is not going to be a linear path. Some of these systems are still evolving, but it's going to tilt upwards very, very steeply because the potential to improve the existing bureaucratic processes we have in our companies is simply massive. So join us on this journey. Come to the webinar, get your hands on Galileo or another tool and download this report. We want you to work with us and share your own experiences. We look forward to helping you build the super worker organization of your company in your domain throughout the year ahead. Thank you.
