Are your employees afraid that AI will take their jobs, or maybe not even something as extreme as that but still uknown? As AI transforms the workplace, understanding how to make your teams feel more comfortable with these tools might be the key to your organization’s success.
Today we’re exploring how AI literacy can transform the workplace with Jason Lapp, CEO of Beautiful.ai. We’ll dive into survey findings that reveal employee fears around AI and discuss strategies for dispelling those fears while integrating AI tools effectively.
Resources
Beautiful.ai website: Beautiful.ai
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Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom
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Transcript
Note: This was AI-generated and only lightly edited
Greg Kihlstrom:
Are your employees afraid that AI will take their jobs, or maybe not even something as extreme as that, but still have a lot of unknowns? As AI transforms the workplace, understanding how to make your teams feel more comfortable with these tools might be the key to your organization’s success. Today we’re exploring how AI literacy can transform the workplace with Jason Lapp, CEO of Beautiful.ai. We’re going to dive into some survey findings that reveal employees’ fears around AI and discuss strategies for dispelling those fears while integrating AI tools effectively. Jason, welcome to the show.
Jason Lapp: Hey, Greg, it’s nice to be here. I’m excited to share some of the insights with you today. Obviously, AI replacing jobs is definitely a hot topic and a lot of people are talking about it right now.
Greg Kihlstrom: Yeah, absolutely. Yeah. And, you know, I certainly consider myself more on the optimist side of the spectrum there when it comes to this stuff, but still, you know, still a lot of valid concerns. And, you know, that kind of beautiful AI did a survey recently of 3000 US managers that, you know, kind of supports some of this, it shows that many employees are fearful of AI tools in the workplace. Can you share some of the key findings of why these fears are so prevalent?
Jason Lapp: Sure, I’d love to. I mean, I sit on the same side of the fence with you. I’m very optimistic. So even the results and the insights we gained from this study were surprising to me as well. And I guess to start, we’re not a market research firm. Beautiful AI builds software that leverages AI to make your job easier. And we do that through presentations in a communications workspace. Annually, we run a very similar study to this. And we do that because we want to better understand our customers, how they’re feeling about the tools they have at work, and really understand the last two years, the role of AI in that space for them. That type of insight helps us build product. So really it feeds into our product strategy or go to market strategy and where we need to focus on sort of user experience and what’s ahead. This year, I really wanted to run this particular study because we’ve seen so many changes in such a short amount of time over the last few years, really since the beginning of the beginning of the AI era. We’ve always had a loyal customer base at Love Beautiful, but some of the things that shifted in 2023 were companies and leaders actively started asking how these tools could be brought into their business and what was the impact. So we really wanted to understand what they were thinking. So as you said, 3,000 US managers, the headline and the focus was really on how are they implementing new AI technologies and their perceptions of that impact. I’m going to spend a second just summarizing some of the findings, both from my perspective and just to give you and your audience a little bit of a data point. And then I’ve got a couple of comments for you. So the headlines from my side after spending time on this in previous studies would be that managers are looking at AI tools as sort of a new frontier for up-leveling their businesses and finding ways to lower costs. Conversely, the employee feels unprepared and fearful for their jobs. There’s a lot to unpack in that, but let’s start with some of the key insights. Managers are saying that they want to replace employees. and that they would benefit financially, and that they could lower salaries, all with the use of AI. The range is in the 40 to 50% in terms of the response levels of this opinion. What we see is that this is highly driven from their belief that AI productivity is equal to or greater to the level of their most experienced workers, with 64% of managers believing this. I believe after two years, they have some real experience to draw on versus just the public studies you hear about where an LLM is taking the SATs or able to graduate from college in record time. So, I think there’s a little bit of real life experience that’s feeding into the data after two years of implementing technologies. From the employee perspective, is that they feel that they’re in danger of losing their jobs. 66% of them feel they’ll become less valuable, half of them feel they’ll end up with lower pay, and over 60% of them feel that they’ll eventually lose their jobs to AI. One of the major silver linings that I observed this year versus last year, that’s because we ran the study twice, is that as managers and as businesses experiment and start to leverage AI tools in the workplace, their expectations become a little more grounded. So this year, we actually saw a 30% reduction in the number of managers saying that they could replace their staff with AI.
Greg Kihlstrom: So yeah, so there’s some to your point, there’s some realism that’s setting in, which is also, you know, kind of some good news for those employees, you know, still, still, you know, some of the some of the statistics could be read as not not great for for the human workforce out there but you know I guess I wonder I have I imagine this is still this is still gonna keep shifting and everything as well but you know in the meantime you know those those managers out there or even those employees um that are kind of dealing with this, this fluctuation, because you mentioned, you know, even two years in a row, even if they’re trending in a more positive way for the human teams out there, there’s still some anxiety. And sometimes that anxiety impacts productivity and impacts culture. You know, what can you know, what can managers and even those employees do as they’re still trying to navigate this stuff?
Jason Lapp: Yeah, I mean, personally, I have mixed opinions. I see a lot of employees and managers, you know, when they when they talk about this publicly or they talk about it at work. they talk very optimistically and energized on the experiences they’re having. So, looking at their feedback through a survey and maybe what’s in their innermost thoughts leans a little bit more to some of their fear and uncertainty or doubt in terms of where AI will play a role in their work. But If I think about this, I’ve been fortunate enough, like you, to have been in the work world during many tech booms, dating all the way back to the internet. And of those new tech cycles, the one this reminds me of the most is the early days of digital marketing. I was only a couple of years into my career, so I didn’t have 30 years of print and TV experiences that were driving how I worked. And back then, the large majority of marketers wanted to hold on to the way things had been done with TV for many years. Only a small part of the marketing world was really embracing digital Yet it seems so obvious to those of us that were new to marketing that this was the future. I mean, it was faster, it was more nimble, it was easily measured. It didn’t require that 30 years of learning to be successful. I even remember that being a time when major brand CMOs would announce that they were going to spend 10 to 15% of their total budget in digital, and it would make every headline.
Greg Kihlstrom: Yeah, yeah.
Jason Lapp: I was, I was trying to remember which, which brand it was. Um, I was in San Francisco and I think it was HP was making a big fuss about having done that. And the, everybody was crossing their fingers, hoping that money would move into digital. I draw this as a comparison because, you know, in that time, the, the digital marketing world, I think like the IAB was the reporting body at the time reported it was like $7 billion in revenue in 2001. in comparison to the 95% of budget that was in TV at the time. And now I think it’s $500 billion. You probably know the stat better than me. But it’s also the primary media for marketing. It’s where the consumers are. It’s where the eyeballs are. And AI is in a very similar stage to those early days of digital advertising. And we’re quickly going on a path of you know, they’re being over a trillion in revenue in the AI industry in the next 10 years. I mean, if you just look at the valuations and the path of revenue for someone like OpenAI, there’s a very clear path of where we’re going. That definitely means that jobs will change. It means that jobs will disappear. It’s undoubtedly, to me, going to mean that there’s going to be a major job creation at the same time. As we know with my comparison in digital marketing, it exploded a market and new opportunities. Long way to say, I think that from an employee perspective, I think this is an era where people need to be eyes wide open and start thinking about what it looks like in 10 years. I don’t imagine that in 10 years, anyone will be sitting there saying that they’re not using AI as a primary part of their workflow, their product, or the things that they need to do to get their job done every day.
Greg Kihlstrom: Yeah. Yeah. I mean, I, I would, I mean, a couple, a couple of thoughts there. I mean, you know, I would even go so far to say, I wonder when we stop even using the term AI because it’s so ubiquitous, but you know, we’re probably a few years away from that, but you know, the other thing just to, you know, going back even further than, than the internet, you know, like anytime and going back to the printing press, right. So like anytime there’s a technological revolution, there’s some job loss and then there’s eventual greater job creation and wealth creation. The unfortunate part, I mean, that’s an oversimplification, because people losing their jobs, that’s a, you know, that’s, that’s a very real and immediate thing happening to individuals and stuff. So, you know, want to be mindful of that. At the same time, I agree with you, like, I think there’s going to be more not only more jobs, but possibly more rewarding jobs created out of this, because I think a lot of humans are stuck doing a lot of repetitive stuff that A, machines are better at, and B, humans don’t like doing in the first place. You know, I think part of this is about understanding things better, you know, so employees and leaders understanding more of what exactly is going on, what the opportunities are. And so the term AI literacy comes to play here. So I wonder if you could talk a little bit about this. And given that premise that a greater understanding of the possibilities and even some of the drawbacks, but some of the possibilities here, how can managers improve this AI literacy within teams? in the hopes of not only alleviating concerns, but also just, you know, getting better work done.
Jason Lapp: It’s a great question. I mean, I think about literacy as experience. And maybe that’s maybe that’s not maybe that’s not the way that you’re thinking about it. But I really think about it as like the hands on experience and And what do you gain from that? And like, what is your holistic understanding of a topic become one of the things that I see often? in these conversations is that people are very educated on what’s available, what are the trends, how is AI in the headlines to how is it impacting their work or what are they using. But at the same time, I find that people actually aren’t trying to build firsthand experiences. So, if I was to break this down for a manager, The first thing I’d say is if you’re a manager, you should already know what AI tools are available for your department. Which ones are the top of the list? the case studies that are building that are available in market and how you, how you can implement them yourselves. Um, there’s hundreds of lists out there and a quick search would give you a lot of relevant lists of options. If it was minor stuff to major stuff in terms of your strategy and the things that you’re, that you’re set to do. I feel like the majority of the conversation tends to resolve revolve around marketing and sales. those organizations, there’s tons of tools, you know, beautiful, we use in marketing, we use tools like Jasper, it helps us to just quickly write or ideate or create content. You know, on the sales side, one of our products for doing sales campaigns is Apollo when they they have built in AI meeting summaries. And there’s a bunch of other applications we’re using in CS and product and engineering at the moment, which those are all first-hand experiences for people. So I think there’s a level of questioning, like what tools do you already have? That’s the easiest barrier to get over, because IT and security tend to favor those versus bringing something entirely new in. But some of your current vendors might have embedded AI in the products you’re using. As an example, Beautiful has AI in it, Adobe, Grammarly, Zoom, Apollo, Jasper, things that I already mentioned. So my suggestion would be for them is to build those experiences and start to build better literacy is pick a few that are relevant for the next six months of activities that you have that you’re doing on a regular basis and test them out.
Greg Kihlstrom: Yeah, and I think to that point, sometimes I give talks on this stuff and I remind people that they’re all, they’ve been using AI for years, right? I mean, first of all, AI has been around for decades at this point. So it’s, you know, some, I think a lot of people think that maybe it was invented with chat GPT, or something like that. But you know, obviously, it’s been around for like 40 years. But also, you know, anybody that’s searched on Google, or use Siri, or, you know, any of these things, they’ve been, they’ve been using AI, it’s just been kind of, masks. So I think, you know, to your point, what I like about that is, you know, getting people to use these things, they’re, they’re getting hands on learning and oh, by the way, you’re using AI and look how it’s not it, it relies on you, you know, maybe it does your work, or at least some of your work more quickly, and maybe some of it better, but you know, it’s, you’re using it, and you’re still here, right? So it’s, I don’t know.
Jason Lapp: Yeah, I think what’s, what’s interesting about that comment is, I think if you were in a room with a group of people and you asked them to talk about AI, they’d have a lot to say. But I find it surprising how many people have not tried chat GPT or free image creation or chatbots. And again, going back to experience, I think it’s one of the most important thing for individuals to start doing, whether you’re the CEO or the manager or the employee, it really doesn’t matter. I mean, I even as a CEO, I use chat GPT in certain certain writing situations where I have writer’s block or I get stumped or I just don’t have the brain power at the moment to figure out what the right positioning of something. And I think what we learned at Beautiful in building products around those generative AI tools that are more designed for leveraging LLMs is that there’s a really important process for building a foundation for the lexicon of prompting. So if you think about Google search back in the early days, back to my, I’m dating myself today. Back in the days, you would find out that if you put a comma or a plus in the line of prompting, it changed the outcome. And then it needs to, with a LLM, it really needs to be relatable to the structure of the way you think in order to get the right prompt back. or the right outcome for the prompt back. So I think that’s step one. The other side of this for me is that by doing that and running little micro tests all the time in terms of experiencing a chatbot is it helps set your expectations on the accuracy and the quality of the output. So we know inside of Beautiful, there’s all kinds of variations. It really depends on which LLM you’re using and what kind of outcome you’re looking for. And the accuracy and quality is improving over the last two years. But I think for anyone who spends a minute testing out these tools, they’re going to realize that we are way far away from generative AI replacing them at work.
Greg Kihlstrom: So in addition to the talk of fear and sort of, you know, lack of lack of literacy, lack of understanding and sort of the anxiety that produces. There is another side to this as well, which is there are a lot of employees already, or even people, maybe they’re in college about to graduate, that are going to start looking at work a little bit differently as far as if an employer doesn’t have AI tools available to them. I’m wondering, you know, is this something that you’re seeing? You know, do you have some, maybe some thoughts around this as well? Because it’s kind of it’s kind of the contrary, but we might live in a world with both, right?
Jason Lapp: Yeah, it’s, it’s a great question. I’ve, you know, I have a teenage son who’s a junior in high school, and he’s going to come into the work world. with only new tools. And I think we as a business in the presentation space are constantly battling the inertia of the way that I did things when I started my career, or my predecessors did as well, and their dependence on software and tools that were there for a really long time. I do believe that employees play a major role in the success of the implementation of a lot of the AI applications and tools in the workspace. But I don’t believe it will be long before employees really flip the script on managers and companies in their perspective of demanding a workplace where they have the tools to do their jobs effectively. And a lot of those are going to be based on things that are entering into the market today. So if there’s advice for the CEO, the leaders, the managers, it’s really to focus on what is working and what’s not in the AI application space, because those are the things that we’re going to be living with in a very short amount of time. And holding on to the old stuff will be harder in this space.
Greg Kihlstrom: Right, right, yeah. So that kind of leads me to the next thing I want to talk about, which is, so, you know, instead of replacement, it’s, you know, I like to think of it as augmentation, but another way of looking at that is AI as collaborative partner. And I mean, to your point, I mean, I use like three or four different AI tools all the time. I’m careful about, you know, how I use them and what I, you know, how I attribute and all that kind of stuff. But at the same time, it’s, I already kind of consider it a collaborative partner in, in my work, you know, as, as employees become more comfortable with AI, when they start using these things, when they’re start, kind of more aware that, again, they’ve already been using AI to probably to a higher degree than they might even realize, Do you think that collaborative partner is the right way of thinking of it? How can AI be positioned as that collaborative partnership instead of a threat?
Jason Lapp: Yeah. I mean, the applications that are available today really are designed as collaborative partners. That’s in large part because A lot of them are productivity-based. They’re built into existing workflows. They’re tools that are designed for efficiency and speed. So, I think the The tools that are available today really support what you’re saying in terms of a collaboration partner. We’re building with that mindset. But again, we’re in presentations. And that’s a common communication tool. And it’s something people do on a daily basis. And they’re smarter than the presentation. And they just need tools to get their job done faster. We even talk about AI as collaborative AI in our own internal language. because of that, because we really want to enhance the user experience. That’s not to say that AI can do more than that. I think there are some fundamental jobs and workflows that are dated, haven’t been innovated or challenged by the cost and resource of delivering them. And one of them that I see, which is maybe a hot topic, maybe a not is, you know, the advancement of AI in the customer success space. You know, what even in our business with millions of users and thousands upon thousands of tickets in inbounds, you can’t have humans do that. And the old hack solution was find the cheapest available resource and offshore it or find other ways to answer it. But You know, user experience and satisfaction is a core tenant to building a strong business. So the availability of AI-based chatbots that can answer things instantaneously at scale has some major implications to, you know, workforces that are in that space. Where as a business, I would say, yeah, Craig, it’s, it’s collaborative. It’s helping my CS team. I would also say, you know, there’s a downside that there are parts of the workflow that need to be innovated faster or can be today.
Greg Kihlstrom: Yeah, I was hoping, I know you’ve mentioned a few things about beautiful AI, but I was hoping that you could share maybe some examples of how are you creating AI tools that support some of this stuff?
Jason Lapp: Yeah, I think what your point of collaboration, collaborative tools or tools that are answering business efficiencies I thought of one example that, you know, I spent, spent 20 years of my career in marketing before I, before I moved to software. And, you know, one of the, the primary roles I was focused on was go to market. So it meant sales and marketing, production, all the, all the types of things that you would think about in terms of like, how do I, you know, how do I deal with client facing activities? And, you know, a good, a good example on beautiful is that, you know, we know we can create high quality presentations in a fraction of the time. You don’t need to be a designer. So you think about the classic sales role. You think about designers even spending a lot of time doing monotonous, repetitive things for proposals or for customers. This is a space where we, we become very beneficial as a partner for both sales and marketing. So if you’re a client facing, you need less support to create your next proposal or customer deck. And it really becomes DIY with the help of an AI software. In a lot of companies, we see marketing and production teams supporting that process. So, you’ve got a lot of back and forth. You’ve got professional designers making the CEO’s deck, the next pitch deck, the company presentation, and there’s a lot of wasted time in that. And it’s also a difficult and time-consuming workflow. So, with beautiful And we really can be put in the middle where you can reduce that support function dramatically. And we see two things happening. Marketing teams love this because they’re freed up to do more engaging work and not work on things that are repetitive or less impactful in the world of things they’re doing. And we also see sales liking the fact that they’re empowered to be able to do things on brand with the influence of marketing with guardrails. So the system that beautiful built was sort of two things. One, it’s really designed as a workflow tool to increase productivity when it comes to client facing communications, but the AI portion of it is really designed to just speed up the process.
Greg Kihlstrom: So I want to follow up a little bit on the maybe the first couple topics that we were talking about, and just get get your thoughts here. You know, we’ve got a lot of managers and leaders listening to the show. And just, you know, as we as we think about AI literacy, if we think about this concept of collaboration. You touched on some of these points already, but I wonder if you could just give some advice. Where should a manager start with building that AI literacy? What would you advise them to do first?
Jason Lapp: So I think to answer your question, there’s sort of a present and then there’s a future of literacy when it comes to managers. I think there’s a big portion of this where I believe managers and leadership need to figure out where they are in the adoption cycle and double down on the employee experience while they focus on operations. There’s sort of four categories that I think of that are important. And this is often confusing when you talk about AI. Is it a tool to help me do my job better? Is there an application for my go-to-market? Is there a product orientation that I need to be thinking about? But the four quick ones are workflow management and productivity. That’s what we’ve been talking about. The jobs to be done, the efficiency, the productivity of your teams. The second for me is sort of the resource-constrained areas. So, things that are really hard to support as a business, their operating costs, they’re hard to get your CFO to pay for, those tend to be support. support roles, they tend to be ops roles, they tend to be finance roles, admins, there’s a lot of opportunity to explore different ways to bring tools in in that space. The third is strategic advancement. So when I think about go to market, there’s so many different ways to optimize your marketing processes, you know, I talk about sales, we have a relatively small sales team. So our, our SaaS stack to support them is is not large. And I’m often jealous of, of all the tools that I see out there that that I see, you know, getting rid of friction in the sales part of the process. And the last which is which is more on the product engineering side, is like, where do you leverage AI as a competitive advancement for your products and your solutions and your services and in a different way? And I think there’s a lot of case studies out there. I know we don’t want to dive into that today, but I think if I’m a manager or leader today, you need to look at all of those categories. You can’t just be so singular to say, hey, everybody start using ChatGPT and get familiar with it.
Greg Kihlstrom: Right, right. Yeah, no, I love that. That’s that’s great. One last question before we wrap up here. You know, I really appreciate all your ideas and insights. And we’re going to link to the report in the in the show notes as well. But, you know, one one last question I like to ask everybody. What do you do to stay agile in your role? And, you know, how do you find a way to do that consistently?
Jason Lapp: For me, there there’s a handful of things. I think the biggest thing, we’re a remote business and we will be for some time. Beautiful is a small but rapidly growing business. What that means for me is to be agile. I really structure my day around 20 to 30 minute video meetings. We have a camera on Culture and a beyond time culture those two things as sort of Rules of the road to help make sure that you know, I’m I’m efficient. I’m using my time wisely, but I’m not also Buried in long strategic meetings where I can’t be available for the rest of the team.
