AI’s Role in Talent, Trust, and the Future of Employee Experience

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Jeanne Meister: One of the really interesting issues is this concept of the underground user of AI. So we know from the latest Microsoft survey that 75 percent of the workers are using AI, but about 50 percent are using it but not admitting that they’re using it to their manager or their team. That’s actually the most dangerous position to be in.

David Rice: Welcome to the People Managing People podcast. We’re on a mission to build a better world of work and help you create happy, healthy, and productive workplaces. I’m your host, David Rice.

My guest today is Jeanne Meister. She is an expert on the future of work and a workplace strategist. We’re going to be talking about AI, how it’s being used in the workplace, and how companies can get a handle on what AI means for their people and the work they do.

Jeanne, welcome.

Jeanne Meister: Thank you for having me, David. It’s a pleasure to be here.

David Rice: Absolutely.

First, tell us a little bit about you, how you got to where you are, what it is that keeps you up at night these days when it comes to the future of the workplace?

Jeanne Meister: Yeah. Okay. So as you said, I’m a global HR consultant and workplace strategist. I’ve written several books. Essentially my career has been around writing a book, building a company, and then selling the company. So I wrote the first book on the topic of corporate universities. Built corpu.com, sold that, and then wrote The 2020 Workplace. Built Future Workplace, sold that, and exited in December of 2023, so just last year.

I’m also very active in higher ed. I’m on the board of an online non profit university targeting working adults. And in my free time, I live in New York City with my husband and my Australian Labradoodle.

David Rice: I don’t know if people tell me about their pets, you know, like I, I have four dogs. And everybody comes on the show, they’re all business. I don’t hear about the pets.

Jeanne Meister: Well, good. A new line of questioning then.

David Rice: Right?

I want to just kind of start the conversation around something people might not immediately associate with AI, unless they’re, you know, a college professor movie, but it’s the idea of trust, right? So when we spoke before this, we were talking about a conference you recently attended and the issue of trust was coming up a lot, right?

But not from the perspective of employers, from the perspective of the employees, many folks are feeling sort of hesitant to use it for fear of how their employer might view the work that they’re doing or the role that they’re in. So I guess, how do you see this taking shape right now? And what should managers and leaders be doing to address it?

Jeanne Meister: Well, in your last question, one of the things that keeps me up at night is just this, David. It’s the emotional side of using generative AI in the workplace and the anxiety, fear, and trust issues that I’m seeing play out. And I think employees are concerned about If they don’t use generative AI, will they not get that next promotion?

If they use generative AI, will they be seen as replaceable? Where, gosh, so many of the activities that you do can be taken over by AI, so what is it that we need you to do now? So I think There’s really a case to be made for how generative AI is really causing employees greater stress in the workplace.

And, David, I’ve done a lot of work in the last couple of years on the topic of financial well being, and that’s Another stressor for employees, and there was actually a survey that said that employees that are worried about their finances spend the equivalent of a part time job 15 hours a week, worried, and that impacts their productivity and motivation in the workplace.

And I’m concerned the same thing could happen here, where employees. I feel they should be a lot more productive using AI, but they’re not. One of the really interesting issues is this concept of the underground user of AI. So we know from the latest Microsoft survey that 75 percent of the workers are using AI, but about 50%.

Are using it, but not admitting that they’re using it to their manager or their team, that’s actually the most dangerous position to be in because you may not know the guardrails or policy that your company has. And importantly, you’re using it in a silo and you’re not sharing and the organization isn’t giving, getting the maximum benefit of the different use cases beyond productivity for driving creativity and innovation.

So I think this issue of trust from the employee perspective is a really important one. So the question then is, what do you do about it if you’re an HR leader? I think the first AI tool that every company should put into place, regardless of their size, Is an AI policy and to communicate that thoroughly.

David Rice: Yeah, it’s something that we’re starting to get a lot more questions about. And I think it’s, there’s like so few clear resources on it cause it’s so new. And you end up with a couple of different types of challenges here, right? You’ve got big companies throwing all kinds of resources at driving AI usage and putting in.

They’ve got guardrails that they’re putting in, and then you have like small to medium-sized businesses where it’s maybe a little bit of the wild wild west, right? Depending on how much leadership actually understands the technology, which I think varies greatly from one position to the next. So, but I mean, if we’re looking at tech companies kind of in particular, where you’re either integrating AI constantly, or in some cases you’re developing it, who knows what sort of experimentation is going on in the background.

I guess my question is, how would you advise to handle the sort of AI challenge differently based on your size and resources?

Jeanne Meister: So, there’s no doubt that the innovations have been in the technology and professional service firms, right? They’re using it, they’re creating it, and they’re consulting on it.

They have huge practices in this area. So, for small to mid sized businesses, Number one, they have to really take notice of this statistic of the underground users that people are paying $20 a month if they use the ChatGPT-4 and they’re bringing that to their workplace. It’s the old bring your technology to work.

On this case, it’s bring your AI tool to work, right? As I said, the first AI tool is a policy. It doesn’t cost anything. It just requires the organization to develop a governing board, including representatives of HR, finance, IT. If they have a legal person in house, or if they’re a smaller company, they definitely have a legal counsel.

Maybe it’s an outside one. And some business leaders and really come to have a shared vision on how are they going to use AI in their business strategy? And then what type of policy are they going to have? And importantly, who is it directed to? Is it just full time employees? Probably not. So many small to mid sized businesses leverage contractors and a lot of vendors, right?

Is it just for employees in the office? Probably not. It’s, you know, they’re going to be working at home in their home offices. You know, I think companies have to really do a deep dive on understanding how AI is impacting throughout the organization, develop this policy, and communicate clearly, not just one time.

So, what I’m finding is It really needs to be a campaign. It can’t be just, you can’t treat it as a compliance training course, you know, take this so you understand how to use AI in the workplace. It needs to be vibrant and ongoing. And I also think one of the missed opportunities is companies aren’t putting recognition in place for those people that are using AI to improve their productivity or drive greater creativity in the workplace.

How do you uncover those, let’s call them power users, and recognize them and reward them, you know, for really grappling with this new tool and having it pay off for them?

David Rice: Yeah. It’s interesting because sometimes if you look at like the media narratives around it, you’d think that the whole world is just switched to doing their jobs with AI.

And now we’ve all just universally embraced it. But I think one of the big discussions that inevitably comes out of increased usage is ROI. And some of it is like, what is the metric by which that’s decided? You know, is it not just a productivity in terms of volume of work, but it’s quality of work, right? It’s, it’s how creative are you being with it? That could be a metric, so.

You know, I’m kind of curious where you feel like we are in the ROI portion of the AI curve, so to speak, because, you know, you want to encourage people to be creative and be innovative with this technology, but you also want to balance it with like, what is actually meaningful for the business?

Jeanne Meister: Yeah, I encourage clients to look at it with a new frame, right? And first to look at, how are they going to use AI to optimize a function? And that may mean, you know, think about talent acquisition, if you will, for HR leaders. I mean, that’s a big, early use case, right? And then how are you going to use AI to accelerate a new product or service that you have?

And for small to mid sized businesses, what I hear a lot is the use, is the use case of AI for coaching. So many people want to learn with others, and there are actually a lot of interesting tools out there. But beyond use cases. Which I think there’s many, many of them. I think companies have to be more strategic and how are they going to integrate AI into their business strategy and really as a team, as a governing body.

Identify those high value, lower risk applications, which are pretty easy to implement, and I think we can’t be shy about looking for those quick wins. I think that we really need the high value, lower risk. Everything has a risk, but some risks are lower than others. So if you put that frame around it, and then look at how can we really drive more value here for the organization.

The research points to the fact that business leaders see that, see using AI as a strong competitive advantage. But they’re being very cautious about investment because of wanting to prove an ROI on it. So you’re right. They need to grapple with this as a cross functional team to do it. And really that’s the same regardless of your business size where it’s all about The strategic use of integrating AI into the business strategy, not just the individual use cases of which there are a myriad.

David Rice: Definitely.

I kind of want to just shift into sort of like a talent perspective here. You know, one of the things AI I think leads to is, and there’s some narratives out there about this, about it kind of leads to people cutting corners. When we see cases now, there’s, I was reading on Reddit recently, another one where people are taking on like two jobs at a time with it.

What sort of concerns do you have around What does it mean for like quality of work, like we were talking about before, and how much you can trust someone that you’re bringing in that they’re going to be dedicated to your team full time?

Jeanne Meister: Well, this is a really good question. And it’s really one that I think impacts all businesses regardless of their size.

So it reminds me, David, of the question, what if I train my workers? And I spent a lot of money in investing in them, and then they leave, right? And the old retort to that was, what if you don’t train your workers and they stay? And so, similarly, with this question. What if you don’t train your workers in how to use AI and they stay, right?

And that’s the risk is, you know, could impact your competitive position within your industry. I think this question, if you look at it, really boils down to trust. Right. As we talked about earlier, are you trusting the employees that you’ve hired to do the best job? I think as we’ve moved from the pandemic from mostly working in person to now.

Having much more choice and flexibility as to where and when you work. This is an issue that has really bubbled up without generative AI, without the fear of gosh, now that they’re using generative AI and they’re so productive, they can have two or maybe even three jobs. This was an issue that came up in the last four years.

Are my employees working if I can’t see them? Or are they just working on my job if I can’t see them? Or do they have any other job? So it’s really trust and culture. And do your employees feel valued? And respected and rewarded in the organization. You’re going to get bad actors wherever you are. I mean, that’s just the way life is.

But what can you do in your culture to instill trust and belonging, a feeling of belonging to the organization and being accountable to your team members, right, being available and accountable and producing for your team members. So it really is an issue that’s, that’s cropped up and it does have the two sides of the coin.

Because the other side of the coin is now leaders are saying, I think it was the Microsoft study again, 66 percent of leaders saying they’re actually not going to hire someone unless they have generative AI skills, and they’d actually prefer to have someone with those skills. Rather than more experience on the job.

So if you’re looking for that as a layer in your recruiting, you’re going to find a population that knows their way around these tools. And you should see that and value that as a good thing. Rather than being fearful, then they’re going to have extra time and gosh knows what they’re going to do with it, right?

David Rice: Yeah. Speaking of what they’re going to do with it.

Another question I sort of always keep coming back to when I, when I talk about this is if you’re in that like small to medium sized business range, right. Or you don’t really have your own AI instance that you’ve built behind a firewall. How much should those companies be hesitant to put company data into the AI?

Jeanne Meister: Well, first we have your AI policy is your first AI tool. So everyone needs to be trained on that. I think you’re going to recognize that people are going to be putting their own data into the tool. They can do things in the back end, like make sure that it’s not trainable with your own data. But, you know, from what I’ve seen in various organizations, They’re keeping really close tabs on usage and possible AI IP infringement.

So, knowing the policy and constant communication and training on the policy. Is really the best strategy to avoid infringement here. And, you know, at the end of the day, it’s actually not all that expensive to have your own playground to start using AI within the organization and to understand how you want to use this and integrate it into the strategy.

So, I think companies are going to find that as they think about what they’re investing in, this is going to be bubbling to the top, and they need to do this in a strategic way, and they need to understand that there are these underground users out there. And they would want to make sure to mitigate any risk that they might start using it inappropriately if they don’t know how to.

David Rice: This last question here, this is the sort of one I’m sure that you get all the time as someone who spends a lot of time thinking about the future of work, but I am curious to know your answer. You know, as companies figure out how to get AI integrated into workflows, into their employees habits a little bit.

Better. What are some of the things you’re most interested to see play out when it comes to AI in the workplace?

Jeanne Meister: I love this question. And I see, well, I recognize the fear of using AI, I also recognize the huge opportunity to use AI to improve and enhance the employee experience. So some of the things that I think are really interesting and I want to see more of is companies re skilling employees whose jobs are, let’s call them right for automation.

And one of the best examples of this is Ikea furniture store, right? They have thousands of customer service reps. And within the last 18 months, they introduced a new chat bot to handle almost 50 percent of the customer inquiries around when is my furniture delivered and all sorts of questions that customers have, right?

So instead of outright losing customer service agents. What they did instead was they re skilled them to be virtual design consultants. So they took their basic core skill in customer service and they added on to that. By showing them how to use 3D applications, taking them through a consultative selling process.

So they were able to speak to a potential customers. They made this a fee based service is as a customer, if you wanted to do virtual design consulting, you could, and it’s already contributed about a billion dollars to their revenue. So I think we have to see more companies. Think about how to use AI to transform and enhance the experience for employees and for customers.

The other thing I’m reading about with, and noting, is the gender gap in using generative AI. A recent survey by Slack, which mostly targets small to mid sized businesses, found that men are 25 percent more likely to experiment with AI tools in the workplace than women. So I’m going to turn the table on you, David, why do you think that is?

David Rice: It’s the first answer that comes to my mind is there’s just less fear among men about what’s going to happen to them if they make a mistake. I know that sounds overly simplistic, but it’s an ingrained thing in us, right? Like in all of us, right? Women have had over the course of the workplace, their time in the workplace have been punished when they make mistakes differently than men.

There’s not seen as. Innovators necessarily, or leaders, or even creators in some case, even though that’s not true. It’s just a thing, like a stereotype that we’ve perpetuated over many, many, many years. And it’s seen from the recruitment process all the way through the talent management process, right? And so I think there’s just less fear among men if they screw something up.

That the hammer is going to come down hard. It’s always like, Oh, I’ll ask for forgiveness, not proficient. I hear a lot more men say that.

Jeanne Meister: I’m really concerned about that. And I think you are right. There’s less fear. There’s more trust that, you know, Oh, if I screw up. It’ll work itself out, right? And I do think that overall, as the Slack survey found, women are just a little more hesitant.

And it also could point to the fact of the jobs overall. We’re talking about the overall workplace, including, you know, the 70 percent of the workforce that we often forget about, which are frontline workers. When you think of the overall workforce, right, a lot of females are in lower level jobs where they are more hesitant, you know, maybe it’s, you know, it’s, it’s, they need these two career jobs for their families.

And there is more hesitancy on their part, and this is something that we have to address for both knowledge workers and importantly for frontline workers.

David Rice: Yeah, couldn’t agree more.

Well, Jeanne, this has been, this has been super interesting. I want to give you a chance before we go to essentially, you know, tell people where, more about where they can connect with you, find out what you’re working on, what sort of things you you’re doing.

Jeanne Meister: Yeah, I hope everyone that listens checks me out on LinkedIn. That’s the first place I will be. And please connect with me, Jeanne Meister. I’m also on Forbes quite frequently, so you can search Forbes for me. I have my own website, jeannemeister.com. And if you just wanna send me an old fashioned email, I’d love to hear from you.

I’m jeanne@jeannemeister.com. One of the things I’m working on and will start in January is a new quantitative survey looking at generative AI use cases, not just for knowledge workers, but for frontline workers. So that’s something that I started to mention here I feel very passionately about. I am the daughter of two frontline workers, two hourly frontline workers.

They are 70 percent of the workforce in the United States. And especially with uses of generative AI, we tend in the HR world to only focus on knowledge workers. So I’m going to be starting this in January, and I hope you invite me back, David, so I can tell you about the results and what I’ve learned.

David Rice: Yeah, that would be great. Definitely looking forward to hearing more about that.

Alright, well, thank you for coming on today. I really appreciate you giving us a little bit of your time.

Jeanne Meister: Thank you very much for having me, David.

David Rice: Until next time, listeners. If you haven’t done so already, head on over to peoplemanagingpeople.com/subscribe. Get signed up for the newsletter. And until next time, ladies, do not hesitate to experiment with the AI. Don’t let historical biases get perpetuated throughout the AI era. Keep the experiment going.