MC: 0:00

Experience Action. Let's stop just talking about customer experience, employee experience and the experience of leaders. Let's turn ideas into action. Your host, Jeannie Walters, is an award-winning customer experience expert, international keynote speaker and founder of Experience Investigators, a strategic consulting firm helping companies increase sales and customer retention through elevated customer experiences. Ready set action.

Jeannie Walters: 0:32

It's the Experience Action Podcast. I'm Jeannie Walters and I'm here to answer your questions Now, I am really excited to share the question that we got this week because it's from somebody who might sound familiar to some of you.

Adam Toporek: 0:48

I'm back, Jeannie Walters. It is your old podcast partner, Adam Toporek of customersthatstick. com, and you know, after 500 episodes together on Crack the Customer Code, I had to come and bother you. I missed you so much and you know, back on Crack the Customer Code we talked a lot about the robots taking over and obviously artificial intelligence has only grown in importance and grown in scale since then. So what I would like to know from you is what do you think the impact on the employee experience will be? The good, the bad and the ugly. All right. Well, congrats so much on the Experience Action Podcast, great dropping in and can't wait to hear your answer.

Jeannie Walters: 1:31

That's right.

Jeannie Walters: 1:31

Our question this week is from my pal and former podcast partner over at Crack the Customer Code, Adam Toporek. Now, Adam and I had lots of discussions throughout the many years that we did our podcast together, where we talked about the robots and how Skynet was taking over and how we had to really think about this stuff even before it became the reality that it is today. So, Adam, thanks for jumping in here and thanks for asking this question, because, while we've talked about it a lot for the customer experience, I think it's great that you're asking about the good, the bad and the ugly when it comes to what will happen as AI really infiltrates our workflow in our daily lives as employees. What will happen to the employee experience? So I loved the fact that you asked this in ways that really made me think about what are the good, the bad, the ugly parts of this that we should be prepared for. Now let's talk about the good first. When we talk about the ways that AI can actually impact our daily lives in the employee experience. There is a lot of good. Now, for example, we have increased efficiency. We are going to be able to handle repetitive tasks quickly and accurately. We're going to free up employees to focus on, hopefully, more creative and innovative and strategic work. This can lead to people feeling better about their jobs, feeling more aligned with their values, feeling like they're contributing more by the way that we're asking them to engage in tasks that, frankly, could feel more fulfilling. Now I know in my life we are already leaning into AI to do things like helping us take meeting notes and helping us summarize big strategic thinking into tactical ideas. AI can do this quickly and efficiently, and it's something that maybe took too much time in the past, so ideas never got translated into action. So increased efficiency is definitely part of the good.

Jeannie Walters: 3:47

Another part of the good is what I would say I'd call enhanced decision making. This is where we have the capabilities right now to, of course, look for insights and analyze data, but AI can do that at a scale around these vast amounts of data that organizations have to really provide, the insights that help all of us, as employees, make better decisions. So you know we're not doing this to collect feedback and to find insights. We're in this so that we can turn insights into outcomes, and that means we have to make better, faster decisions, and AI can help us do that by simply speeding up that analysis, by helping us find trends more quickly and before they become something that is a lagging indicator, it will help us be more predictive about the actions that take place for our customers. So this enhanced decision-making is a big deal, and I think that's something that AI will really continue to help us do at faster speeds, in more accurate ways, in ways that, again, are more meaningful for the very customers that we're serving and the organizational outcomes that we're looking to achieve. And then another good here is around skill development. You know, as AI and automation becomes more prevalent and accessible and visible within the organizations, employees will have opportunities to learn new skills and adapt to changing technologies. Because AI can help us create the right curriculums, it can help us provide microlearning in new ways within the actual workflow. So I think that that will be interesting too. If you're curious about something, you can learn it. You can ask AI to help you learn it, and that means that if we have learning paths available and if we have career development paths available for employees, they're going to have more ways to actually realize those ambitions that they have.

Jeannie Walters: 5:54

Okay, now let's move into the bad. The bad that everybody talks about is this idea of role displacement. We might not have the same jobs that we have today. We are already seeing some of this happen. Right, this is a significant concern that AI and robots and machine learning and all this great technology could lead to actual job losses, especially in these roles that involve repetitive tasks. Now, if you go back to the CX Pulse Check that I did with Maria Villablanca, we talked about how this might have a really big impact on contact centers, and we have to start planning for that. We have to start reskilling. We have to make sure that we are addressing the uncertainty and anxiety among employees around job security. Now there are ways that we're going to need people to help supplement what AI does. We're going to need people who can help train the machines. We're going to have situations where we absolutely need to connect to a human, and so, as we look at the jobs that might be replaced, I want to encourage all the leaders out there to think about what are the reskilling, upskilling options, as well as what can we do that will make everything work a little faster, better, with more empathy. So that means, if AI is handling those repetitive questions and tasks, when do we really need people to show up to provide that empathy and human nuance. So the job displacement question, it's real and I think we have to address that as part of being leaders when we talk about AI in employee experience.

Jeannie Walters: 7:43

Now, another bad part, I guess, is around kind of gaps in skills, because, just like every other kind of technological revolution that we've had, there is a difference in accessibility, in who gets access to this technology and who doesn't. Now that means that the gaps between even our employee base could be pretty dramatic. We need to make sure that when we are inviting people into this new world of AI and machine learning, that we are prepared to develop those skills with them so that they can work effectively with this technology. Now, a lot of this comes down to equity in education, equity in simple access to the different tools that we need in order to leverage AI, and in that education, so that we are preparing the next generation to really understand how to effectively partner with this technology and how to make sure that we all come to the right conclusion around it. We will need to invest in training and development to bridge this gap, and the tricky part here is that it's not necessarily just about our organization. This is a bigger societal question, and I think that leaders in organizations and businesses will have to lead the way in partnering with different government opportunities, different nonprofit organizations and folks like that. It's a big, big question, and I think it's something we need to probably talk about more. Now,

Jeannie Walters: 9:19

another thing that might be bad is that we've already learned the hard way that now that we all have spellcheck, we can't remember how to spell things. That now that we have voicemail and you know contacts in our phone, we don't remember people's phone numbers anymore, and so when those things happen, we have this dependence on technology and I think we might see some over-reliance on AI. That can lead to kind of the loss of human creativity and certain aspects of thinking strategically and writing skills and all of these things. That just it's a practice, and the more you practice, the better you get, but if you don't practice it, if you just rely on technology, we're going to lose those skills. So I think it's also really important to encourage people to not just rely on AI but understand what are the guardrails and how do we protect the very thing that makes us amazing and human, which is the human brain, and how we can really leverage innovation and creativity and all of the things that we bring to the table, just as these you know these organic creatures that we are. So I would say we will have to really be aware of this moving forward. Just like we're having conversations about our mobile phone dependence and how people are so dependent on not having any downtime without that dopamine hit from looking at the phone, we're going to have to have conversations like that around when do we have to set our own restrictions and make sure we understand our own limitations so that we can challenge ourselves to be creative, to be innovative, to think of that next thing, because AI will never do that the way humans can.

Jeannie Walters: 11:12

All right, now let's get to the ugly. Now you might think the bad is the same as the ugly, but I thought of this a little differently. I think the ugly is around where we talk about ethical concerns. We have a lot of ethical questions we need to continue to ask and answer as we implement AI throughout the workforce and the employee experience. Now there are already some you know, big discussions happening around bias in decision making algorithms, and that's because we start with humans, and humans unfortunately have biases right. Some of that is known, some of that is conscious and some of that is unconscious.

Jeannie Walters: 11:55

So we have to really look at what are those places that we know this might not be set up in the right way and what do we do about that to make sure that we don't perpetuate the very things we want to move past. We also want to think about surveillance and privacy invasion and what that might mean if we are asking everybody to kind of plug in all the time, and AI has different ways of really tracking both data and content and, frankly, people, and so we want to make sure that, when we are asking employees to work remotely and be independent, that they feel trusted and empowered and supported and not surveilled. There are already some big discussions around this, because there are all sorts of mechanisms that employers are trying to use to make sure that employees are working when they say they're working, and so now there are actually mechanical tools out there that will jiggle your mouse and do different things to trick your employer into thinking that you're working. But really people do that partially because they do not feel trusted or empowered. If they are not held accountable for outcomes, and we're only holding people accountable for hours, then that is not really building that environment of trust. So when we think about the ethics of AI and the employee experience, we really have to think about it in all these different ways, with both what's good for the organization and the outcomes that we need. And how do we help our employees feel supported and empowered and not really watched over or not trusted, and strike the right balance there? That's a big question that I think we're still going to see a lot of evolution around.

Jeannie Walters: 13:43

And then you know the one that we talk about a lot right and I know, Adam, this one is near and dear to your heart where, if we're not careful, we're going to lose that human connection. And when we talk about customer experience or employee experience, we are talking about human beings, and so we have to remember that as AI takes over more tasks and more situations that might lead to misunderstanding about am I working with a robot or am I talking to a person, we need to make sure that we are emphasizing human connection when it matters most. If we don't, this could lead to isolation, this could lead to people feeling low morale because they're not really knowing their fellow colleagues or customers. We have to make sure that we are creating space and doing it intentionally to create that human connection, to keep that human connection, which is so, so important. Sometimes a robot might give us the right answer, but a robot won't be able to look us in the eye the same way a fellow human does and say I understand, I understand you, and we have to really work hard on that moving forward. We cannot let AI and machines do everything, simply because we know that that is absolutely vital to the health of humanity. And so, when we're looking at how to use AI, I would also encourage everybody to think about where should we not use AI? You know it's easy right now to maybe join a team and be quote unquote onboarded with a series of animated videos, but it's very different to have somebody say do you have any questions? Can I help you? Do you have somebody to eat lunch with? Can I show you where we have the courtyard to go outside when you want a break? That's very different. That's what builds relationships and that's what people report are most important about how they feel about their work. So we need to make sure that we are not losing that human connection as we develop more ways to use AI in the employee experience and throughout kind of the life cycle of the employee with our organization.

Jeannie Walters: 16:04

And then this last one, I think, is universal with humanity too. You know what many, many people just don't like change. So there might be this big resistance to change. There's already fear and anxiety around this technology. But what can we do to make sure that the people who maybe aren't quite ready for this change or don't feel that they are confident enough in their own competence to move forward with changes around AI and machine learning? We want to make sure that we are giving those people the right tools, the right support, the right confidence, the right kind of playground to experiment so that they do feel confident about how to use all of this, so that they can see that sometimes automation actually makes their lives easier.

Jeannie Walters: 16:55

Because if we just say this is what we're doing now and everybody get on board, then that's not really going to help those people who are feeling anxious about this change or not confident about their ability with it. So we really have to think about what is that resistance for change and how can we work within our environment to make it as easy and simple and straightforward for the folks who might be struggling with that a lot. Because if we don't really think about that, that can create its own set of friction points within the organization, even between employees who, some of them, are all on board and very excited about this change, and they're going to, you know, get very frustrated with those employees who maybe aren't as excited about these changes and don't feel ready to step in and experiment and don't trust themselves to quote unquote do it right, so they just avoid using AI or machine learning or automation, and so we have to think about that as leaders, we have to think about how do we move forward with this in a way that makes sense for everybody. So I think this was a great question, and I hope that you're as excited about the possibility of AI as I am, because I do feel like, with the employee experience specifically, we have lots of ways to help people do their jobs more efficiently, more accurately, more quickly and, hopefully, with more meaning, and I think that's the part that I really want all the leaders to really think about how can we help people embrace these ideas around AI, but do it in a way that has meaning for the people, and if we're not thinking like that, we are missing an opportunity to really set up our organizations for success and also to pass on those meaningful moments to employees, who then pass that on to customers. So that is what this is all about. We want to create those meaningful moments so that people feel valued and heard and recognized, and then they are more likely to stay. They are more likely to stay as employees, they are more likely to stay as customers, and that's what leads to the outcomes that we're all looking for as well. So I hope that you know that you'll come back and ask more questions.

Jeannie Walters: 19:16

Adam, I really appreciate you jumping in to do that. I love hearing from friends on the podcast. I also love hearing from all of you. So don't forget, you can leave me a voicemail at askjeannie. vip. I can't wait to hear your next one. I can't wait to hear how you're using AI and machine learning. So let me know. Drop something in the comments on social media, send me a voicemail, let me know, or just send me an email off our site at experienceinvestigators. com. I can't wait to hear what you're working on. I can't wait to hear your next question and I will talk to you next week.

Jeannie Walters: 19:59

To learn more about our strategic approach to experience, check out free resources at experienceinvestigators. com, where you can sign up for our newsletter, our year of CX program and more, and please follow me, Jeannie Walters, on LinkedIn.