January 25th, 2024, 10:00 am PT / Category: Interviews, Provision Partners
With such a wide range of AI technologies and applications available, how can organizations avoid the risky behavior of "AI-washing?" And how can Design Led Thinking be used to discover the AI trends that truly align with your business goals and objectives?
David Chestler
President, ProVision Partners International [Linkedin Link]
David Chestler is recognized as an icon of the global hospitality and travel industry, having forged a successful career in hotel technology that spans over three decades. He currently serves as President of ProVision Partners International, Inc, a hotel and travel consultancy and marketing firm that he co-founded in 2019. Since beginning his career in hospitality in 1989 with Utell International, Chestler has held leadership roles with some of the industry’s most prominent organizations, where he consistently delivered global scale and growth by developing high performance teams focused on complex technology solutions.
Sally Kelly
SVP Advisory Services, ProVision Partners International [Linkedin Link]
Sally has 15 years of experience and expertise in the development and execution of strategic communications, consulting, product development and deployment for the hospitality and travel industry. Prior to joining ProVision Partners, she held a leadership role at KPMG, and spent six years working with the Amadeus IT Group. She also served in a strategy and consulting role for Accenture, a global professional services company, before opening her own consulting firm in 2020.
Sandra Vazquez
User Experience and Design, Encora [Linkedin Link]
Sandra Vazquez is a UX and CX leader with more than 10 years of experience helping software companies improve the user experience of their products. With an entrepreneurial background, she guides companies on how to build engaging products and impact market adoption. In her role as Head of User Experience, Sandra works with clients from all around the world to discover their user’s perspectives and translate them into actionable design solutions that ultimately drive growth. She has a bachelor’s degree in Management Information Systems from the University of Arizona.
Podcast
Transcript
Kim Lantis: Hello and welcome to dojo.live this Thursday, January 25th, 2024. My name is Kim Lantis and it’s my pleasure to be hosting today with what is our second of a five-part series here on dojo.live, which is “Do More in ‘24” as we identify how to take the next step with AI. Joining me today is David Chesler, President of ProVision. He joined us in our first segment, actually. Good to see you again, David.
David Chestler: Good morning, Kim.
Kim Lantis: Yes, good morning! And then, also from the ProVision Partners team, we’ve got Sally Kelly who is the SVP of Advisory Services. Sally, we’re excited to talk with you.
Sally Kelly: And it’s my pleasure to be here, Kim. Nice to see you.
Kim Lantis: Yes! Nice to see you as well. And finally, and last but not least, we’ve got Sandra Vasquez who is the Head of UX Experience and Design with Encora. Sandra, we’ve had you here on the show a few times. It’s good to have you back.
Sandra Vazquez: Thank you. Likewise. I’m really excited to be back and very interested in this topic, very excited. And thank you for having me.
Kim Lantis: You’re welcome, you’re welcome. You know, today’s topic here on part two is really about the overwhelm that we can feel and how to overcome that feeling when it comes to AI adoption and developing strategies. We’re going to talk and deep dive into how to use Design Led Thinking in order to do that. But before we do, I just want to give a small little recap of what we talked about in our first session, sort of just laying the groundwork for the “Do More in ‘24” series. That was with David and Andrea Mane, also with ProVision.
I think the takeaways there are, and David, you can correct me if I’m wrong… Number one, we established that it really is necessary to implement AI Technologies in pretty much any organization, but particularly in the hospitality industry. And that’s not because these robots are going to take over but because the competition who is utilizing AI is going to do what we’re doing, only better. And that of course, because of this pressure to implement AI, a real risk is this term that we talked about which is “AI washing,” right? This temptation to maybe implement AI just for implementation’s sake which might lead to bad experiences over the actual goals that we’re trying to achieve. And then, of course, there’s not this one-size-fits-all solution, unfortunately, when we want to know how to implement AI best. And I guess that’s where we’re going to lean in today, with how to go about that implementation. Did I sum that up alright?
David Chestler: You did a brilliant job, Kim. Thank you very much. The only thing we’d extend on that is, again, understanding that it is a technology, and you have to have a planned approach to deploying it. Therefore, making sure you have that plan is critical and that’s why we wanted to have someone like Sally Kelly, who leads the charge for us, kind of explain how you go through the process, because it is a process. It’s not one and done. You don’t just sign in, implement, and it’s over, right? Chat bots and similar.
And I think there are so many permutations of AI, understanding how you want to use it, right? Because it’s not AI going to replace your job, as we established. It’s someone using AI who’s going to do your job better, right? And I think how do you deploy it internally or externally, customer facing or optimization and similar, those are all decision points that need to be made by businesses based on the customer, based on the colleague, or the users within the organization, based on your budget and any number of things that we need to go through. So, it was important to bring someone who’s done this before into the environment and that’s why Sally was a perfect candidate as she implements a lot of the processes for our organization with customers.
And her background, having both the operational side and the vendor side, she knows the dark side as well, gives her a great perspective and a lens to lend into establishing what we want to talk about here. So, I’ll lean back and let the professionals take over.
Kim Lantis: Perfect, thank you. Sally, did you have anything to add to David’s wonderful introduction of yourself, really quick before we dive into the topic of conversation? A little bit about your background?
Sally Kelly: One of the things that I think is interesting that Dave was just talking about, and apparently you explored on the first of the podcasts, is this notion of AI washing, right? The fact that AI can solve all the problems. It’s kind of like, I think everybody heard it growing up, it’s Maslow’s Hammer: if the only tool you have is a hammer, then every problem you have is a nail. So really, taking a look at every possible problem to be solved by AI really is taking a shotgun approach when really you need more of a target pistol, right? You need something that you can really begin to home in on: what the issues are, the friction points, the pain points, and then go out to look for possible solutions and then begin to prioritize them. And that’s kind of where AI and Design Led Thinking work very well together. So, David, it was a perfect introduction. So, thank you.
Kim Lantis: All right. Well, thank you! That’s great. Sandra, I think this analogy that Sally was utilizing just now, shotgun versus sniper rifle, is a lot of what you do also with your user experience and design.
Sandra Vazquez: Definitely and I totally agree with Sally. One of the things that I will complement, and I think that AI allowed us, is to actually choose what problems we don’t want to start working on. What are these repetitive tasks that we don’t want to spend time on? So, AI is a tool for us creative people to let us focus on the more complex problems and let us think broader and kind of eliminate the things that might not provide that much value or joy that can be done by AI. So instead of thinking, “Oh, this is a technology that will take my job,” the way we think is, “Oh, it’s this technology that will allow me to solve more complex problems.”
Kim Lantis: Yeah, like, “Let me do the fun stuff and you do the boring stuff, AI.” I love it. That’s great. So, as we dive into this, you know, we did talk a little bit, but I think it’d be good to… well, we’ve already talked about these benefits – but real fast if we could summarize maybe some of the benefits of AI, the transformations that organizations can expect one more time before we dive into the “which one do I choose?” So, I think we talked about optimization a little bit, we talked about here the enjoyment factor, right to get to do the more challenging aspects, or the funner aspects of our jobs, anything else that we’d like to add to that list?
Sally Kelly: I think one of the interesting things about Design Led Thinking in particular, and we’re not going to dive into the methodology today, but one of the things it does, and Sandra, I know you probably experienced this as well, is it allows you to really correlate the emotional with the functional, right? People going into environments have emotional reactions to things, right? If you’re going to check into a hotel and that process is hard and it’s 11 o’clock at night, you’re going to have a very emotional reaction to it. You’re not going to like it very much, right? And Design Led Thinking actually says, “All right. Let me figure out what the pain points are,” right? Is it that checking in at 11 o’clock at night with a process that doesn’t make any sense, let’s say, even if you’re a loyalty member, you’re still out there trying to do something. It’s bringing together the power of the emotional and the functional here that really can satisfy all constituents in the process because you look at what hurts, you try and fix it, and then you make it better.
There’s a corollary to this as well that I think is obvious to me, maybe just because I’ve done it, is when you involve users, whether they’re inside or outside your organization, developing a solution, implementing it, is not hard because they’ve been part of the solution all along, right? When you go out to that person who wants to check in at 11 o’clock at night and say, “Tell me your pain points about checking in at 11 o’clock at night,” which is the Design Led Thinking part, then you can begin to isolate the ways you can solve that problem. And then bringing in AI, where does it make sense? Back to that repetitive task, right? Am I going to use facial recognition, let’s say in this particular case, to solve that problem? So, that person will love it; they got their oar in the water. All your people as well are going to like it because, back to that repetitive task automation, they don’t have to worry about passports, identification, credit cards, all that can be done for them using AI.
Kim Lantis: I love it. I think that’s a really good example of the emotional side. About two years or so ago I ended up choosing a hotel when I was traveling, and it was a chain hotel, a lower end one, and I was checking in at night and I remember at this point I actually had to be standing outside and the person who was receiving me was behind glass with like a little one of these things and I’m like, “What in the heck part of town am I in?” And like, okay fine, it is what it is, but like, “Can I come inside?” Perhaps if there was some of this AI implementation to make me feel safe, to make the clerk safe as well, that, “Hey, this is Kim,” facial recognition, “She’s fine. Let her in.” You know, that could have been wonderful, yeah!
Sandra Vazquez: Another thing I would like to add here is that I totally agree with Sally in terms of understanding the problem that your customers are facing because then we all have had that bad experience, and the result is the same – we don’t go back. We don’t go back to the hotel. We don’t go back to use that application. And as technology advances, we as users advance also. We expect everything to be quick, we expect everything to work at once. We don’t give that much permission for companies and products to fail because we have so many options.
And another good thing that AI allowed us is the power of analyzing larger sets of data in a faster way, in an easier way than it was before. So, we can provide more customized user experience for the customers that we are analyzing, that we are learning from, with the Design Thinking process. So, this capability allowed us to give personalized recommendations. I keep getting a lot of ads that I wonder, “Why am I getting these ads? I am not the target audience. Clearly some marketer is not doing their job right.” And once in a while I see this ad that is exactly the thing that I’m looking for because of my age, because of my demographic, and you can start seeing like, “Oh, there’s some AI behind this ad because it’s just right.”
Kim Lantis: For sure. I think you bring up a really, oh, go ahead David.
David Chestler: No, I was just going to say following on from your point about that experience behind the banker glass, you know, trying to check in. Using some of the ideation that you can do through Design Led Thinking, some of the process that Sally and her team have led before, allows you to identify those areas and then start to determine how do you apply a certain solution set to it. Whether it’s using your app to engage with conversational AI and move someone through a process credentialing and recognizing them so that they don’t have to wait outside the bulletproof glass, they have access to the lobby whilst they’re traveling in their Uber or taxi, or similar, and it’s that application of engagement and how you do it, not just a person answering the phone but potentially conversational AI or, you know, some form of experiential component that allows the data to help bring and usher the guest to where a colleague can support that experience and make it frictionless. But that is where you have to identify the problems and that’s why having the customer, the employee, the operators, all talking about it, breaking down the silos – that’s the part that Design Led Thinking really helps do that many in our business don’t look at first, of breaking the silos. It’s either IT, or it’s front office, or it’s marketing, or it’s sales versus I need constituents from all of those various operating groups, including my customers, and potentially my partners, my vendors because I can’t afford to build AI in into my own Tech stack. I need the help of others; it takes a village I heard once said. Right? So, please.
Kim Lantis: Yeah. Is there a framework, Sally, that you could walk us through in terms of Design Led Thinking? Are there particular steps to follow as we try to move from this sense of overwhelming options to, you know, overcoming? And actually getting to the quote unquote “easy” implementation?
Sally Kelly: Well, you’ve already done all the hard work by the time you get to the implementation, so it should be easy, or easier, anyway. You know, there are some terrific statistics out there to support the reasons transformations fail, right? And unfortunately, they fail more than they are successful, so you know it’s one of the things that as businesses look at transformation, they are a little skittish, right? They’re sort of like, “Well, I’m spending billions of dollars.” And then if you look across the market it’s trillions of dollars. Roughly 30% of them meet their goals, right? So, when you really take a look at what’s invested versus what is actually reaped as a benefit, sometimes it’s not what you expect.
So back to process, you know, what the second thing behind budget that typically causes projects to fail is user adoption. So back to what David was talking about, right, all of those constituents that you have in your environment, by getting them all together in Design Led Thinking – we’ll get back to the process in a minute – you also just break down a lot of their assumptions. So, if you work behind the front desk, you have a set of assumptions. If you are a customer, you have a set of assumptions. If you’re a partner you have a set of assumptions, and so on. Getting everybody together to kind of go, “Oh, you really do think that way? Oh my God!” You know, we can do something about this simply by having this conversation.
Back to the process, Design Led Thinking has been around for a long time and even though it is not something well known within the hospitality industry, it actually is responsible for a lot of the things that you see today that you may not even know about. So, let’s look at the success stories first, briefly, and then we’ll just take a quick look at the – there’s five, sometimes six phases of Design Led Thinking, depending on how you think about it.
So, when you take a look at what worked in the hospitality industry relative to Design Led Thinking, Marriott is an example. Marriott started tours and leisure activities in about 2018 but they really ratcheted it up during the pandemic and also in response to changing traveler demographics. Millennials and Gen Z that are coming up, these are people that don’t just want accommodations – they want experiences. So, using Design Led Thinking, Marriott went out and figured it out. So anymore they are not simply an accommodations company, they’re a travel experience company because you can book all these cool tours and activities and theme park tickets and all sorts of stuff using their tours and activities platform and you can earn points. And that was all done with Design Led Thinking. And one of their partners is an AI partner, when you look at travel and activities.
Another really good example is Hilton. I don’t know if any of you are Hilton Honors members, but at a certain level Hilton Honors members can actually book their rooms online. That was all done through Design Led Thinking with Hilton reaching out into the Honors Community and saying, “Guys, how can we help you? What can we do? What’s really bugging you about us and let us fix it!” So, Hilton, because of their unique technology stack, actually can do that because they have a single image of inventory. You can choose your room and they know who’s checking out, when you’re checking in, etc. That was Design Led Thinking. Now, it didn’t use AI, per se, but back to solving the problems. It solved the problem.
Kim Lantis: For sure. And not only for their users, making their honor members happier, but it’s leading to more direct bookings – making them happier – and they’re not having to pay out commission to OTAs or anything like that.
Sally Kelly: And that is such a great point because it is. Hilton has the highest percentage of book direct, right? And it’s partly for that reason. So, they’re saving all the intermediary fees, and you get your favorite room. So, it’s all good, right? So, there are two good examples of Design Led Thinking, one with an AI component, one without – but how successful they’ve been.
Relative to the process, the first process is called empathize and I think we all know what that means. We just talked about it. Go out and ask people what’s bothering them, right? So, you’re going to get a lot of answers but you’re also going to find commonalities and differences in them, from which you can begin to prioritize them for solutioning. Second is to define the problem. So, people are going to give you a lot of emotive content when you take a look at empathize. Defining it is really saying, “How does it work today?”
So, you can really isolate where the problems are and then you’re going to do what David was talking about, which is ideate. So, I know what people feel. I know how the process works. Now, getting these cross functional teams together, how do I fix it? Right?
So, you sit down, and you brainstorm – that’s what ideate means. And you get this cross functional group: you get the IT guys, you get the front desk guys, you get the loyalty guys, you even get the customers in the room. Try and figure out this solution. Then you just start to prototype, and you prototype with feedback and then you implement, and Sandra I bet your process is probably very similar to that. But in a nutshell, that’s what it is.
Kim Lantis: Yeah. Did you have anything to add there, Sandra, with that?
Sandra Vazquez: Our process is very similar. Actually, we follow also Design Led Thinking to build Technology Solutions. And one of the most important things, and I heard Sally emphasize this as well, is to get everybody in the room because it’s not the responsibility of only the directors, it is not the responsibility of only the IT team. You get the most out of this process when you have everybody: the users, the person who works at the front desk, the person who is answering the phone, the person who is even cleaning the rooms. When you have all of these profiles in the room it’s when you get a chance to actually see the whole problem from different perspectives and provide better solutions.
And something that we say is at the prototype level, when we do our ideating or when we are defining what the solution will be, it is cheaper to test there than once you start writing code and bringing in technology. Then things get really expensive.
Sally Kelly: Yep.
Kim Lantis: That’s a really good point. You know, when it comes to bringing these people together, what’s that process? Or what are the numbers that we need? Because to me, I listen to this, and this can also sound overwhelming. Like how many clients do I need? How many colleagues do I need? How many representatives from all these different units that we’ve spoken about? How much does that require? What’s the general time frame for this Design Led Thinking process? And how do we go about making it happen?
Sally Kelly: So, Sandra, I don’t know if you agree, but I don’t think that there is a standard time frame that you can look at. It depends on the size and the depth of your problem, right? If it’s a big problem, it is going to take longer. If it is a simpler problem, like what experience do you want to offer? That has a lot of emotional components to it, but sometimes it doesn’t have a lot of the technology components, right? So typically, what you do, and everybody’s process is a little different when it comes to Design Led Thinking, so, Sandra, if you have a different process or a different idea, please feel free to step in.
Typically, what you do is you want to have, it’s kind of like agile design, you kind of want to have three or four of each, right? So, you want to have teams that you put together, again helping you break down those silos. Typically, you have them work in teams. Let’s say that you’ve got a customer, you’ve got a frontline operations person, you’ve got an IT person, you’ve got an IT security person, depending on what the problem is. There may be a designer, like Sandra, in there trying to kind of think about what the wireframes might look like and how it all works. But you take these teams, and you pose the problem to them, and they come back to you with solutions.
So back to ideate, you’ll probably get three different solution sets. Each one will be slightly different depending on the people involved, their perspective on the problem. And, again, it sounds like it’s a long-term process. It’s not. You start to collapse things from there, but in order to get the best thinking you really want more rather than less people involved. Again, it also gives them a stake in the process by helping with the solution. So typically, the broader your reach, the better your solutioning is going to be. And Sandra, I don’t know if you think differently about that problem or not?
Sandra Vazquez: I agree. There is not a one-size-fits-all because each problem is different. Sometimes you’re dealing with a whole journey map when the customer is interacting with different touch points. I think the most valuable thing is that you have a variety of people and profiles. So you want to build these things when you have somebody – I will talk in technology terms because it’s what we do, applications and solutions – but for us, it’s very important that you have somebody from the back end, that you have somebody from the front end, that you have somebody that is the user. If we do this in a hotel, we want somebody from the front desk, but we also want somebody from housekeeping because perhaps they will interact. So, the value is more on the different profiles that you can put in the same room, at the same table, to work and ideate because it allows you to see the problem from different perspectives.
David Chestler: The only thing I would add is that you also need to have that support from the C-suite all the way down, because if you don’t have that commitment to this effort, what’s going to happen is it’s going to start to move in different directions that aren’t focused on the ultimate outcome which is either internal facing or external facing. But what is the outcome for the users, customer or colleague? And what is that impact to the tech stack? Because we all know now that interoperability is much more important for the evolution of the tech stack and for big data and CDP/CRM engagement so that you recognize, you personalize, and you optimize. And those are things that we’re all looking for as outcomes, including some creative value at the end of this journey. That “I could pay for this.” That it is justified, right? Details, I know.
Kim Lantis: For sure.
Sally Kelly: The interesting thing about it though is, look at the conversation we just had with Kim, right? So, Hilton goes out, uses Design Led Thinking, decides they’re going to let you book your room direct. What do they do? They make money. They increase loyalty, right? So done right, all of these things happen. It’s not an accident. You’ve involved all of these people, you know, back to these differing perspectives. And it is beneficial to everyone to have that, right?
Only because, again, when you look at all of us and our assumptions, where we come from, what we think, what our backgrounds are, they influence how we think. And it’s really just trying to kind of tear this apart and put it back together in a way that functions better.
We keep talking about the sort of front of the house/back of the house, right? Our customers or guests. It’s all yin and yang, right? If you change something for the customer or the guest, you’ve got to change something on the back end too, so people know how to service it. And I think frequently, as we were talking about, there are these silos. You either focus entirely on the guest or you focus entirely on hotel operations, understanding that they sometimes don’t very peacefully coexist, right? And breaking down those barriers is a good thing.
Kim Lantis: For sure. We’re coming into the final few minutes. I cannot believe it’s been nearly 30 minutes already. This conversation has flown! That’s when you know it’s a good conversation. But talking about flying, talking about pace, the pace of AI and any technology is just extremely fast. And I think with AI it is even getting faster with this compound, inception type movement. How do we keep up in that sense? I think our segment four here on the series is going to be more about the testing component, right, and the iteration. But how do we keep up with that pace? How often do we need to come back to Design Led Thinking?
David Chestler: Well, I’ll answer before Sally jumps in. Remember, it was identifying that there’s a problem and then going through a planning phase to understand magnitude, costs, everything. And that’s why we like Design Led Thinking, because it brings more constituents. But you then have to understand the implementation/deployment effect, timelines on that, and whether it’s iterative in that deployment, the testing and iteration, like we talked about, and then, ultimately, that summarization and the forensics of how it worked. And that circles back to almost beginning again, almost like we did with PCI and all those various security implementations we’ve had to go through. AI is a technology and that’s why I think going through the phases of it are critical. Sorry Sally, I didn’t mean to interrupt.
Sally Kelly: No, no. By the way, there’s a lot to your question to unpack, Kim, and it’s a really good question. I think that the good news about working with AI and Design Led Thinking, AI learns, right? So, AI is constantly refreshing itself. It is constantly analyzing the inputs and it is changing what it knows, it’s adapting kind of on the fly. So, you’re able to see the results that you’re looking for and you may not get them the first time, but you have data to support why you didn’t get them the first time. So, you may just need to go back and tweak some of it. You may not have to do some massive, brain damaging kind of AI analysis. You may say we need to focus on this small part of the problem because our solution didn’t quite hit the mark and then go back and do that. So, I think that’s partly, I would defer to Sandra here as well, because she’s got a lot of experience, that’s where AI is really good because it’s constantly turning through data, it’s constantly giving you data points and analytical points that you can go back and reference.
Sandra Vazquez: Yeah. I will add that at the end, this is an iterative process. One of the steps of AI is prototyping and the prototyping is because you want to validate. You want to say, “Hey, this is my assumption. Does it work? Doesn’t it work?” So, there will always be tweaks that you will be doing to the final solution. But also, doing this exercise in which you start incorporating the Design Led Thinking into the organization, will lead to a change in the mindset of the people. So, it will become part of the philosophy, part of the day-to-day work that we do. And when there is a new change that needs to be done then people will start thinking, “Hey, wait a minute. Should I involve the user? Should I go and talk with somebody?” Maybe they won’t do the whole exercise, but they will go and do an interview.
And that is something that happened to us in Encora, Kim. I remember 2015 we did a lot of workshops and the result of that was that when the People and Culture team was designing their onboarding, they went and did interviews, that it was part of the process. And we didn’t sell them the Design Led Thinking philosophy, we just started teaching them and it became part of the entire organization. So that is something that, as we expose our people to these methodologies, the way that they start solving problems also changes.
Kim Lantis: It becomes a lifestyle, a culture. I wanted to leave it with this, we’ve gone over the half hour just a little bit, but I think it’s a simple question. Sandra, you mentioned the word “exposure.” As we were wrapping up the first segment with David, he had earlier mentioned that when it comes to technology, specifically AI, it can feel scary. And so, my question is, his tip was to utilize a little bit of AI every single day, even if that’s something as simple as going into ChatGPT and asking for it to create a summary for you or having fun and creating, turning yourself into a Viking, right, with a photo. Is there anything that the two of you do, Sandra and Sally, to make this pace, this technology, a little less scary? What might be some of your suggestions or the tools that you appreciate that our viewers might also glom on to?
Sally Kelly: Go ahead, Sandra. You got an idea.
Sandra Vazquez: For me it’s like jumping into the water. When I first start hearing about these new solutions, I start experimenting. So just go and experiment. I think the recommendation that he provided is really good because I remember when I started experimenting, one thing that happened, and really amazed me and kind of got me hooked into continuing with this, was the speed at what solutions are being built. I remember we started using a tool to test images and prototypes, and by the time we completed the first experiment that was a two-week experiment, new tools were provided. The quality was way better. So, this just amazes you. And my philosophy is, “Okay, what of my day-to-day work I would like to reduce so I can do these other things that excite me the most?” So, once you start thinking on this, instead of the, “Oh, will I lose my job or not?” Then you start looking for solutions on, “Oh, how can I reduce this task that is something that I need to do but I don’t like to do?” to do more of what I really want to start doing.
Kim Lantis: Thank you.
Sally Kelly: Well said. Me, I’m sort of like Sandra, so we’re very much alike. These things don’t scare me at all because, to your point Sandra, they’re not going to take your job. They’re going to free you up to do the things you do well while they do the things that maybe you don’t like, right? Or are repetitive and maybe a little boring. David, I’m going to talk to you about those invoices, maybe we can use AI. But, you know, really, I think it’s very exciting and I think one of the things that people, at least for my money, need to understand is this is probably the slowest pace of change we’re going to see in a long time. It’s accelerating at such a rapid rate you’re going to have to learn how to assimilate it and not be scared of it, right? So doing a little bit of it, looking at it as a friend rather than an enemy, is probably the best thing you can do.
Kim Lantis: Thank you, and that brings us to a great conclusion for today’s show. Thank you, Sally. Thank you, David. Thank you, Sandra, for sharing your insight on AI technologies, how to implement them and starting with Design Led Thinking. All right.
Sally Kelly: Terrific. Thank you.
Kim Lantis: You’re welcome. Hang on for just a minute as we go off air, but before we do, I’d like to remind the audience that this segment is occurring every other Thursday all the way through March 7th. So, feel free to join us again on February 8th where we dive into the implementation side, the “easy” implementation of AI technology, also at 10:00 Pacific.
And then join us next week here on dojo.live, we do have two shows. First up is John Taylor, he is with the company Odynn, John Taylor Garner, founder and CEO. We’re going to be talking about loyalty programs in a post- COVID world. That is on Tuesday and on Thursday we have John Sarver of Saaslogic. I do not have the topic for that show yet, but it’s guaranteed to be a good one. See you then. Thank you everyone, bye for now.
