NextMapping™ Future of Work Blog
Welcome to the Future of Work blog – this is where you will find posts on all things related to the future of work.
We have guest bloggers that include CIO’s, Behavioral Scientists, CEO’s, Data Scientists including posts by our founder Cheryl Cran.
How AI, Bots & Automation Are Impacting The Future of Work/Life.
June 14, 2019
An interview with Ryan Lester, Senior Director of Customer Experience at LogMeIn.com
I recently had the pleasure of interviewing Ryan Lester of LogMeIn and am happy to share the transcript of the podcast here – enjoy!
“I think the more we can make technology accessible and approachable and it really is pervasive in our lives today” Ryan Lester
Cheryl Cran: Good morning everyone. Welcome to NextMapping podcast. Very excited for today’s topic and also our guest. Today’s topic is how AI, bots
Cheryl Cran: I also want to add that Ryan leads strategic development and implementation of LMI customer engagements flagship product, Bold 360 and is well versed on how chatbot and live agent solutions are impacting our working world and additionally as host of LogMeIn’s Bold360 podcasts, AI IRL, Ryan is also comfortable speaking in recorded environment. So we’re really pleased to have you with us Ryan. It’s interesting timing. I’m not sure if you, you probably super busy so you may not know this, our company NextMapping is about integrating technology with human and leadership consulting. I recently put into practice what I teach and preach, which is you have to have to be a lifelong learner.I just signed up for MIT’s AI course and I’m halfway through it. So it’s very fascinating to me. A lot of people hear AI, they’re very intimidated or they hear chatbot or bots and they get all freaked out. So I’m really thrilled that you’re joining us today to give us sort of
Ryan Lester: Yeah, thank you so much. Same here. Throughout my career I’ve loved , technologies. My education was actually engineering and then as I said, I did some sales and now I work more on broader strategy. And I think the term artificial intelligence can be daunting. There are scary movies about the topic. So we’ve all just got a mental model of this daunting technology that offers a little bit of hope and promise, but it also offers a little bit of a scary future. And I think the more we can make it accessible and approachable is good as it really is pervasive in our lives today. We just oftentimes don’t know how much AI is already in our lives. MIT is doing cool things with AI in its media lab. There’s a lot of really great stuff out there that’s actually quite accessible and it’s more getting your hands dirty and
Cheryl Cran: I introduced you, but tell our group, our listeners, a little bit more about your role at LogMeIn and your podcast. Tell us a little bit more about that.
Ryan Lester: Yeah, absolutely. So once again, I have the mind of an engineer and the heart of a marketer and problem-solving person. And so my role here is really interesting of I work in our go-to-market strategy around our product that focuses on customer engagement, Bold360, and how you help engage customers in a more realtime way through technologies like AI and also make your employees more productive at the same time. But as I’ve been doing this work, I found that there’s a lot of misconception, there’s a lot of hype around AI. I have traveled the world, I have all these conversations and people have common questions of how are people really using AI, where’s it being used best?
And what I thought is we should really start building a podcast where I interview people that are living AI in real life and learning from those insights. And so I do a weekly podcast where I interview people, most of them are focused on customer experience and how you can improve how you engage with your customers. But I also will bring up other topics of how AI is pervasive across different industries and they’re all real-world examples and there are lots of examples of real world success.
“And so the question really becomes – what problem are you solving and then what part of AI or what solutions are out there to help you solve that problem. ” Ryan Lester
Cheryl Cran: I hope we have enough time to get into some of those real-life examples because I think that’s what people can really connect to. And also if we have time, I want to give you a scenario and get your expertise on it if you don’t mind.
Ryan Lester: Yeah, sure.
Cheryl Cran: What do you think is the biggest misconception about AI and, and why do you think that is?
Ryan Lester: There are two big misconceptions. The first misconception is that AI is daunting and the second is that AI is to very costly or that AI needs to be like a long term strategic approach. And that’s not the case at all. There are AI technologies out there, solutions that you can implement in a matter of weeks. AI conversations need to come from the board room and it needs to be something that you are going to look at as a year-long vision. You can have a vision but think about AI as solving a problem. A great question could be: what’s the problem we’re going to solve this quarter and how are we going to develop a solution to solve it now? Because, if you take a long term approach, you’re not gonna start seeing that quick ROI. The second thing though is that I think because of all the hype around AI, people think about it as a magic wand. So even with some of our clients, you know, they’ll say, well, I just turn it on and it’s going to do everything. It’s AI, it’s
Cheryl Cran: I love the way you described that because in our work at NextMapping we research the future and we’ve written a number of white papers about technology being very human. It’s really about not polarizing technology. In other words, making it a new silo, which is what we observe, is that many companies make IT or the technology a silo when it needs to be integrated into the entire organization at every level. What we really see as the future is the human technology integration. It’s that hybrid of the best of human ability with the best of the technology and to your point that people think it’s just going to, oh, we’ve got this technology, it’s going to solve it all. It needs to be more of the bigger strategic objective as you said, in order for people to really get it to do what it needs to do and then let the people that are working in the company leverage what they’re doing as well. Would you agree with that?
Ryan Lester: AI has two really great impacts. One is it can let you monitor all of those digital end points, all of those touch points where they’re customer facing or employee facing. So your monitoring capabilities go through the roof, but it also then can aggregate that data and start to provide you broader insights. So it’s giving you that kind of granular view so you can go solve specific problems, but then it also gives you that macro view. So I think the way you’re talking about spot on, we also like to use a term called harmony, where it’s, it’s really, it’s the harmony between the AI and the employee and the customer. And you can’t think about those things as separate.
Cheryl Cran: Exactly.
Ryan Lester: Now that will change from business
Cheryl Cran: Yeah, I like the word harmony. It’s a nicer word. You know, I think for corporate, in our experience, there’s still a lot of siloing going on. So even just using the term integration freaks them out.
Ryan Lester: Yes! Exactly.
Cheryl Cran: So I think really what you’re talking about here is really relevant to the future and what we’re really wanting organizations to do to leverage AI and technology. So can you share with us – you opened by saying, you know, we’re living with AI, we’re living with these bots already. Can you share with us all of the unseen or known ways that we’re currently living with AI and automation in our daily lives?
Ryan Lester: Yes. And there are two really good examples that everybody can relate to. So one example, it’s timely, is a couple of big IPO’s in the last few weeks of Lyft and Uber. And when you think about it their technology appears as simple AI, it seems like rideshare is a pretty simple use case.
You want to go somewhere and you use an app to get a driver to drive you somewhere. However when you think about all the technology that is happening behind the scenes of orchestrating all those drivers, orchestrating the pricing for those drivers to help meet supply with demand, orchestrating getting you on the right route to the right place, and then following up all the billing process and all the review process. There’s actually a lot of complexity that’s all behind the scenes. But what AI is doing in addition to some really good user experience work, is it’s taking all that complexity and masking it to the user. And so where AI is very powerful is where you can use it to manage massive amounts of data, but to help you make better real time decisions. So you know, going back to the Uber and Lyft example, what if we change how we showcase how quickly a driver’s going to get there? How does that change user behavior, both driver behavior in this case, which you could think about kind of as the employee and also customer behavior of are they going to take the ride or not. And so those are some things that we all can experience and obviously has a dramatic impact on the way we live our lives. So that’s one example. I think the other that we often talk to companies about is things like virtual assistants and things like chatbots. And I think we’re at earlier stages there. But there are really good examples of things like with Facebook messenger or chatbots on websites where customers are starting to see better outcomes through things like natural language processing and understanding. So you’re not waiting on hold for an hour to talk to an agent, but rather you’re getting your answer to your question immediately. So those are two places where I think we’re starting to see some really great success in the customer service use case. And in some of the transportation and logistics use cases of the technology really rapidly scaling.
Cheryl Cran: Excellent examples. And you know what I love about Uber too is as the natural language processing and machine learning gets more sophisticated, right? As it gains more knowledge, I love how it rates the rider and the driver.
Ryan Lester: Exactly!
Cheryl Cran: So I’m rated as a Uber rider at 4.5 I think. And it’s like, damn, why am I only 4.5 I’m a 5 right? So I mean, I think there are some really cool upgrades that AI are doing for customer experience, those are two really great examples and I think there’s lots more. I’d love to maybe do a follow-up interview with you in a few months just to stay on top of that because it’s really relevant to our audience.
Ryan Lester: Yeah, sure.
Cheryl Cran: How do you see chatbots being able to increase customer service in the future? I know we’re seeing them now, but again, it’s the NLP, right? That is going to increase efficiencies?
Ryan Lester: Exactly.
Cheryl Cran: But I’d love to hear more about that from you.
Ryan Lester: There’s actually a quote I love by Brendan Witcher who is an analyst over at Forrester he says, there’s like a short term and long-term value of AI and machine learning. The long term value, the way Brendan talks about it is moving from monologue to a dialogue with your customer. So think about today, when you go to a website, that experience if it was delivered in a physical store, you would be like this company is crazy. So imagine walking into a physical store and no one greets you, no one talks to you. Or they start pushing offers in front of you. They’re like, here’s a shoe, here’s a broom. And that’s the experience on a website today. The customer is left to do much of the navigation themselves. Or maybe we have some popups or have some display ads of recommendations. But it’s not a dialogue. It’s all purely pushed by the company. So, where this is a really unique opportunity with natural language processing and natural language understanding is how do we start to create more of a dialogue? How can we do it in a low-cost way to start with a bot? So have the AI
Cheryl Cran: I’m thinking like a consumer and of a couple of recent transactions I’ve had where I was just frustrated like nothing else. And I have no problem saying one of the businesses here on this, on this podcast, but one of them was Expedia. I use Expedia for all my business travel, right? And I book a lot of travel and they do not have a nice cohesive process online where you have that chat, you know, that says to you, what do you want to do? How can we best help you? And then by the time you get to a live person, they don’t have the data to make an informed assist. It’s just such a problem. And I’m going – come on you guys, in today’s day and age, I actually tweeted about it to Expedia cause I’m like, what? What are you guys missing here around the opportunities to give really good customer service here?
Ryan Lester: Agreed. And it goes also the fact of, and that you touched on this earlier about you know, concerns and organizations of things are siloed. So the marketing team is different than the customer service team. And so you have only solid groups and they’re optimizing for their individual experience.
Cheryl Cran: Yes, that’s right.
Ryan Lester: But as a user you’re like, well now I have three different phone numbers and email addresses. And that’s unacceptable. Like in the world of today, it’s crazy to think that we’re still operating in this way. And so AI really is an opportunity to start tying those threads together and then creating those conversational interfaces where the bot says, oh, I know this is a customer service issue now I will help you get to the right person versus putting the onus on the actual consumer.
Cheryl Cran: So one of the fears about AI and automation is that it’s going to be taking jobs and we’ve done a lot of research that shows with any major technological revolution, there have been jobs gained, things have changed. We’d love to hear your take on that. What are your thoughts about AI and automation in the future of jobs?
Ryan Lester: This is a common topic we talk about and I hear a lot of questions around. So I think that in the short term people are looking at like cost management and cost savings opportunities of you know, how can I better optimize my contact center or my inbound support through AI? And there are certain opportunities where you can say having to reduce the burden on my contact center with AI. But in reality, most contact centers today are not properly staffed to deal with every customer anyways. So hence why we have hold times are why no one, they’re widening of the channel, say no agents available. So in reality, where we see an opportunity is that the AI takes a lot of the mundane and low-value work and it actually frees your agents or your employees to spend on more high-quality things. And so you think about today paying an employee to answer the same 15 questions of how do I reset my password, how do I track my package, what’s your return policy, have all that stuff go to the AI. Then, have your employees instead spend time better understanding the customer or working on cross-selling, upselling or saving a customer that might increase returns. So there are all these use cases where human support can provide much higher value. And that’s what people, that’s what humans want to spend time on. Who wants to sit at a desk every day and answer the same 50 questions?
Cheryl Cran: Agreed!
Ryan Lester: You can think about this in the world of like even factory automation now, the automation has not eaten every job. It’s eaten, the low-value jobs. And where does is it allows us to be more human because we’re doing bigger thinking, more complex problem-solving. And that’s where we wanna spend our time. So I think to your point, I think it would be just the opposite of it’s gonna take away all that mundane work that nobody really wants to do anyways. And rather, and I think another long-term trend is if you look at contact centers, there’s a lot of turnover, a lot of employee attrition because the work is hard and difficult and repetitive. So if you can say – Hey, I’m going to take all that junk work away and you can spend time really being a brand advocate and really spending quality time with the employee or our customers. I mean that’s a great job. So once again, I think it’ll shift the type of work and the longterm will make people more excited about doing that type of work.
Cheryl Cran: That corroborates our research as well. If you look at Lowe’s, they have autonomous robots that can help with customer service. Many retailers have self-serve checkout now, all of these things are shifting. The skill sets of the workers are shifting from being ‘order takers’ to being ‘solutions providers’.
Ryan Lester: I think actually using a place like Lowe’s or Home Depot is a great example. When Home Depot first started, most of the people that staff the store, cause they have very few stores were like ex-carpenters or ex-electrician?
Cheryl Cran: That’s right.
Ryan Lester: Someone would come in and they’d say, oh I’m trying to do this. And the person that worked there had all this expertise because they were in a lot of stores. What happened over time is as they expanded now people are spending more time restocking and just trying to find something in the store so that the work has become much more mundane and therefore they’ve lost that subject matter expertise. But imagine a world where the employee in the store, rather than trying to be like, well where’s this thing on? What shelf? Or like you know, why isn’t this in stock? If instead they could be an actual consultant and become an actual expert again, it’s amazing. Of
Cheryl Cran: We are talking about the customer experience.
Ryan Lester: Totally agree. I’m now forgetting the name of the store. When I was growing up, there was a store. Oh wow… And the model was at everything on the floor was for show and all it was was that you walk around and play with it and talk to the expert and then there was no inventory on the floor was all on the basement and basically there is automation to bring it up to you when you’re ready to buy. But that’s
Cheryl Cran: Yes!
Ryan Lester: And it’s not around. Help me find it because that’s, once again, low value. Amazon has everything in stock. I can get it delivered to your home.
Cheryl Cran: Well, I mean we could talk much longer. Let me ask you one more question and then like I said, I think we should set up a part two interview here because there’s so much intel here with what you’re sharing. So I used earlier the example of Expedia. How can companies like Expedia or Uber increase customer care with better integration? You gave Uber as a great example, but how could they be even better with that people tech example or AI or bots or any of these things that we’ve been talking about today?
Ryan Lester: Yes. There’s another common question that I get. So when you look at today, still much of customer service is inbound or it’s reactive. So it’s hey, I built some AI and it’s really around deflection of questions. These are the common questions I get where we see the next wave going is really much more about being proactive and proactive across a variety of locations. So not just necessarily online but also to your point in a physical store. But as you start to get to know things, whether it’s you know some context about the user. So who is this person? There’s some interesting examples happening in the apparel industry where customers are scanning products as they’re taking them into the dressing room. So you can start to get a better sense of what do we know about this person now? How do we more proactively either service them or proactively help them on their journey? And so that’s the next big wave we see where especially with AI, the cost of those proactive interactions is really inexpensive. You’re talking about a few cents for a bot to practically engage and one it can practically engaged to solve a problem before the customer knows they have it. So think about in the travel space, might your flight’s been canceled, I’m going to have a product of bot engage with you to maybe get some preferences so your flight’s canceled, here are other options today, do you have some preferences? And then it passes those preferences to an agent who is actually going to do the heavy lifting. But how can you be more proactive and customer service or how can we be more proactive in product discovery? So we were talking to one of the leading consumer brands and they make fragrances like perfumes. And those typically turn those over every year or 18 months when they stopped making certain fragrances. So someone will come to the website and say – hey, you don’t let her sell the one I loved. What should I buy now? And that experience today is kind of like left to the customer. Either they have to go into a physical store or they have to try and figure it out. But imagine a bot says, well, what did you like about the last one you had? Like did you use it in the summer or did it feel summery or did you like to use it when you went out for a date? So it can take some variables from that customer and than offer them a better option. So help them with things like product discovery. So this proactive outreach of AI I think is really the next big wave. Once again, solving the problem before the customer knows they have it or helping them find better product fit for the thing they want to buy from you.
Cheryl Cran: Excellent. Good. Any last insights or comments before we wrap up this part one?
Ryan Lester: Yeah, so I think the biggest thing I say to everyone is if you’re not doing AI, then you inherently are falling behind your competitors. We just did some big did some big research with Forrester and there’s a, there’s kind of a maturity that happens with the customer experience and the most mature companies are investing in AI at a faster rate and it’s further distancing them from everybody else. So just like there are technology advantages in other ways, AI is also giving the best customer experience companies a bigger advantage to being, it’s a catalyst to get them further advancement. So don’t think about it as we have to get the boardroom involved, we have to spend seven figures. AI projects can be very manageable and can be done once again in weeks. So if you’re not doing it today, start now and there’s really good ROI to be had and don’t make it a science project. There are really great
Cheryl Cran: That’s brilliant advice. And Ryan, where can people find your podcast if they’d like to go search it out?
Ryan Lester : AI IRL podcast, and it’s on all the major services, iTunes, Stitcher.
Cheryl Cran: Absolutely! And so like I said, in the future we’ll talk about some of these thoughts I have around leveraging AI. I think I’ve got some really brilliant invention ideas here I’d love to share with you down the road.
Cheryl Cran: Thanks for your time, Ryan. Excellent insights. Excellent interview, enjoyed talking with you and I enjoyed our dialogue.