How GoTo Sees The Reality Of AI Adoption In The Workplace

[00:00:04] Welcome back to the Tech Talks Daily podcast. Now, a quick question for you all. Have you ever noticed how workplace conversations this year seem to circle back to AI? Yeah, I know, it's felt that way for a couple of years now, but many teams still don't have clear rules for how they're supposed to use it every day.

[00:00:26] So in today's episode, I'm joined by David Evans, Chief Product Strategist at GoTo. And together, we're going to take a practical look at what the future of work is starting to look like, especially when you strip away the hype and focus on what is actually changing inside organisations.

[00:00:44] Because we're going to talk about employee readiness, why everyone already gets AI is a very dangerous assumption, and why the Gen Z stereotype doesn't always hold up when you look at the real workplace adoption. And we'll also get into today what this means for the tools that people rely on every day, whether it be contact centres, customer support teams, or the communication platforms that underpin hybrid work.

[00:01:11] And David will share why many companies are moving towards more integrated platforms in a bid to reduce complexity and cost. And we'll also discuss how conversational AI, including AI receptionists, are gaining traction as deployment gets easier and trust continues to increase. But don't worry, we won't ignore the security side, shadow IT, data privacy, and all those new risks that come with AI sitting inside everyday workflows.

[00:01:40] So we're going to try and cover a lot today, and you're all officially invited. So buckle up and hold on tight as I beam all your ears to the UK, where you can sit down with myself and David right now. So a massive warm welcome to the show. Can you tell everyone listening a little about who you are and what you do? Yeah, thank you very much for having me. So I'm David Evans. I'm Chief Product Strategist here at GoTo. I've had two parts of my career.

[00:02:08] The first part was working within IT and specifically endpoint management, and the second half was working within business communications. I took a set of dice there, and I rolled them, and I changed industries. And the good news is that working here at GoTo, GoTo has two portfolios. It has an IT portfolio and has a business communications portfolio. So if I was going to find a home, this is a great place to be. And the role that I have here is Chief Product Strategist. I'm here to steer our products across the portfolio from a product strategy perspective.

[00:02:34] It used to be traditional product management, and how to steer through market opportunities for competitors. Obviously, now we're talking about how do we steer through the world of what AI is doing to how we build products and how we work. So that's my job right now is to help steer the company through these tumultuous times. Wow, quite a challenge there, I would imagine. There's so much going on, and there's a lot of confidence from leadership about AI adoption.

[00:02:59] But just how prepared are employees in reality to using AI tools effectively in their daily work? And is there any resistance to AI and change and fear of AI? What are you seeing? So we're seeing – well, firstly, we're seeing what you said around some confidence from a leadership perspective. We do a Pulse of Work survey every year. We've been watching this progressively over the last few years. And there is some general confidence around the way businesses are deploying AI tools.

[00:03:26] But what we see on the flip side is that nearly 90% of employees are feeling like they're not making the most of AI. They're kind of in a fear state. And that fear state is pretty typical when a technology is moving so fast that it surpasses our ability as humans to even comprehend what it can do. So there is a bit of a disparity between the two. And the reason we think that is – and there are probably many reasons why that is, right? But the reason we think it is is that businesses are thinking about AI as software, as a tool.

[00:03:55] Thinking about it as something – you put it out there, people will use it, and you'll get the benefits. But it's not that. It's an existential change to the way that we work. And every function needs to reimagine what it's doing. So when businesses think about AI, they need to think about the technology and making the tools available. But they have to think about that kind of psychological reimagining of every function within the business that AI is disrupting. And we think that's one of the main reasons why there's a disparity between, hey, we've got the tools and employees feeling like they can't make the most of it.

[00:04:25] And one of the things I love doing on this podcast is busting a few myths and misconceptions. And one of the things that I loved about what I was reading about you is you've challenged this idea that, hey, Gen Z automatically understands workplace AI. And mature people in the workplace will be thinking, it's all right for you kids. You know how to use it. But you see that that is somewhat of a myth as well. So why is that assumption flawed and what kind of support does ultimately every generation actually need right now?

[00:04:52] Yeah, it's a really interesting kind of facet to what we're doing. And I want to be careful not to deal in stereotypes here. But there are trends. There are clear trends. We do see that the older demographics are a little bit more resistant. I think that's natural. That happens with every kind of technological evolution that we see. And we do see Gen Z and younger generations being generally more comfortable with this technology. But comfort isn't always good news, especially for businesses. And I think also in terms of our kind of personal responsibility with AI.

[00:05:23] So while older generations are tending to not get the best out of the tools, they're a little bit more resistant. We're seeing younger generations actually being a bit too trusting. They're sharing a little bit too much. And from a business perspective, that could be private information strategy, finance, customer information. And we've all been there. We've all seen how tempting it is to take a three-hour task and do it in five minutes. And one of the reasons we think that that comfort is going a little bit unchecked is because, well, where's the accountability?

[00:05:49] Data loss prevention tools haven't really caught up with the idea of protecting information leaking into AI tools. But where you start to see it come out is in this kind of really insidious way that, let's say you start sharing competitive strategy information about your company. Well, where it comes out is when your competitors ask, hey, what are these guys up to? And it starts spitting out your whole strategy and they start reacting to it. It's kind of an insidious thing, but there's no immediate accountability there.

[00:06:16] So what we found is that, generally speaking, older demographics need a little extra help to become comfortable. It's not their natural state to be in digital. Although the pandemic really accelerated a lot of digital understanding across all demographics. And what we find with younger people is that the comfort's there. Not always, but the comfort is generally there. But they need help to understand how to use it responsibly. And arguably, that's probably more dangerous in the near term is the sort of prevalence of sharing that.

[00:06:43] And I talked a bit about how that impacts in our personal lives as well. It happened with social media. We all jumped into social media and then we all decided, well, we're renegotiating how we feel about it. I think AI is going to be the same. How our digital image is used on the internet and how we exist there and how AI takes that and can manipulate it in both good and bad ways. We might see a renegotiation there as well. So yeah, every demographic needs help, but just in a slightly different way.

[00:07:09] And one thing that makes me nervous as an ex-IT guy is the fact that many organizations are introducing AI without any clear guardrails. Of course, we've been here before with things like BYOD. But what risks does that create in terms of not just shadow IT, but shadow AI now and inconsistent usage, data privacy? There's a long list of concerns. As I said, I don't want to be the boring ex-IT guy, but it is a risk, isn't it? It absolutely is.

[00:07:37] And I probably touched on the biggest one that I think is front of mind for us, which is data leakage. And it plays out a little bit differently depending on what industry you're sitting within. If you're in a highly regulated industry, AI is, again, in general, it's not only not a good thing, it's potentially a very bad thing. There's not checks and balances around that that allow it to always operate within the regulatory frameworks that you work within.

[00:08:01] So I think one of the areas that I think we should be most concerned about is where there are laws that govern the way information is shared, because it's so easy to step outside of those. And I don't think we've seen the full ramifications of that yet, again, because that feedback loop of when something goes wrong, it's a little bit murky. But then there is a – I think there is a wider issue of just sharing sensitive information with these models and how it's used.

[00:08:30] And I think we're all living in a happy world where AI, the good part of AI, is helping us on a day-to-day basis. But there's always this kind of clandestine sort of malevolent part where AI can be applied to good and it can be applied to bad. And I think that technology is usually the recipe, always has been. Back in the day of BYOD, we have here a go-to, a portfolio of mobile device management products that kind of help that. Technology will always catch up to defend against that. But can it be fast enough?

[00:09:00] I think we're probably in the most dangerous zone right now. So the responsibility falls on every organization. And it happens in two ways. There are practical guardrails you can put in place. So we have access as employees here at GoTo to pretty much every model that's out there and our own custom models and workspaces. But it's done using our own published version of the GPT. So we go through our own network and our IT department has created the connectivity on the back end.

[00:09:29] We don't use the public interfaces. That gives you a lot of control. But not everybody has the luxury of being able to do that. So there are some cases where you can put controls in, but it has to come down to education in the beginning. It has to come down to responsibility. And you have to update your policies and your education and be at the front edge of that. So, yeah, we're in probably quite dangerous times here. But I know there's a good place on the other end of this. When everybody's got all the AI there is in the world and it's just how we get work done, there will be some equalization. But people need to be a little careful right now.

[00:09:59] And before you join me today, I was doing a little research on you. And I was reading how you've said that AI is becoming embedded in everyday workflows rather than just sitting as a standalone tool. So what does that look like in practice? Across collaboration, meetings and customer interactions inside every sized organization. Yeah.

[00:10:19] And I think there's good parallels between how we think the recipe of introducing IT into our products works and actually how we as humans think about or prefer to absorb IT. And we think about it in three phases. The first one is productivity. So when we first started looking at using Generative AI when it first came in, it was really easy to see where the productivity was, especially in business communications.

[00:10:45] You know, summarizing calls so you don't have to write those notes up at the end, making sure you're reviewing all calls that happen, picking out the topics and the sentiment. We hit those pretty early. And so those kind of productivity gains, that's the way to get anybody hooked from any demographic on AI. Take something they hate doing and make it easy. And suddenly you're in and you're hooked. So that first phase of productivity and insights into your business, that was a big bucket. We break out insights into everything that's happening within your communications environment.

[00:11:13] The second part, which is I think where we are now, is we're now talking about workflows. How do you take these point in time kind of actions and insights and productivity and start taking over some of the multi-step, more complex things that we do as humans? And we have several. The way we think about call triaging, that's something we're looking at the moment. So, hey, you're sitting there. Customers on the phone saying, hey, I had a really bad experience. Well, how do you figure out what's happened?

[00:11:39] Well, we can turn that into a single button exercise where we look at all the previous communications, everything they bought, everyone they've spoken to. And in probably a matter of seconds, come back with a pretty good idea of what's happened there and also some steps on what goes wrong. So those are multi-step workflows that would have taken time. And quality management was another thing. We were somewhat late here at GoTo into Contact Center and into CX. We primarily serve small, mid-size and very large companies with multiple locations.

[00:12:08] So we've met everybody where they were on their technology journey. And those customers tended to be not in that first wave of AI. They came in during the generative AI revolution. And so, yeah, what we found is that by building quality management, not in the old way, using kind of code and legacy sort of logic, we built it using AI.

[00:12:32] We've made what is a really complex thing to understand every call, understand how they're adhering to your company kind of preference on service. And then crunching all of that into a score and then into a training plan, wow, that's really quite difficult. But it turns out the AI makes that really easy, especially from the consumer experience. So that middle section is where we're at, where we're automating quite complex things. Where things get really fun is number three, the third pillar, which is where things get really transformative.

[00:12:58] That's where technology changes the whole way we get things done. And we released an AI employee, we call it AI receptionist, as our first sort of productized AI employee. We've been working on it internally for a long time. And what that's done for our customers is it's shifted a lot of the work from kind of human back end and taking it right to the front line. That has drastically changed the type of service, making sure that customers can get help out of hours,

[00:13:24] making sure that if you're really struggling to hire people, you don't need to do that anymore because we can answer questions, we can capture information, we can route. We're really strong in automotive. So we're probably number one deployed in North America for automotive. And we've just released scheduling. So all of your service and sour scheduling is all taken care of by our AI receptionist now. This is where the really cool stuff starts to happen is in that third pillar.

[00:13:47] So I think where we are right now, this being buried in everyday workloads and also hiding the technology away from some of our customers. They don't care if it's AI or not. What they care about is whether there was something I couldn't do, and now there's something that I can do. That's a huge difference for our customers or something that took hours now takes minutes. That's where they're really seeing the benefits. But if we really, you know, we'll come back maybe in 12 months time and all we'll be talking about is those big transformational things.

[00:14:15] But right now, those workflows are becoming very, very exciting. And I'm glad you mentioned contact centers there because that is one of the big frustrations that many people will encounter. And on the flip side of that, they are often the early adopters of automation. But IVRs, getting people to push various number sequences to get which area they want to speak to in the organization, that's beginning to show their age now.

[00:14:40] So how do you see contact centers evolving this year, particularly in terms of smarter automation, better agent tools and the rise of more remote roles? How do you see that improving and evolving this year? Yeah, I think 2026 is that. And I've been in contact center now for the better part of a decade in one way or another. And, you know, watching the evolution over those 10 years, they're actually stubbornly, there are large parts of the world that are still stuck in the previous paradigm.

[00:15:08] So I think there's always going to be that disparity between the forward looking. And I think 2026 is the year where there's not an excuse anymore. It doesn't matter how big or small you are. There is a path for you, either on your own or with a vendor, to really transform the way that you're providing service and get away from that. Press one for this and press two for this. So I think 2026 is the year where it's like, OK, there's no reason that anybody shouldn't be looking at this.

[00:15:33] And if you're not thinking about the benefits of what this technology brings, then now's the time to really jump in with it. But I think most folks are on that journey in some way. And I think what we found, and let's talk specifically about IVR and specifically about how you root calls. There are things that AI is really good at, and there are things that a traditional dial plan builder.

[00:15:58] So one of the biggest differentiators that GoTo has had since the beginning is we have a wonderful visual dial plan editor. So people who needed to pick up the phone and talk to an MSP or somebody to make a change, they can just jump in and visually see it. It's been a wonderful thing for us. But when we built our AI receptionist, we rebuilt our whole routing logic in an AI model. And so we've discovered the good things about that, which is it's more natural, it's more dynamic. It's such a more natural conversation to have with this technology.

[00:16:27] But on the downside, there are times when you need to stick to the script. You need to do things in a certain order. And so what we're finding is that there is a blend still between the static on guardrails and the slightly unpredictable but more natural way of it. So I think we'll probably live in a world where we need both of these technologies for a period of time, is my assumption. But there's no question that once AI really understands when it needs to stick to the script and stay on a very prescribed thing,

[00:16:54] once we get that balance right, we can definitely see that you should never hear press one for this and two for that in the future. But I think it's here for some time still. And as you said, most companies are already on that journey forward and are increasingly moving towards fully integrated communication platforms. But why is integration now a cost and a productivity issue rather than just simply an IT preference that it was, what, five years ago?

[00:17:22] Yeah, so I've always had a geek passion in my life, and that's process automation. I love the idea of taking something that's really complex. And I have loads of it at home. I have loads of automations and things that trigger, and Christmas lights come on when I say turn on Christmas and all of that kind of stuff. I've always loved process automation. And what's interesting about AI at its core is that it is, in some respects, just a better way of doing process automation,

[00:17:48] is taking things that humans would do in multiple steps and, in some cases, not do very well, and doing it in an incredibly intelligent way. Obviously, there's more to AI than that. But fundamentally, it's actually a similar concept to process automation. And what do you need with process automation? Well, you need to be integrated. You need to be able to get – the software needs to be able to get to the systems of choice. And the second thing you need to be able to do is build workflows. How do you create these flows so that they're effective?

[00:18:18] And so if we think about integrations, I don't think the nature of what integrations give you hasn't changed. So when I started looking at and working within contact centers, I worked for a company that was entirely embedded into Salesforce. We built software to look and feel like Salesforce. So we started with integration and embedding at the core of it. It was our business model to do it in that way. So I've always probably been on the pro side of what an integrated story is.

[00:18:44] I think what's changed now and why it's gone from, hey, it's better if we're integrated, it's now essential. And I'm heading to Enterprise Connect in a couple of weeks' time. I'm doing a panel session on how integrations are kind of destroying the typical model of contact centers. I'm very passionate about this topic. It's now non-negotiable because when you see the power of technology and especially AI, if you can give it the right federated secure access to the right data and you see what it can do,

[00:19:13] it's a wonderful transformational thing. But I think that value has always been there. It's just been really hard to get out, whereas AI helps you unlock it a bit better. So being integrated is absolutely essential. And it's probably the biggest investment that we're making right now. As I talked about having an automotive offering, we've got a healthcare offering coming out this year as well. So we're out there embedding it in all of the healthcare systems. We're already very, very strong in healthcare. This is now a tailored kind of HIPAA compliant package. So integrations is front of mind for us.

[00:19:42] And once you sample the power, we were at NADA a couple of weeks ago, which is the big automotive conference in North America. But people come from all over the world and seeing our AI scheduling interact with like X time and book an appointment and it's showing up. And then customers tell it. This is like witchcraft to people that have sometimes been a little bit behind.

[00:20:08] So integrations, I think, is although we think about it as like, hey, we've been doing integrations forever. Just when you couple it to AI, that's when things get very, very exciting. So, yeah, integrations are a big part. They're not always easy. They're doing all of this stuff for us. But right now, you know, there's still some work involved in it. But, yeah, it's a very big part of what we're doing right now. And your passion for this space really shines through today.

[00:20:34] And conversational AI and tools like AI receptionists that you've mentioned today are beginning to gain trust with enterprises now. So what is it that's changed that make businesses more comfortable in deploying these systems at scale? Because traditionally, they've been risk averse, cautious to things like this. But there seems to be a real appetite for opportunity at the moment. Yeah. And I think it's we've been in.

[00:20:59] We didn't jump in, as I said, that first wave of AI, prior generative AI and LLMs that when everybody had their own bespoke models. We had a philosophy here at GoTo. It's always been the same. We're the champion of small, midsize and multi-location businesses. And that philosophy means that everything we build is at an ease of use and at a price point that our customers can consume. It's everything we do has to fit this deep criteria.

[00:21:25] And when we looked at the early kind of conversational AI that came out, it was very expensive. It was also very poor quality and it was very hard to deploy. So there was no chance of us getting involved. I think what we've done now since LLMs and generative AI, especially in the last 12 months, 12 to 18 months, the quality of everything across the board, the quality of the interactions, I think is really important. The ease of deployment has become within reach.

[00:21:54] It is within 10 minutes you can have an AI receptionist answering your top 10 questions. Literally within 10 minutes, we just go scrape a website, go scrape any knowledge base, any documents you've got, pull it in. It's that easy to deploy. But the one thing that if I were to choose one thing, it wouldn't be either of those two things. I would say it's the quality of the voice, the actual voice interaction that has changed.

[00:22:18] As humans, we're disproportionately resistant usually to an awkward interface where there's long pauses and the voice isn't very good. It's a real turnoff as a consumer. And I think we're now at the point where it's so natural to interact with this technology that we're starting to enjoy it. And as we start to enjoy it more, we start to get back. Voice has been on the decline in favor of digital. What we found with our AI receptionist is that actually people want to use voice.

[00:22:46] They just don't want to sit in a queue for ages and then speak to somebody that doesn't know what they're doing. If you can phone up and immediately get something that can help you to do what you need to do, we're seeing this big renaissance in voice. And I'll say one thing. I will know that we've got there when this one thing happens that I'm really passionate about. Right now, when a business is thinking about their brand and the way they serve customers, they say, our brand identity is this. This is how we serve customers. You see it everywhere. And everybody chooses their tribe and how they want to serve.

[00:23:14] What this technology now allows us to do is build profiles of our customers that we serve. And some people love small talk. They love the chat. They love to go slow. And some people are like, time is money. Get to the point and give me an answer. When we start to see humans, when we start to see brands saying, it's not about how I want to serve. Hey, how about I serve people how they want to be served? And when you take an AI receptionist and you apply these profiles, you see just how powerful it is.

[00:23:39] So not only do you get, wherever you call, you should be getting a good service, but you should also be getting your service. I think that's one of the real promises of conversational AI is that we'll get to that point where we're getting served how we want, not having to choose a brand that is the way that I want to be served. So I think there's a lot of really, really amazing stuff that's happening. But I think that voice quality is really central to what I think is helping adoption right now. Yeah, I completely agree with you.

[00:24:07] And as generative AI inevitably becomes more embedded in communication platforms, are there any security capabilities that IT leaders should expect from providers like GoTo to manage privacy compliance and governance risk? Because I would imagine that when people come to you, you'll get various stakeholders. They'll have their needs and requirements, but then IT will get involved and quickly they've got a different set of requirements from you. So tell me more about that.

[00:24:33] Yeah, so I think we, and I'm reminded again of what we talked about earlier about technology catching up. And also when you see that tied with what small, midsize and multi-location businesses need, there's a, in the enterprise, we can see a world where enterprises and global systems integrators work directly with AI models. They can leverage it. They have the money and the resources and the tools to take advantage of it.

[00:25:00] But we think that smaller companies will always need, will always need help. And in fact, more so. The more that AI surpasses their ability to keep up with it, the more they need a custodian, a partner. And that's how we think of ourselves in the market is that we do all that hardware. We think about all this gnarly technology and we bring it only when it's ready and we pop it kind of out to you. And that's the same with security. So right now, making sure that we are compliant with regulations, making sure that information is secure, all of that is taken care of by us.

[00:25:30] I think as we move into the future, there are a few things that become more important. I think we'll see more zero trust architectures out there. We have, you know, GoTo is a pioneer in zero trust in our IT solutions right now. And I think that will look like human in the loop in a lot of cases. So rather than AI being able to just go off and do things, there will be a time when AI needs to come to a human. And that will actually inherit the permissions of that human to actually get things done. And it means human in the loop is a big part of what we need to do.

[00:26:00] So I think, you know, zero trust in human in the loop, I think you'll start to see more of that over time. But then it comes back to the basics. Where is your AI going? You know, how is it being used? How is the any LLM that you're using that's collecting data? You know, how are you securing that as well? And the final piece is being auditable. Now, I have my concerns right now about the audibility. Like if I want to know what an LLM knows about me, like how do I know that?

[00:26:26] And I think as vendors, we and certainly as GoTo, we think a lot about how auditable AI behavior is. So, for example, if an interaction comes in, we have a single platform for UCAS and CCAS. There's no multiple platforms bolted together. It's a native platform, which, by the way, is quite hard to do. It's the road less traveled in the industry. But what it gives you is a seamless experience. When a call comes in, it might go into the context and into the back office.

[00:26:53] And what we're able to see is when it hits an AI employee, you can see exactly what was said. You can see what skills were triggered. You can see what data was pushed. You can see forensically everything that happened. So, you know if something goes wrong, you know exactly why that is. So, I think those are the things that you want to be looking for is that there is a security model in place, that there is an understanding of where the data is going, and that you can audit it as a customer, that your vendor is giving you that visibility.

[00:27:20] So, those are the things that security has to be built in alongside AI. Otherwise, it will probably fall apart on us. So, yeah, that's what I would say is important. Well, so much food for thought and so many big takeaways for people listening. And this space is moving at breakneck speed. And at the same time, there's almost a realization that it might not move this slow again. It can be difficult keeping up. So, people listening want to find out more information about everything that you guys are doing this year and beyond.

[00:27:48] And keep up to speed with some of the inevitable announcements that will be coming out through the year, I would expect. Where would you like me to point everyone? Yeah, I think GoTo.com is always a good place to start. Actually, keeping websites updated fast enough with the amount of software that we're producing right now is actually, you realize that you stretch some of the boundaries of some of our web teams who hate us right now. We've always been very fast at creating software for our science, but now it's in the stratosphere. So, GoTo.com is a great place to go.

[00:28:14] The Pulse of Work survey, really, really nice piece of research to understand what's happening out there more generally. And LinkedIn, there's an army of people from GoTo that are all over LinkedIn. Everybody's very welcome to connect with me and my colleagues in the GoTo channel. That's probably the best place to consume the front edge of what we're doing. But also, say, if anyone's at Enterprise Connect, come see us. We're at NADA. We're going to be at a lot of the healthcare events. And GoTo as a company, we don't spend big on advertising. That's not really our model.

[00:28:44] We do. We have, even just as a UCAS and CCAS portfolio, we have 100,000 customers. And a lot of that comes through our wonderful partner network and through word of mouth and through people connecting with what we do as a brand. So, once people find us, they tend to stay as well. So, yeah, I think if that sounds like, you know, if you're big and have multiple locations, if you're a mid-sized small customer, that's what we're here for. So, yeah, come listen to what we say. Our software doesn't have to be for you, but hopefully we can help you along that journey.

[00:29:13] And if anybody wants to connect with me personally, you can find me on LinkedIn. I'm always happy to talk to people that are trying to deal with the same challenges that I'm trying to steer us through as well. So, yeah, that's where I'd go. Well, thank you so much for joining me on the podcast today. We covered a lot there from how conversational AI is gaining momentum thanks to easier rollouts and increasing trust in tools like the AI receptionist that we talked about, and also why companies are shifting towards fully integrated communication platforms

[00:29:43] and cutting complexity, cutting costs. So many opportunities here. So I'll have links to everything that you mentioned. In particular, I would love people to follow you on LinkedIn. There's a lot of great stuff coming out of that channel there. So I'll have links there. But thank you for sharing everything with me today. Really appreciate your time. Yeah, pleasure to be here. Thanks for having me on. If there's one theme I'm taking away from this conversation today, it's that workplace AI adoption is becoming less about the model

[00:30:11] and much more about the operating system around it. Clear guidance, responsible use, and support for every generation in the workplace matter a lot more than just assuming, hey, some people will figure it out. And I think David made a very strong case there that the winners this year will be organizations that remove friction, simplify the stack, and make it easier for people to do good work without jumping between five tools and a dozen tabs.

[00:30:39] Let's face it, we've all been there. And this is where integrated communication platforms, smarter automation, and better contact center tooling can genuinely change the employee experience, especially as more roles become remote and distributed. But yes, there is a trade-off. The easier these tools are to roll out, the faster shadow IT spreads, and the more pressure falls on security and IT teams to protect data without slowing everyone down.

[00:31:08] And that tension will help define a lot of the next chapter of workforce technology and how successful it is. But David and his team at GoTo, they certainly seem to have mastered it from their side. So I'll add links to GoTo and where you can connect with David, and I'd love to hear your take too. Do you think the biggest blocker to AI at work in 2026 is skills and culture, or a lack of clear guidelines? Or is it something else?

[00:31:35] Share with me your thoughts, techtalksnetwork.com. I'll be over there waiting to hear anything that you want to share with me. Let's keep this conversation going. But right now, it's time for me to check out for the day. But I will be waiting in your podcast feeds tomorrow, so I will speak with you all again then. Thanks for listening. Bye for now.