How AI is transforming the hourly workforce webinar

Daniel Blaser (00:00):

Hello everyone and welcome to our panel today, all about AI and how it's impacting the hourly workforce. We've got a lot of experts with us today to share their perspectives and their knowledge, and I'm really excited personally. To kick things off, my name is Daniel. I'm with Workstream. I'm gonna give each of our panelists the opportunity to also introduce themselves. Ana, let's start with you.

Anna Khan (00:24):

Yeah. Awesome. Thank you so much for having me. So I'm Anna Khan. I'm a general partner at CRV. We are one of the oldest venture capital firms in the us. Just raised our 19th fund of 1.5 billion. And the reason I'm here today is because we were one of the earliest investors in workstream. And a lot of what I care about and am passionate about is how we build and develop software for what I like to call is the forgotten worker. There's so much innovation for the white collar workforce and, you know, all the software products that frankly all of us use on a day-to-day basis. And yet for so much of America, they're still sort of mired in manual processes. And so the work stream was my first check at CRV and is very near and dear to my heart. And I'm excited to talk more about what I think is especially unique about the product and about its application of ai.

Daniel Blaser (01:26):

Awesome. Well, thank you. Ericka, I'd love to hear brief intro for you, please.

Ericka Garza (01:31):

Good afternoon, everyone. My name is Ericka Garza, and first and foremost, I wanna thank each one of you for inviting me to be part of such a special panel and topic. I have become a huge fan of workstream. I've had the honor of most recently become an advisor for the brands. It's a tremendous honor for me. I've been in the franchising space for about 20 years. I've had the, the, the fortunate opportunity to work at global organizations like Yum pizza Hut bot Pizza seven 11. And most recently I stepped down from my presidential role at Buan, which is a global company. I'm also serving as the Hispanic chairwoman for the IFA board, and I serve on the board as well. And thank you for having me again.

Daniel Blaser (02:20):

Yeah, absolutely. And Bo, love to hear your intro.

Bo Li (02:25):

Hi, can you hear me?

Daniel Blaser (02:27):

Yes.

Bo Li (02:28):

Hi everybody. This is be, I'm so glad to be here today. A little bit about myself. I have been building software for SaaS software for over 25 years before workstream. I have been working for a company called a DP for almost eight years. I, a year ago I joined Workstream because workstream is such a almost awesome company. And it's focused on a very special segment, desolate workers, which really need a lot of technology. So I'm very glad to be here. Recently, I'm working on the AI product for workstream, and we're building something very special use case for desolate workers to help them find jobs using the chat bot. Nice to be here.

Daniel Blaser (03:23):

Awesome. Well, thank you. Really excited to to chat with all of you and hear so much about your, you know, individual experience and backgrounds. The first question I had is for Anna, when you kind of look at how, you know, new technology makes its way to different industries, what trends do you see? And like, specifically, I'm wondering, you know, when you look at the hourly economy or the deathless economy like where do, where do some of those industries fall in the typical adoption curve?

Anna Khan (03:55):

Yeah, I think that's a, that's a pretty layered question. Maybe I'll address it. Two ways. I think the first is, and, and, and this is not to say that non dustless workers don't have core use cases, but the way I see the Dustless market is there are a few things that they really struggle with that they have to get right. The number one thing, and this is actually part of the main pitch Desmond had given me when we first invested, is they really deal with turnover and labor, labor shortages. Like asked someone who has, who is either a franchise owner or a manager at a franchise, like that's their number one issue. And so in my investment horizon, in my investment thesis, I look for does this software or this application of software solve your top three core use cases? I'm sure there are 10 or 20 other things that products can do, but those are nice to haves.

(04:56):

And in the dustless workforce, I think there are a few things we chatted about labor turnover. So that's, how do people find a job? How do they show up to an interview on time? How do you then get them onboarded? And then Bo you worked at a DP so you know this, how do you get them paid? And then all the other stuff comes after, which is how do managers talk to their teams? How do they motivate their teams? I think that's likely gonna happen in the second and third wave. When you talk about sort of the the cycle of innovation, I don't even think we're there yet. I think the first wave of critical use cases has still not been met, which is why as a VC and as an investor, we get so excited about this market because there's so much that's, it's still not offered. That is still, like, I sort of, you know, said in my intro in binders, in papers, like, still faxes are used in this industry. And, and so that's what I think is, is, is so important and can create so much value, and then we'll get to the second, third order use cases.

Daniel Blaser (06:04):

Yeah, yeah, that makes a lot of sense. Now Ericka, I know you, you know, you mentioned in your intro you have this, this wide background in the franchise world, and I know franchises are all about like scalability. Why is technology such a key part of successful scaling?

Ericka Garza (06:23):

Yeah look, first, I think that's a great question and I, I'd love to share with you my perspective from having the experience of running a franchisor and working directly with franchisees, because I've always been the liaison <laugh> between both. So I get both perspectives and I play and I understand both worlds. And, and, you know, I, I think my response, I think it's important also when it comes to technology. It's, you know, from the franchise or perspective, the expectations are way higher with franchisees, what they expect from the franchisor side. So I wanted to, to share that. And scalability is fundamental. It's an aspect of the franchise business model. And it plays a pivotal role in achieving successful scaling technology. Empowers franchisees to expand and grow efficiently, efficiently by street blinding operations, has enhancing customer experience and obviously optimizing decisions. In the process, I can tell you that technology is a, at least what I consider to be a key part of like scaling a business from the FraNChiS to franchisee by operational deficiency, data-driven decision making, standardization, enhanced customer experience.

(07:38):

From my experience, I know that from working at Yemen Banon, but most recently when it came to technology, I'll be very frank with you, I think the site of <inaudible>, we did lack quite a bit of technology, and I think it, it unfortunately hindered some of the business because it was difficult to keep up. But some of the examples that I can share with you that I think Yum did an excellent and, and when it comes to technology and, and, and driven solutions. But for us, as I reflect back, what was limited to us, I think back about not having any labor metrics or labor system. And that's critical, right? When you're trying to like control p and ls or when you don't have loyalty or you don't have delivery I do think it's very important to share with you that all Baan is a non-traditional business, but at the end of the bus, at the end of the day, the main goal for the franchisor and franchisees is to be profitable. And so when you don't have the technology that's needed, a, to keep up, two, to keep customer service, you know, I, I won't say the word to be in trend, but I, but I will just say that it, it can hinder the business and that's why I I strongly think that technology is just incredibly important in order for you to be able to, to grow business and scale.

Daniel Blaser (08:54):

Yeah. Yeah, that definitely makes a lot of sense. And you know, we've kind of been talking about technology more broadly and obviously today's conversation, we're gonna narrow that down a little bit more to AI specifically. On a, now there's been a lot of discussion about AI last six to nine months, especially, it seems like you can't go anywhere or talk to anyone without someone mentioning, you know, chat GPT or something. Right? can you kind of talk about, from your perspective and what you get to see in your role like, you know, what do you think about this recent excitement around AI around the recent AI developments, how it's impacting different industries?

Anna Khan (09:35):

Yeah. You know I'm sure most people that are are, are gonna listen to the, the panel are aware that the markets were in a place of struggle publicly. Things were not how they looked like in late 2020 and 2021. And it was a little bit dry in terms of both IPO number and deal velocity and AI sort of emerged earlier this year, actually in November of last year, as sort of this, you know, lighthouse of, of sort of new innovation and a, a new wave that investors and frankly, developers could get excited about. So I think it's a mix of like, we really needed something new to get excited about in terms of innovation, and also a lot of amazing technological advances went into making it what I like to call sort of customer and business ready. So I think it was, it came really at the right time for the industry.

(10:39):

That's sort of the positive way to look at it. I think given that I spent most of my time in application software, I think the more nuanced view would be I think it will be very hard for AI companies just for the sake of AI to ramp up and be scalable companies, right? If you're gonna be a net new customer service chat bot, but you're starting off just on the basis of ai, I think it's gonna be very hard to find scale. What I like, and this actually applies very much to workstream, is existing companies using AI to accelerate their existing moat and their existing business use case. So Intercom is a great example. I was an early investor in that business. They're already a service chat bot. What did they do? They incorporated AI in sort of their core use case. They launched a you know a product called Fin Workstream.

(11:36):

I loved what you guys built. I mean, you are a sort onboarding platform for dustless workers, and what did you do? You brought AI to accelerate that use case. And so I think we're gonna see the real orders of magnitude change in AI when businesses that are at scale, and maybe not even the scale of Intercom or work stream, maybe even think a hundred, 200, 300 employee companies use sort of AI much in the same way we use the acceleration of cloud computing or mobile. But don't just start an AI company just for the sake of AI unless it solves a core use case. That's sort of the conclusion that I've come to after sort of nine months of this. But again, the beautiful thing about Silicon Valley is things change all the time, but that's kind of where I would stand, sort of the positive and then the more nuanced way to look at it.

Daniel Blaser (12:32):

Yeah. Yeah, that perspective makes a lot of sense. And I think that transitions well to the question that I had for Bo, which is like, you know, kind of given this context, you know, Ericka talked about experiencing some lagging technology in previous roles based on what Anna was saying about, you know, building AI into existing solutions. Why, why do you think, Bo, that now seemed like the right time for workstream to kind of make its expansion into ai?

Bo Li (12:59):

Interesting question. Actually, workstream has been looking into AI since we first start. One of our founder, max, he is a AI mer majored engineer. And when he and Desmond met years ago, the first use case was a AI powered engine. But over the years, as Anna have said very well, we shouldn't be just for the sake of technology, doing technology, we should look for customer issues to solve. And the first technology we have brought into tech desex economy is using text. And we have been very watchful to new technologies. As on our, on our mentioned since late last year, we have you know, the, the AI came in from a open AI chat, GPT. And from that moment, we have been investing our time to look into what does technology mean, right? First of all, study it's maturity, also understand what can it do.

(14:08):

Once we understand those two, we look into our customer base, our industry to see what problem that we really knew very well that this technology can solve. And when we add this two pla you know, one plus one, the problem on one side, technology on the second side, we found a perfect match. The AI provided gave a very awesome solution for translation. 20% of our work workforce are non English speakers. So using AI to help translate, communicate is a huge tool, right? The second thing that AI has brought to us is text gen generation. So we look at our space, look at the problem we're trying to solve. Well, the problem is the restaurant owners are so busy, but they have such a high hiring needs. They're spending time on writing job descriptions, which is, you know, important with ai. We just launched our first AI use case, which is a job description generator, right, by AI awesome fit. So what I'm saying is we believe technology is mature, we understand our customer and our problem space very well. That's why this is the awesome time for us to start investing in ai.

Daniel Blaser (15:31):

Yeah.

Anna Khan (15:32):

And Daniel, you know, if I may, I think Bo brought up a, a, a really good point. One of the other, I think the best way to say it is cultural shifts that happened is I think it was really interesting that Chad, GPT both, you know businesses could plug into it, but also customers could use it. And so the funny thing is, a lot of aspects of ai, maybe not this powered, existed for a very long time, but when you packaged it to a business, they would be a little bit spooked by it, right? What are you doing with my data? Actually, no. Like, I wanna talk to a human. I don't wanna talk to a chat bot. This is weird. I don't trust it. What if it gives me the wrong answer? But since they were interacting with chat GPT, and it was all over the news in a more fun culturally accepting way, way, it actually made this perfect storm for the business use case as well.

(16:29):

And in application software, we've actually seen this a lot where technology becomes much more accepted in the business use case. If we experience it personally. A lot of people believe that's why Slack took off the way it did, because we were so used to iMessage and WhatsApp at that point. You know, the Slack use case already existed in Yammer years ago. Business chat wasn't a new thing, but because we were so inclined and we understood it, like, wow, this works, someone can respond in five seconds, then, you know, it sort of took off. So I think people underestimate how much, what happens at home and how we use technology in a consumer fashion, how it, you know, very much sort of moves to the business side as well.

Daniel Blaser (17:17):

Yeah, yeah, absolutely. Bo if you wouldn't mind muting just I think what's happening is you mute and it, the background noise goes away and then it ramps up again. So just anyway, we can kind of play around with that a little bit. Sorry, did you have something you wanted to respond to though with, from Anna? From Anna's comment, or just wanna give you the chance, but Bo okay.

Bo Li (17:41):

Can you hear me?

Daniel Blaser (17:42):

Yes. Yeah,

Bo Li (17:44):

Yeah, definitely. I do feel, I, I totally agree. There is a adoption curve or adoption trend of technology. Technology always come from early adopters and consumers, and it goes to business, right? And then from a business perspective, always goes to the high tech, high touch industry first, and it goes to general business. And that's why I felt workstream is at a perfect stage where in this industry, people have not heard, I literally have spoken to business owners that they have never chat, check out with chat GPT, they have no idea because they're so busy. And it's up to us, the technologists to bring the technology to them and make this accessible to solve their business problem.

Daniel Blaser (18:36):

Yeah. Ericka I'd love to kind of hear your perspective. We're talking about, you know, the concept of technology adoption and then specifically around ai. Like, who's feeling, who's feeling more or less comfortable with it? You know, now we're, I, it seems like a lot of people are, are more aware of it. Like Anna was saying what is it? What does the franchise space look like? Like, is there kind of that same, the same excitement around AI maybe, or is it a little bit more subdued than the broader tech market?

Ericka Garza (19:06):

Yeah. So before I answer that, I wanna compliment Anna and Bo you di you guys are doing such a great job. I'm learning so much from you guys and your point of views, and Anna you know, to go back to something that you said, I, I appreciate your honesty because I do believe, you know, in order for me to kinda approach this question, I think it's, it's, it's important that, you know, it's something that we know, but it's important to be, you know, said again in the QSR space, in the franchise space, particularly in the restaurant. This is my personal point of view, I think there's been an unfairness of, of, of, of really understanding and embracing and adopting ai. I, I just do, because I think that franchisees and franchisers are so fully concentrated, which I understand on the labor and the food costs and the supply chain and all the other issues that come with running the, the restaurant space.

(20:00):

And I think therefore, as much as AI has definitely made an impact on the franchise space, I'm just not sure if the franchisees or franchisors are jumping in or have, like you said, that subdue feeling as other industries do. I think I think as much as they've been able to catch on, I think that there's a lot of, in addition to the concerns I just talked about, there's the privacy, right? There's the overall cost, which is very expensive. I think the bigger franchisors are able and have the capabilities, you know, with the franchise organizations and communities to have these pilots. But I do think that you're gonna find that sentiment that a lot of franchisees and franchisors why I think they're, to share the same sentiment. I think it's gonna be a little bit more of adopting the approach of let's wait and see what is actually gonna happen. Because I do think the concerns are so high. And again, in my humble opinion, I think it's, it's disappointing because I think it's something that could be incredibly helpful in so many ways. But I think until these alarming concerns that are impacting the bottom line and the business and employees as well the focus is gonna be highly concentrated in those areas. And I think for, for quite some time, honestly.

Daniel Blaser (21:21):

Yeah. I guess, you know, that, that's a good transition to a question I had for Bo. You know, Ericka's mentioning some obstacles when it comes to, you know, certain industries of the franchise space, QSR the, she, she talked about just cost both in terms of like actual cost, but also, you know, time, their, their, you know, a lot of people are just focused on day-to-day running their business. They, they, they can't really, you know, worry about AI or, you know, other new technology. Given some of those obstacles, like what you know, what did we kind of prioritize as, as workstream was looking into, you know, expanding into ai? Like, how did you know, how was workstream AI built with some of these concerns in mind, I guess?

Bo Li (22:06):

Very good, Danielle. Good question. So one thing that we have learned is when we talk to our customer about ai, it doesn't register because nobody knows what the heck is ai, right? <Laugh>. It's like if we are a car builder and we find a new way of building engines and we talk about engines to a person who needs to go from 0.0 A to point B, that doesn't actually, to them it does. It's meaningless. So from a work stream perspective, we have to go through our core. What are we here to do? What problem are we trying to solve? Talk to our customer about the actual problem and how we're solving it. Maybe the last sentence is, by the way, this is powered by ai, but it's more important to talk about the problem and how we're solving it is less important to talk about the technology, if that makes sense.

Daniel Blaser (23:05):

Yeah, yeah. I like the, the car analogy is great, I think, 'cause for me personally, I'm not a, I'm not a big car guy. Like I, you know, but you show someone in a, you know, new Subaru Outback going, you know, camping or fishing, I'm like, oh, okay. You know, the use case, like you said, solving the actual problems. And that, I think that goes, you know, that fits right in with what Anna was saying as well, about, about ai. But it's, you know, it's gotta be rooted in actual problem solving, not just for its own sake. Now Ericka, I did wanna ask you about, you know, you kind of mentioned some of the obstacles around, you know, new technology adoption. I'd just love to get your take, you know, as you kind of learn about workstream, ai, workstream assistance, some of this stuff. What was, you know, what was your kind of, your initial take, and specifically what do you think it could mean for helping those in the franchise space?

Ericka Garza (24:00):

I, I think in the, in the context of franchises where scalability is so crucial I believe that workstream AI is a game changer. I really do. I believe that so many franchises often face challenges in managing so many multiple things, whether it's hiring, screening, retaining and it's just hard to keep that, that flow and that process keep it going efficiently. I believe that integrating work stream AI into franchise operations will lead to improved efficiency, reduce time and ultimately contribute to the success and growth of all the franchise businesses. Plus the fact that inter lingo <laugh>, I think is, is, is incredible. And I, I can tell you that you know, running the franchisor and being incredibly involved in the day-to-day operations and being the leader of rolling up your sleeves and interacting with the employees at the restaurant and cafe levels, I can tell you from firsthand experience that a lot of the times that our employees weren't able to go to the next level or get any clarification and concerns that they had, it was always an issue because of language barrier.

(25:22):

That's one. Number two, there was an issue of at home, many times not having technology in their house, but they did have a phone. Number three, the intimidation, right? Because of not knowing what to ask, what to say, am I gonna sound correct? And I think the fact that workstream, I, in my, in, in my opinion, it's, it's, it's one of those, you know, when when I started getting to know more about workstream and the benefits to the employees, the fact that there's a platform and there's a business and there's leadership in the top that is thinking of hourly employees and how to facilitate the process, not only for the business from the HR side of it, but really with the heart and the soul and the mind and the intention of the actual hourly employees and how to get them to the next step and how to facilitate the process and make this more mechanical and more user-friendly for them to be able to go to the next level. So I think it's incredible, and I, I am a strong believer that it's a total game changer for franchisees and franchisees, but most importantly for the employees.

Daniel Blaser (26:26):

Yeah. Yeah. Well, that's great. I'm, I'm glad to hear that you, you know, you kind of see that potential. And I, I did wanna ask, you know, Ana, you, you talked about this a little bit earlier, you know, what you kind of see as being the, you know, the, the unique value of workstream ai, but I I to kind of, you know, dial down in that a little bit more, you know, like, what, what do you think are some of the other differentiators when it comes to AI for the Desus workforce, specifically the, you know, kind of the workstream assistant model. Like how do you think that that could, you know, influence hiring and, and retention? And some of these things,

Anna Khan (27:04):

I think Ericka sort of hit the nail on the head, which is they have a phone, even if they don't have enough technology at home or are comfortable interacting with it. And I think what's really great about what your team did and and bo with, with your leadership is you took the AI where it can impact them the most, right? The modality that they're used to is a text message. And Ericka, you, you, I loved all three of your points, but your third point was also like, sort of intimidation of what to ask for. And here you're lowering the bar of like, ask me any question. Like, I will have an answer for it. And even if you have one of the best labor processes, maybe you're one of the biggest franchises in the world, you're not gonna get such quick tailored responses without ai.

(27:56):

And so I I, I love that you sort of met the customer, or the, right now your customer is basically that employee, even though the business is, is, is paying for it right where they needed it most. I, I think that's one. And then I think that one of the key ways to measure this goes back to like actually hitting the bottom line, is hopefully now that you've eased the burden, you sort of lowered the bar of interactivity, you now see this AI feature actually increase your attach rates. More people are buying the platform, more people are applying to the program. And when you can show that real ROI to the business, hopefully, and, and I'm sure it will sort of increase that revenue growth, increase our expansion growth, you know, hitting our net dollar retention. And then once you sort of solve that for one product, but already discussed this, you can start doing it for job description generation. And as a software investor, that's what we look for. We look for, you know, what was your land in terms of an A CV and how did you expand? And the fact that you're able to do it with AI and you can paint that story. And then also most importantly, to Ericka's point helped that employee that you have built the product for, I, I, I, I think there's nothing better.

Ericka Garza (29:18):

Yeah.

Daniel Blaser (29:18):

Yeah.

Ericka Garza (29:19):

And Anna, if I, if I may add to something Bo and I think it's you know, I I, I'm a big believer of always, and I'm sure everybody on this panel, you know, probably has the same mindset, but I always put myself in the individual individual's shoes, right? So what timing, what critical timing is for me might not be for somebody else. And so these responses, right, could seem like forever when without thinking, well, somebody within the office, the GM or whoever should be responding to that, they've got a million other things to do as well, or they might not not know how to prioritize. And with this feature, it is just this ease, I think to to, to the potential employee. And also we are in the QSR space, the restaurant industry where, you know, I, I can tell you with <inaudible>, one of the things was in some areas we're very fortunate to have loyal employees to retain them, but in many areas, right next to one of our locations, they would leave for a quarter or for 10 cents more than what you were paying for them. But why, because of timing, why, because of so many, so many factors that were differentiators from what you had. But one of 'em was speed, one of 'em was communication, and most importantly was it took you a minute to get back to me. And so there you go, you lose a great employee because of timing. So I think that this is brilliant bo that you guys have been able to think about, I mean, about absolutely everything to make this easy for the employee.

Bo Li (30:53):

That's awesome. That's awesome. That's exactly the use case, what we're working on. And also, you know, coming back to what we were talking about, we want to start with the problem we know the best, right? And then use the mature technology AI to solve. One thing that we're working on is the employee onboarding. Right now we have our employee onboarding product, which people love. And the employees will go through the onboarding experience. Do you know everything they need to do? One thing we have learned is every company that use our employee onboarding always upload their employee handbook. And the employee handbook, it's usually a book sick many pages, right? All they want the employee to do is to sign an employee handbook. It was always in our mind how many employees actually read the handbook and remember what's there. So we have validated with many people, our customers, that they're just putting a handbook out there, hope people can read it, but nobody has time to read it.

(32:06):

So our, there we go. That's our use case. Our, we will train our AI to learn about the handbook. So the employee doesn't need to remember every single page, every single paragraph they want. Instead, whenever they need something, they can ask the AI at the moment they need it for the knowledge they want in the language they most familiar and get an answer. So that is a huge plus for the employee. And also reduce the cost for the cust for our customer and the manager, so the manager can on running the business, treating their customers.

Daniel Blaser (32:43):

Yeah. yeah, that, I, I think that's, you know, like you said, it's a great example of like trying to anchor to an actual use case like we've talked about a little bit. And and Eric, I like that you brought up speed. We, we have data within workstream about the importance of replying once someone you know, applies for a job replying, trying to schedule an interview, we recommend that it's within 24 hours. We have data that, that it makes a submit significant impact in the likelihood that you'll end up hiring that person. But I do think that like, you know, workstream assistant, it, it kind of answers the question of like, well, what, how can you act quickly before they apply? Because that's been like sort of that, that, you know, that time period that is just as important, but it's been harder to figure out, like, you know, how can you be responsive?

(33:35):

So I really appreciate that, that you brought that up. I'm kind of looking at the clock and I'm looking at our, our, our questions, and I feel like we've, we've really kind of touched on everything here. And I, I know everyone has other things to do the rest of the day, so I don't want to take up too much more time. But I did want give maybe each of you just like one more chance to, if you wanna leave like one final thought, take away comment, anything like that no pressure if you don't have something on top of your mind. But just wanna give everyone one more chance. Maybe we'll start with you, Ana.

Anna Khan (34:10):

Yeah, I mean, I, I think Bo is already very much on top of this, but I would say that you know, the most important thing when you launch a product is, you know, listen to your customer, listen to your customer, listen to your customer. And I think also with Ericka's help, like if we can sit and observe at these franchise restaurants, sort of how they're using our product, not how we wish they used our product, but how they actually use it. And of course, I know you guys did all this research before you developed it, but you just learn so much more. And sometimes I find in the companies that I work with after launching something, the iteration stops because it's like, oh, like we finally did it like so much work. But I would say that because AI is such a fast moving sort of goalpost and we have access to these amazing franchises that are rapidly scaling, just like spend as much time with the customer as possible. That would be my sort of final thought.

Daniel Blaser (35:07):

Yeah, that's great. Thank you

Bo Li (35:09):

So much, Anna. That's a very important reminder as a product person, I really appreciate. No problem. And also, I'm very grateful, not only, you know, with you as our advisor thinking about where we're going, but we have people like our, keep us honest because Ericka and people like Ericka knows the industry well, and, and that's literally you know, there to help us to confirm we're solving the right problem. So thank you so much, both of you.

Ericka Garza (35:43):

No, thank you guys. Thank you.

Daniel Blaser (35:47):

Yeah. Any, any other final thing you wanted to mention, Ericka, or No, no worries. If not, just wanna give you a chance.

Ericka Garza (35:52):

No, it's okay. I, I think, you know, I think embracing AI in the franchise space would undoubtedly open new opportunities and unlock so many different ways and, and create such, you know, sustainable success and efficiencies, and most importantly, innovation <laugh> for, for organizations. Because at the end of the day, the, the, the franchiser and the franchisee wanna be profitable. That's what, what, and I do believe with AI it's just, it's a way of just unlocking so many different potential opportunities.

Daniel Blaser (36:29):

Awesome. Well, thank you once again for all three of your time and, and sharing your, your knowledge. This has been great.

Ericka Garza (36:37):

Thank you. No, you so much. Thank you guys. Thank you Anna Bo, and nice to meet you, Daniel. And have a good afternoon everyone.