#729: The mindset shift needed for AI integration success with Rafael Flores, Treasure Data

Summary

Podcast Summary: The Agile Brand with Greg Kihlström®

Episode 729: The Mindset Shift Needed for AI Integration Success with Rafael Flores, Treasure Data
Release Date: September 5, 2025
Host: Greg Kihlström
Guest: Rafael "Rafa" Flores, Chief Product Officer at Treasure Data

---

Episode Overview

This episode explores the foundational mindset shift required for organizations to successfully integrate artificial intelligence (AI) into their marketing and customer experience strategies. Host Greg Kihlström is joined by Rafael Flores, CPO of Treasure Data, to discuss how brands must adapt not just technology—but also culture, processes, and structures—to truly leverage AI for personalized experiences, organizational agility, and sustainable growth. The conversation covers practical industry examples, the future of SaaS in an AI-driven landscape, and tangible advice for leaders navigating the complexities of digital transformation.

---

Key Discussion Points & Insights

1. Defining "Real" AI: Beyond the Hype

Timestamp: 03:35–06:46

• Flores' Definition of AI:
  “My definition and our definition of AI here at Treasure Data is a combination of two elements: gen technology…and predictive and machine learning. That, to me, is credible AI.” – Rafael Flores [03:45]

• AI’s real value comes when generative technologies and predictive/machine learning are combined for actionable, credible solutions—not just flashy features.

2. AI-Driven Personalization in Action

Timestamp: 02:43–06:46

• Retail Example: Rafael shares a Nordstrom store experience where the store layout, informed by customer data and AI, catered to the needs of time-pressed executive shoppers, demonstrating real-time, in-the-moment personalization.

  • “The moment I walked into the Nordstrom store, suits were right there to the right. They identified that consumer pattern…” – Rafael Flores [06:27]

• Broader Application: Personalization is no longer aspirational—gen AI and predictive analytics make it tangible both online and in physical environments.

3. AI Use Cases Beyond Retail

Timestamp: 07:57–10:02

• Financial Services:
  AI can power personalized banking experiences, such as targeted campaigns for “steady savers” with emails like: “Hey, want to beat last month's savings streak?”

• Healthcare:
  Wearables can use AI to detect stress spikes and provide real-time wellness interventions—e.g., sending meditation tips by SMS.

  • “Those are some of the cool use cases … there's so much that they could do.” – Flores [09:43]

4. AI’s Impact on the SaaS Landscape: Speed and Agility

Timestamp: 10:02–14:15

• Market Consolidation & Agnostic Solutions:
  AI enables rapid software development—companies can become more “market agnostic,” building highly customizable solutions with composable data and AI agents.

  • “To you a product may look like regular SaaS…it may very much be all agents underneath the hood.” – Flores [11:26]

• Operational Shifts Required:
  Treasure Data renamed its professional services to “AI and Personalization Services,” focusing on deploying tailored agents and restructuring internally for agile innovation.

• Development Mindset:
  “Do one thing for one customer really fast...you touch most of your customer base, which is better than sending them to a community support channel.” – Flores [14:08]

5. Treasure Data’s Vision for AI: "AI First," Not "AI Adjacent"

Timestamp: 17:00–18:43

• Genuine AI Capability:
  Flores emphasizes seeing “real AI you could touch,” referencing Treasure Data’s AI Agent Foundry, which allows clients to build and harmonize custom AI agents.

  • “We have to be AI first. We can’t be AI adjacent...” – Flores [18:21]

• Data as the "Prompt":
  “AI is as good as what you feed it...data is the prompt.” – Flores [17:43]

6. The Diamond Record: Next-Level Identity Unification

Timestamp: 18:43–21:04

• Evolving from Golden Record:
  The “Diamond Record” surpasses traditional customer identity solutions by merging data securely and in real time, embedding with multiple ID graphs, and supporting immediate omnichannel actions.

  • Real-world scenario: Detect in-the-moment mobile searches as a shopper walks into a physical store, enabling timely personalized offers.

7. Expert Advice for Marketing & CX Executives

Timestamp: 21:04–24:10

• Overcoming Overwhelm:
  Don’t try to adopt AI everywhere. Form an AI Use Case Review Committee to align AI applications directly with business impact.

• Focus on "Solve for One":
  “Solve for one, don’t solve for many. Focus on fixing your data and feeding it the right data for that one use case…Don’t boil the ocean.” – Flores [22:37]

8. Culture and Mindset: Taming the Fear of AI

Timestamp: 24:10–26:09

• Change Management:
  Technology is only part of the equation; people and processes are critical. Fear of job displacement can be overcome by involving teams in fun, creative AI experiments.

  • “Beat the fear of AI by doing fun and innovative things with them.” – Flores [25:50]

• Continuous Learning:
  “You’ll never know everything…learn day by day in the doing.” – Flores [24:23]

9. Staying Agile: Two Roadmaps and Personal Wellbeing

Timestamp: 26:20–27:27

• Strategy:
  Maintain two roadmaps: one for non-negotiable priorities, another for nimble adaptation to market changes.

• Personal Advice:
  “Focus on your health…If you do that, plus know your non-negotiables, plus keep a little bit of a nimble path...you can support the business and you can better lead.” – Flores [27:08]

---

Memorable Quotes

• On the fundamental shift required for AI:
  “Agility requires not only embracing new technologies like AI, but also a fundamental shift in mindset, processes and even organizational structure.” – Greg Kihlström [00:39]

• On real-world personalization:
  “When those two [generative and predictive AI] meet, brands can decide in that storefront what the next best action may be.” – Flores [05:54]

• On change resistance and learning:
  “Don’t try to stay ahead of AI. You never will…focus on what you can control, which is learn day by day in the doing.” – Flores [24:19]

• On driving organizational buy-in for AI:
  “Have people use the AI in fun and creative ways...do things like that, right? That way people don’t fear AI.” – Flores [25:54]

---

Key Timestamps

• 03:35 – Flores defines AI as the mix of generative technologies and predictive/machine learning.
• 05:48 – Nordstrom example: AI-informed physical retail layout.
• 08:48 – Financial services and healthcare AI use cases.
• 10:48 – AI driving SaaS market consolidation; “agent” powered software.
• 13:03 – Restructuring teams for AI innovation.
• 17:00 – Treasure Data’s vision: “AI First.”
• 18:55 – The "Diamond Record" vs. "Golden Record" in identity management.
• 21:41 – Advice for overwhelmed marketing leaders.
• 24:10 – Overcoming fear and resistance to AI.
• 26:20 – Staying agile as a leader and practitioner.

---

Conclusion

This episode delivers an in-depth look at what it truly means to integrate AI: not just adopting new tools, but fostering an experimental, pragmatic mindset throughout the organization. Rafael Flores’ insights—grounded in practical experience—stress the importance of credible, actionable AI; starting small and focusing on impact; and nurturing a workplace culture that learns and adapts together. The path to AI-driven value is as much about people and process as it is about technology.

---

For more:

• Follow Rafael Flores and Treasure Data via the links in the show notes.
• Explore more episodes at theagilebrand.com
• Contact host Greg Kihlström for consulting or speaking information at gregkihlstrom.com

---

Stay curious, stay agile.

Transcript

[A]

The Agile Brand.

[B]

Welcome to Season seven of the Agile Brand where we discuss the trends and topics marketing leaders need to know. Stay curious, stay agile and join the top enterprise brands and martech platforms as we explore marketing technology, AI, E commerce, and whatever's next for the omnichannel customer experience. Together we'll discover what it takes to create an agile brand built for today and tomorrow and built for customers, employees and continued business growth. I'm your host Greg Kilstrom, advising Fortune 1000 brands on martech, AI and marketing operations. The Agile Brand podcast is brought to you by Tech Systems, an industry leader in full stack technology services, talent services and real world application. For more information, go to teksystems.com to make sure you always get the latest episodes, please hit subscribe on the app you listen to podcasts on and leave us a rating so others can find us as well. Now onto the show. Is the hype around AI and marketing justified, or are we setting ourselves up for yet another tech bubble of disappointment? Agility requires not only embracing new technologies like AI, but also a fundamental shift in mindset, processes and even organizational structure. It demands a willingness to experiment, learn and adapt quickly to the ever changing marketing landscape. Today we're going to talk about how AI is poised to revolutionize marketing, from personalization and customer engagement to the very structure of the SaaS market itself. To help me discuss this topic, I'd like to welcome Rafael Rafa Flores, Chief Product Officer at Treasure Data. Rafa, welcome to the show.

[A]

Thank you for having me. Excited to be on here.

[B]

Yeah. Looking forward to talking about this with you. Before we dive in, got a got a few things to talk about here, but before we do, why don't you give a little background on yourself and your role at Treasure Data.

[A]

Yeah, no, definitely. I always like to introduce myself as a people first leader. So I am a father of three, Mia, Noah and Liam. I am a husband of a nurse and I grew up my whole life and spent my whole career in California. So that's a little bit about myself as a person, as a leader. I've been doing product management for over 15 years. I'm a builder. I love to grow companies from the ground up, take them public and then I I stay for the post public commotion and then I go build on the next one. Right. And so I was with Treasure Data for seven years. I left for about three and then I just came back as a boomerang. Very excited to be here, especially at the time where AI is a lot of noise in the market. And I think we're poised to hopefully do some great things with it. So thank you for having me, by the way.

[B]

Yeah, absolutely. So, yeah, let's, let's dive in here. We're going to talk about a few things and really all centered around AI, as we both mentioned sort of in our intros. I want to start with personalization. And this is an area where I'm personally excited about, personally excited about personalization. But just because again, we've been talking about personalization for years and it feels like decades we've been talking about it and yet I feel like generative AI and some of these other tools that are a little more recent are actually enabling this. And you've spoken about how AI can save physical retail. Can you elaborate on that and perhaps share an anecdote of how things like analyzing shopper behavior can translate into tangible real time improvements to the customer experience?

[A]

Yeah, no, it's a great topic. Personalization. I am with you. I've been hearing around how can you master the art of personalization for the last decade or so. And I think before I speak to retail specifically, I think it's important to define AI, right? And so my definition and our definition of AI here at Treasure Data is it's a combination of two elements, right? It's gen technology, which it's obviously hot in the market today, as well as predictive and machine learning, right? And so that to me is credible AI, right. In terms of how it can save physical retail and many other industries, in my opinion. Right. I think it all starts with in the moment experiences, right? I recently wrote an article where I spoke about this concept. But when you think of physical retail, everyone focuses around foot traffic, right? Getting somebody to the storefront. But you also have to think about that foot traffic in the terms of them navigating the store and then that foot traffic of them leaving your store. Right? And so from a, from a physical retail standpoint, you want to make sure that you think about end to end, what foot traffic means to you. And staying in that moment and the way I can allow you to do that is two things. The Gen AI piece, right, it's fed a lot of data around your shopper or consumer behavior. It allows you now to go and make sense of data that perhaps before required many years and many, many headcount. On the IT and data analytics side, the predictive and machine learning angle of AI helps you define brand affinity. It can give you an accelerated score with AI decisioning to ensure that you understand who is actually the best Shopper for you across those moments. And so when those two meet, I do believe that it can empower brands to decide in that storefront what the next best action may be. And I think one of the. The best examples I could give you, I travel fortunately and unfortunately, quite a bit for my job. And we have one of our second headquarters in Tokyo in Japan. And I recently had to buy a suit. I ran out of suits. I was traveling so much, I was on the road, I ran out of suits. So I had to go because dry clean couldn't get it to me on time. And I had to walk into a Nordstrom. And what I loved about Nordstrom is that they have figured out that, hey, if you really look at consumer behavior, when somebody comes in through an entrance, especially those looking for suits, they're looking for potentially quick hits, because a lot of the demographic that's buying suits right now are executives like me who are on the go. Right. They need to go and find a suit. Yes, you will still have your typical shoppers of weddings, et cetera, but that is who's purchasing right now. And so the moment I walked into the Nordstrom store, suits were right there to the right. They identified that consumer pattern. Right. And they put it at the storefront. And so that's an example of, hey, they have actually kind of mastered the art of personalizing that. If I come in knowing the type of shopper I am and what's hot in the market today, with some AI in the mix, they can navigate me in that moment experience of when foot traffic is at your storefront, which is very critical.

[B]

Yeah, yeah. I mean, and I love that you reinforced that idea that, I mean, I think most people listening to this show probably know that, you know, there's more than just generative AI out there. But I think, you know, generative AI has been getting kind of all the oxygen in the room, so to speak. And, you know, AI, you know, has been around for decades. And I think some of the, like, most meaningful use cases are still, like, old school, like RPA and stuff like that of, like, just getting some immediate results. I think what you're talking about, though, is really powerful in combining different types of AI together. And also an example how a store is laid out. It's not the typical use case you're thinking of, okay, well, how do I automate something on a website or a mobile app or something? But that combo of how do we take predictive data or analytics in the real world and actually map a physical location? I wonder, you know, Are there, are there other examples even, you know, beyond retail, like other maybe less obvious applications of, of this that you're seeing across different industries as well?

[A]

Yeah, no, I mean there's, there's so many. Right. But I could tell you too, that are top of mind that I think people often overlook that, that they can have a tremendous impact in the sectors. Number one is financial services. Yeah, right. And the way I think it is, if you can actually feed AI the right data, right. And you have all these financial institutions leveraging it properly, Right. With the right governance in place, obviously you name it, right. You can launch campaigns based on this type of behavior. Right. So a great example is if I think of financial services, I was having a conversation the other day with a major bank and they said, hey, look, we want to target people based on where they are in their life, right? And I said, okay, let's think about a use cases. And one of the ones that popped to mind right away for me was you have steady savers, right? You have folks who like to save, right? Now I know we tell everyone, hey, you should be saving, but not everyone saves.

[B]

Right, right, right.

[A]

And so that's your segment, it's your audience. And so what I said to them is what if you can identify who your steady savers are so you can then go power a customer experience campaign on something very simple as an email goes out and says, hey, want to beat last month's savings streak?

[B]

Yeah.

[A]

Here's where you saved, here's where you're forecasted to save this month. Now for the bank, it's a win. We all know the more liquidity they have, the more they can loan out, the more stability, right. For you as a consumer, it's meeting you where you need the bank to advise you. And so that's a great example of one. The other one that also comes to mind always for me is healthcare, right. And not in the sense of AI is going to give you your own, your own plan of how to treat things, right? Definitely not. But if we for example, gave you a use case where, hey, your watch data can tell you when stress spikes, right? And you know that at this time of day it spikes the most. Well, I would like to know that because then I can send you meditation tips and tricks via SMS push because we know that you're probably spiking and you're likely on your phone. And so those are some of the cool use cases that I kind of think of as I hear some of these examples that I think those industries, if they Use it to their advantage. There's so much that they could do.

[B]

Yeah, yeah, I love that. I love that. Another thing that you've talked about and written about is just the AI's impact on the SaaS landscape. So as anyone that goes to any conference or reads any publication, every platform is like saying AI this, AI that. And so everybody's got their AI features or whatever. But I think it can go much deeper than that when applied. Well, you've predicted that AI will drive market consolidation and a rise in market agnostic software. Can you talk a little bit about that? What specific advantages does a market agnostic solution provide over specialized platforms?

[A]

Yeah, good question. And I'm going to give you a very atypical answer. I think when I speak of market consolidation and I think of me as just, I mean, you know, 16 years ago as a product manager, just building products. Right. I think the reason AI is allowing folks like myself to build fast is it has really reshaped how you can build software. Right. It's that simple. I mean, to you a product may look like regular SaaS. Right. It's on the cloud, it has a UI, but it may very much be all agents underneath the hood. Right, right, right. We have an agent to give you an example that now actually will give you the react code for the front end. Right. And so market consolidation is there for two reasons. Right. It's there because, yes, people want to mitigate costs in the current macroeconomics, which we know we've been dealing with, but it's also now possible, because of my earlier comment. Right. That we can just build so much faster. And I think the advantages of, to your second question there, what are advantages of this market agnostic solutions or more specialized platforms? I think specialty comes with ability to move fast. And if you're willing to innovate with these companies, they're going to go and try to specialize and tailor even agents to your need. And that makes it market agnostic. And so I think we're in a new era where even composable. Right. The idea of composability, it's something that Treasure Data has dealt with for years. Best breed versus compostable. Composable to me is being able to use your data anywhere and using the best pieces of any product. You could do that with us, you could do it with many. Right. And so the question is, who's going to win that race? Right?

[B]

Yeah. So how do you, as a SaaS company, how do you, how do you enable your teams and the platform itself to Move at the speed that it. Because being able to move quickly is one thing, but actually doing it and doing it well, that's the magic, right? How do you do that and kind of set a platform and a team up? To be able to move quickly, I.

[A]

Think you have to rethink across the organization first, how you gear up structurally and functionally for it. I'll give you a tangible example. We reshaped our traditional professional services team here and we renamed it to be AI and personalization services. Their focus is to deploy agents that are tailored to you. But we're gearing up for a world where our product is going to be powered by agents. So we need professional services that really knows how to even build those agents themselves. Right. And so I think to move fast, you have to first look at within and set up your organization that way. Now, how can I move fast with quality in mind? Right. With my teams, all my development teams. I think that I do bad product management principle. And I'll tell you why. Typically they tell you, hey, do a feature that impacts many. I think it's different now. I think because you can move so fast and leverage AI for it. You can do one thing for one customer really fast and there's 365 days in the year. If you shrink that in half and you do just that one thing for that one customer, you touch most of your customer base, which is better than sending them to a community support channel, right?

[B]

Right, totally.

[A]

So those are all steps that you could take that I personally take here and that we've taken as an organization to just get ready for this new world.

[B]

When you're hiring, the process can often be so time consuming, including waiting for the right candidates to apply, sorting through resumes, trying to get in touch with potential candidates, and even finding the right candidates, only to come to realize they're not actively looking for jobs. Well, the future of hiring looks much brighter because ZipRecruiter's latest tools and features help speed up finding the right people for your roles so you can save valuable time. And now you can try ZipRecruiter for free at ZipRecruiter.com work with ZipRecruiter's new advances, you can easily find and connect with qualified candidates in minutes. Over 320,000 new resumes are added to ZipRecruiter monthly, which means you can reach more potential hires and fill roles Sooner. No wonder ZipRecruiter is the number one rated hiring site based on G2. At ZipRecruiter.com work use ZipRecruiter and save time hiring 4 out of 5 employers who post on ZipRecruiter. Get a quality candidate within the first day. And if you go to ZipRecruiter.com work right now, you can try it for free. Again, that's ziprecruiter.com work ziprecruiter the smartest way to hire Want to learn more and join the discussion About Marketing and AI? Attend a premier conference dedicated to marketing and AI. That's Meikon, the Marketing Artificial Intelligence Conference from October 14 through 16 in Cleveland, Ohio. Meakon brings together the brightest minds and leading voices in AI. Don't miss this opportunity to connect with a dynamic community of experts, visionaries and enthusiasts. The Agile brand is proud to be the lead media sponsor of this important event. Register today@marketingai institute.com that's marketing AI institute.com and use the code AGILE150 for $150 off your registration fee. I can't wait to see you there. And so, you know, I want to talk a little bit more. I know you've touched on it a bit throughout, but I want to talk about the really Treasure Data's vision for AI and how that's going to evolve. And you know, I always love, you know, I think it definitely speaks to a company and a platform when someone comes back like yourself. So you've, you know, you were there, you came back and you know, sort of with this renewed vision. So, you know, could you talk a little bit about, you know, how do you see AI being a key part of Treasure Data and kind of your place in the market?

[A]

Yeah, very good question. I mean, one of the reasons I came back, I'll tell you why I came back, obviously I trust the team here and for us with the founders and the board, right? But I was very excited to come back because Treasured Data actually has real AI that you could touch. Right. And what I mean by that is I said to them, show me the product, right? Like what has happened? What has changed in the product from when I left it? And they walk me through something new, which we have. It's called AI Agent Foundry, right? You can actually go build and harmonize your own agents. So it's not just AI on the website. I actually trust the data. Before I joined, they didn't even have it on the website, right. Which blew my mind. I said, well, wait a second, let's get this on the website. So they had it, right? So we have credible AI, right. And I think when I Think about what credible AI means. You can actually power the right use cases. Right. And I think Treasure Data historically has been, I mean, the leader in many ways when it comes to managing very high scale loads of data. And so AI is as good as what you feed it. Right. If you go on chatgpt, it's not very good unless you give it a good prompt. And so data is the prompt. And so when you tie those two concepts together of we kind of own this first party data here, that's your powerful prompt. Plus we have this foundry here you can build any agent on top of. Right. That's tailored to your business. And so to me, that has to be our focus. We have to be AI first. We can't be AI adjacent. I think there's a lot of AI adjacent companies. There's a lot of website AI companies, right?

[B]

Totally.

[A]

There's not many that actually have AI. And we have it. Let's use it, let's make it more powerful, let's speak of it. Right. And let's not be scared. You have to take risk. And I'll tell you this, I'm a risk taker. So we're pushing through.

[B]

Love it. Love it. One other concept that as I was prepping for this I came across was the Diamond Record. So do you mind just explaining what that is and how that kind of fits in?

[A]

Yeah. This one is all around identity unification. Right. And in today's day and age, we have been in this Golden Record era where you can go set up how you merge those records. Right. Where an email here matches a cookie here, it matches a mobile device one here, and therefore that is Raphael at Treasure Data. But a lot of marketing dollars are wasted in that approach because yes, it's deterministic and probabilistic. However, if that email and that device match, but the device is actually my wife looking at online shopping now, all this company is targeting me in ways that it's a waste of their money and it lacks the knowledge it needs in real time. And so the concept of the Diamond Record, it's different from the Golden Record in three ways. It allows you to really set up the right merger, how you merge those records in place to safeguard that it's actually the right profile. Number two, it's highly embeddable. We want to embed with a lot of different ID graphs, the trade desk, the Liveramps, you name it, to make sure that we can power everything across and they can also power things from within. The more we share id, the more we go across. Highly embeddability. Is important. And then in real time, right? Most companies, I hate to say all, but if not all, right, have some pipeline delays and typically it's 24 hours. So you have a lot of credible information and it's good enough. But what if it can give you every behavior in real time that going back to the physical retail store example, if you have somebody walk in and they just got out of their car, in between the car and the entrance to that store, they did a quick search of a competitor, right? Like, are those shoes cheaper somewhere else? Right here, Nordstrom, Is it cheaper at Macy's? And that person knows the moment that person walks into the store, when they put their phone number, that they just did that search, you can offer them a discount, right? But you can't power that unless you have a diamond record. And so it's hard to do. That's why we historically also had not done it. But if we do it and we do it well, we put ourselves in a very different sphere.

[B]

Yeah, yeah, I love it. So now, you know, look, looking from the, you know, there's a lot of marketing leaders and execs listening to this, a lot of people at enterprise orgs that are, you know, any company, I would say, probably falls into this. But you know, those, those large orgs, they're being asked to do more with less, they're being asked to consolidate, they're being asked to do all of these things. You know, what, what advice would you give to those marketing executives that are, you know, they may be excited about AI, but also, you know, kind of overwhelmed by the rapid pace of change and you know, what, what should they be focused on?

[A]

Yeah, good question. And I'll tell you what I often hear, right? You have the CMOs, the CXOs, even CDO is where the CEO is telling them we need AI first vendors, right. Because the board is telling the CEO you need to be AI to drive valuation. Right? So we have to think about this unit of economics that happens here, which even happens to me in my role. But a lot of them don't even know what AI is, right. Or how to actually use AI to drive profits and revenue. Right. Which is ultimately what you're trying to do. And this is why so many companies are actually failing, because they're trying to deploy AI and it's not repeatable, it's not credible. It kind of reminds me of the Internet of things, which I was at the forefront of that when I let teams that ARM holdings for it. Right. And so my advice will be, honestly Two things. Number one, immediately set up an AI use case review committee. There's a lot of focus around AI review committees when it comes to governance. And is the AI safe? Can I trust it? And that's extremely important. That's a piece of the iceberg. Why are companies not also focusing on how they can actually use AI in one or two ways that will drive revenue and that involves a lot of functions coming together. Do that now. So when you go evaluate vendors, there's enough meat to the bone of understanding what AI will do for your business. Yeah. So that will be the first step, I will say the second step is solve for one, don't solve for many. Focus on fixing your data and feeding it the right data for that one use case. If you try what I've seen and we've seen also at Treasure Data with our customer base, when they come with all this data and they just want to fix it all and then deploy AI, it's too late. Somebody has already beaten you to it. And so you have to make sure you get your data right. But get it right for the credible use cases that are top of mind for you and that are going to drive business impact. That will be my advice. Don't boil the ocean. Doesn't work. There's a reason that phrase exists, right? It's the number one advice you get all the time.

[B]

Yeah, yeah. Love it. And you know, so thinking beyond the technology component or even, even the data component, is it skills development, organizational structure, like what else should be part. Because I mean, I, I know in my experience, you know, the. Everybody thinks that the tech is going to solve all their problems, but it's the people in the process that make or break, to be honest. So, you know, what, what, what of the people and process part of that equation goes along with, with what you're. What you're just saying?

[A]

Yeah, no, it's very good question, by the way. I, I think it's a few things, right? Don't try to stay ahead of AI. You never will.

[B]

Yeah.

[A]

Even me. Right. Like in my job, I can't stay ahead of it. Every day there's something new and by the time I go try it, my team, somebody in my team has heard it, a customer has heard of it. Don't even try to catch up. It's okay if you don't know everything about AI, you won't know everything. There's a reason it's artificial. Right? Right. It takes time and you'll never catch up. And so focus on what you can control, which is learn day by day in the doing. The second thing is. And the biggest challenge that companies will have as they try to embrace AI is change is difficult and there's a lot of fear around AI in general. Is it going to take my job? Is it not? Does it actually make me a superhuman? Does it not? Just so, you know, Treasure Data, my vision is we're making people superhumans, we're not taking their jobs. I'm not going down that path because I don't believe in it. And so. But part of that is you have to beat the fear factor. The best way to do it is to actually have people use the AI in fun and creative ways. And I'll give you a very quick example. Recently I was up late, up until midnight, and I thought to myself, we have a new suite called Creative AI Suite, right? You can do email, text, agent and generate copy or image, et cetera. And I used it, I play with it, right? I can't be a good cpo, not use the product. And so I went on there and I generated my own image and I had fun. And so I recorded myself for three minutes, I posted on our company Slack channel and I said, hey, fun challenge. Go generate your image now with this new suite and I'll send you an Amazon gift card for 100 bucks. Right? It generated so much momentum. I mean, we had over 100 people participate. It went Treasure Data viral. Right?

[B]

That's awesome.

[A]

And so do things like that, right? That way people don't fear AI. That's extremely the number one thing. I think if people can take away from everything. I just rambled on. Beat the fear of AI by doing fun and innovative things with them.

[B]

Yeah, yeah, that's great. Well, Rafa, thanks so much for joining today. One last question before we wrap up here. What do you do to stay agile in your role and how do you find a way to do it consistently?

[A]

Good question. It's hard. How do you stay agile? Right. I think you have to have two roadmaps. I think you have to have a non negotiable roadmap of things that you're not willing to lose, right? And that's what you share with customers and the board. And I'm a big believer that a roadmap has your signature on there, must deliver. It may shift a little bit, but those non negotiables have to persist, right? But you have to save some percentage of your investment to actually being nimble, right? And being flexible. And so that's second roadmap. Sprint over Sprint. Look at meeting customers in the market where it is and not having them meet you where you are as a business, right? And so you have to do that and quite frankly as a leader to stay on your toes, focus on your health. I think we talk a lot and I do all this podcast and the one thing I tell people always is you can stay agile and mood fast if you're healthy, right? And so focus on your health. That includes your mental health. Take breaks, go on walks, do whatever you need to. If you do that, plus know your non negotiables plus keep a little bit of a nimble path here on the second roadmap, you can support the business and you can better lead.

[B]

Yeah, yeah, I love that. Well again I'd like to thank Rafael Flores, Chief Product Officer at Treasure Data for joining the show. You can learn more about Raphael and Treasure Data by following the links in the show notes. Thanks again for listening to the Agile Brand brought to you by Tech Systems. If you enjoyed the show, please take a minute to subscribe and leave us a rating so that others can find the show as well. You can access more episodes of the show@theagile brand.com that's theagile brand.com and contact me. If you're interested in consulting or advisory services or are looking for a speaker for your next event, go to www.gregkilstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay Agile.

[A]

Brand.

[B]

Before we continue, I wanted to share a key strategic resource that a majority of the Fortune 500 are already aware of. Finding the best technology, business and talent solutions is not easy. With business demands and competitive pressures mounting, you need to be able to design, deploy and optimize your technology to provide leading customer experiences while driving business growth. Those of you that have been listening to this show for a while know that this podcast is brought to you by Tech Systems, a global provider of technology, business and talent solutions for more than 80% of the Fortune 500, TecSystems accelerates business transformation for their customers. Whether you're looking to maximize your technology roi, drive business growth, or elevate customer experiences, Tech Systems enables enterprises to capitalize on change. Learn more at techsystems. Com. That's teksystems. Com. Now let's get back to the show.