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Greg Kilstrom
We all know data is valuable. We use it to tell a story to make informed decisions for our businesses. But turning data into actionable insights can be a challenge. It's time to unlock the true potential of your business data with Domo's AI and Data Products platform. Domo lets you channel AI and data into innovative uses that deliver a measurable impact. Ask your data Anything at any time. Anyone on your team can use Domo to easily prepare, analyze, visualize, automate and distribute data, all amplified by AI. Domo goes beyond productivity. It's designed to transform your processes, helping you make smarter and faster decisions and drive real growth. All powered by Domo's trust, flexibility and years of expertise in data and AI innovation. Data is hard. Domo is easy. Make smarter decisions and propel your business forward with Domo. Learn more today@AI that's AI.domo.com the Agile Brand 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. And now on to the show. We are recording live at Qualtrics X4 in Salt Lake City and seeing and hearing all about how to create amazing customer and employee experiences as AI and AI agents increasingly play a role. With a potential 1.3 trillion in revenue gains and cost savings on the table, organizations across industries stand to gain a lot through strategic investments in AI. Today we're going to talk about enabling and accelerating customer experience success by augmenting your teams and processes with artificial intelligence based tools. To help me discuss this topic, I'd like to welcome back to the show Isabelle Zidatny, Head of Thought Leadership for XM Institute at Qualtrics. Isabelle, welcome back to the show.
Isabelle Zidatny
It's fantastic to be here. Thank you for having me again.
Greg Kilstrom
Yeah, absolutely. Yeah. Good to see you in person here.
Isabelle Zidatny
This is wonderful.
Greg Kilstrom
Do so many of these remotely. It's always nice to be in person.
Isabelle Zidatny
It's my favorite part of X4.
Greg Kilstrom
Yeah, absolutely. So for those that didn't catch you when you were on the show last fall, why don't you give a little background on yourself and your role at Qualtrics?
Isabelle Zidatny
Yes. So I lead thought leadership for Qualtrics XM Institute, which is almost like a little think tank inside Qualtrics. And we're really dedicated to building the category of experience management. So less focused on the product and more how do we equip CX&EX and XM professionals with the tools and the insights and the data and the best practices and the frameworks that they need to feel confident and successful in their role? So I produce our content, I advise companies on the design execution of their program, speak on topics, design training. And I got started back in 2013 at Temkin Group and then joined Qualtrics when we were acquired. Acquired in 2019.
Greg Kilstrom
Great. Great. Wow. So, yeah, you're doing a lot here, so let's. And yeah, I want to talk primarily about some research that was recently published that I know Qualtrics and McKinsey worked on. So want to start there. And we certainly talk about AI a lot on this show. I think literally every conversation somehow goes into AI, if not starting that way. But your research, as I mentioned at the top of the show, shows that businesses are standing to gain anywhere between $860 billion to $1.3 trillion by making strategic AI investments. So let's start at the beginning again. That's predicated on the making the right investments. So where are businesses maybe going wrong as they plan and strategize?
Isabelle Zidatny
Yeah. So I would say I'm seeing two big mistakes that organizations are making in their approach to AI. First, I would say is that they are implementing AI for the sake of AI. There's the allure of the shiny new feature, or executives are putting pressure. And so they're just like, we need to stand up these technologies rather than starting with what is the outcome that we are trying to achieve. And then how could we possibly bring AI into the mix to help us get there more quickly and economically? And then the second big one I'm seeing is more at an organizational level as opposed to CX specific, specifically that they're struggling to get out of pilot purgatory and invest in the types of systemic changes that are really necessary for unlocking the full value of AI. So they start small. They do very Expensive experiments and then they don't really scale them more broadly across the organization, which is not creating the value that AI can create.
Greg Kilstrom
Yeah. And I mean, that said, I mean pilots is a good way to start, but what do you think is kind of what's the leap they need to make from pilots?
Isabelle Zidatny
Yeah, I think you need to move from doing AI in silos to kind of system wide organization and management. I actually just saw an Axios article yesterday that I think 71% of executives are concerned about how much AI development is happening within silos at organizations. And so I think a lot of teams are looking at here are the solutions. We're doing that work for us and there's not a lot of up leveling yet. And that requires some fundamental changes to your data and technical infrastructure too. And change management. Right. Scaling can be quite difficult.
Greg Kilstrom
Yeah, yeah. Are there particular, I don't know if it's industries or use cases where benefits of AI are particularly clear or maybe potential? I mean obviously that's a big number of potential, but where are you seeing some of the biggest potential?
Isabelle Zidatny
Yeah. So just to give a little bit of background about this research report, so we partnered with McKinsey against. The goal here was really to put some hard numbers around the opportunity that AI can present to organizations who use AI to improve customers experiences. Our source of insights, I would say for this research were one. Qualtrics conducted an executive study of 1500 global executives in Q4 of last year, asking them about their expectations and efforts around both customer experience and AI, which yielded some really interesting insights. And then McKinsey performed a detailed value analysis sizing the opportunity, the potential impact AI could have across 19 different industries. So that's where that $860 billion number comes from. And then we also interviewed a number of innovative clients to understand how they were using AI to better understand and serve their customers. So for McKinsey's value analysis of that. So AI enabled customer experience is expected to drive an estimated $860 billion and possibly all the way up to $1.3 trillion in annual value. And it's expected to do this in three ways. So the biggest opportunity that they found was in productivity gains. So $420 billion is expected to come from productivity gains. Using AI to augment and automate work. $260 billion expected from revenue growth. So using AI to transform how you acquire and grow customer relationships, intelligent targeting and personalized messaging, and then another 180 billion from process improvements. So using it to optimize your operations lower cost to serve customers. So they also broke that number down across those 19 industries. And the biggest opportunities were B2B. I think it was 420 billion opportunity. The biggest was business and professional services, which was $150 billion opportunity on average. And that was through things like personalized marketing and I believe optimized operations. Also on the B2B side, commercial insurance was 70 billion opportunity and SMB banking was 60 billion opportunity. And both of those are from things like automated processes and risk assessments and things. On the B2C side, both retail and retail banking were $100 billion. And then there's a whole host of other B2C ones that were pretty close, like hospitality, airlines, QSR. So yeah, there's, it's definitely the nature and scale of the opportunity varies a lot, but it crosses everything.
Greg Kilstrom
Yeah, yeah, there's something for everybody.
Isabelle Zidatny
Yeah, exactly.
Greg Kilstrom
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Isabelle Zidatny
It's such a good question and I'll say one of the things I heard the people I interviewed over and over is the technology is not actually the hard part. It's getting people to use the technology effectively and feel comfortable and confident using it. That that change management piece is actually I think long term going to be much trickier. So yeah. So I would say again, start with what is your, your organization kind of AI vision and strategy and value. So what are the outcomes you're trying to drive? And that will be different by different businesses across different industries. Right. You might want to increase customer spend or average contract value. So starting with a central organization, wide vision, having governance structures in place like a centralized governance council, some way to monitor all the different AI use cases and make sure that they're getting implemented effectively. You need common risk and ethics guidelines and that should help with the culture change. Right. Starting with this is the vision that we're all trying to move towards. And this is why we are asking you to change your behaviors and adopt these new technologies and then making sure that your workforce is ready for AI, that they have the skills they need. You do a capabilities gap. Where can you upskill people? Where do you need to bring other people in? One of my favorite stories from this report was when I talked to ServiceNow to get change management, get people comfortable using AI. They have a central, they call it an AI control tower. So a central dashboard that has all of their different AI use cases across the company. It was like 350 when I talked to them. Everyone can see it, here's who owns it, here's what value it's driving. And then they selected certain roles across the company. They looked at those roles and they identified ideal workflows, they talked to people, what are your tasks like? And then matched here's the parts of your job that you don't love, that you don't find engaging, that could be automated based on the AI solutions we have or augmented through synthesis or prediction. And so taking that type of role based approach of like this is specifically how this is going to help you do your job better was really influential for getting that change management and buy in across the company. It's not here to replace you, it's here to help you.
Greg Kilstrom
Right, Right. Yeah. And I mean, that's, I think that's such an important point is the visibility on it. It's not so much having these siloed tools that do individual tasks. And that's a lot what I heard this morning at the keynotes here, having almost that operating system that allows you and not only the executives, but the frontline employees and everybody in between. Right.
Isabelle Zidatny
Yeah. I mean, you really need all the data to be living. You need to be moving towards some type of enterprise data warehouse or something where you can be applying these models on top of using them. AI compounds the garbage in, garbage out issue. So making sure it's all clean and good for powering your LLMs, it's a big undertaking.
Greg Kilstrom
Yeah. So what about the customers? And we've talked a lot about the enterprise level and leadership and even employees, but what do customers want out of this? How are they responding to greater AI integration? And you know, what have you seen as some of the best customer responses to AI?
Isabelle Zidatny
Yeah, so we saw as part of our 2025 consumer trends that consumer comfort with AI dropped 11 points year over year, which I think shows we're kind of in this trough of disillusionment, part of the hype cycle right now. So I think one of the things from that was like, again, rather than organizations were telling customers like we're doing AI, your. Your experiences are now AI customers don't care about that. What they care about is being able to achieve what they want to achieve, you know, quickly, effectively, enjoyably. So I would say some of the best use cases I've seen are using AI like virtual assistants to help customers complete complicated tasks. A big one. One of the companies I talked to for this report used it for their claims process, which historically is like a very long, complicated process. You don't know what on my receipt is eligible, what's ineligible. And then it would take on the back end, someone multiple days. Right. Sometimes to review is the information inserted properly. So the virtual assistant help walk people through. They could take a picture of their receipt, even like a CVS receipt that's really long and filled with things and it would automatically fill out that process. And it moved from being, I think, two days to like under two minutes for 60% of the interactions. So that's good for customers. Right. They have something they have to do that's not fun. How can we use AI to help them achieve their goals better?
Greg Kilstrom
Yeah, definitely. And I Mean that, that's where I mean, I think kind of what you were referring to earlier is that lots of companies were throwing AI at the wall to see like the chatbot thing that isn't really smart and it gets you into the like doom loop just like, you know, calls sometimes still do. But I think agentic AI, kind of what you're referring to here really does kind of bridge that, that gap. And so I mean, do you, are you seeing that consumers are, I mean obviously there's a, there's a little bit of a trust gap it sounds like right now I think in the last year, according to like Forrester and some others, there was a dip in CX in general.
Isabelle Zidatny
Yeah. Yes.
Greg Kilstrom
So like maybe that's related to what you're saying too. But do you think we're going to kind of cross that threshold?
Isabelle Zidatny
I think usually if we look at new technology adoption, you have, something comes out, people get very overexcited, they start applying it to things they shouldn't. So chatbots are a great example where again, garbage in, garbage out. They started training chatbots on bad internal data, old, old knowledge based articles. The technology wasn't there, so people were having really bad experiences. So then they're like, well this isn't living up to the hype. What then often happens is that companies get much more buttoned down and understand these are the best use cases for these specific tools and start improving that. And consumer perception's a lagging indicator behind that. But eventually kind of comes back and they're like, oh, but I think it's all about like what's in it for them? How is it helping them? Not they probably the less they know that they're engaging with AI and that's like even in their thought process, probably the more enjoyable the experience is.
Greg Kilstrom
Yeah. And I mean, I think eventually, I mean I've heard other people have said the same like I think in five years we may not even use the term AI, it'll just be doing stuff.
Isabelle Zidatny
But well, because it's also so kind of ethereal now where people. Yeah. Don't distinguish between like analytical and generative.
Greg Kilstrom
Right. But, but the promise of this and you know, I think what's, what's really powerful is you know, you've got the, you and someone characterized it this way, you know, you've been listening, you have a lot of data already. Generative AI helps kind of make sense of all of that data now. Agentic actually can tie the pieces together. And you know, not every organization is there just yet, but that promise of one to one. I've been talking about one to one personalization for years, but never felt like it was possible until a year or two ago. So how close are we to that for brands?
Isabelle Zidatny
Yeah, I mean I think Ethan Mollick, who's a Wharton professor and AI researcher, describes the jagged frontier of AI gets really good at some things and is very far out in front and then it's really strangely bad at other things. So I think right, we're still some things are moving forward at a much faster rate. I think that we're closer than people think we are. It's like it's a cliche now, but that old Hemingway quote about going bankrupt, it happens slowly than all at once. I think a lot of the foundations have been built that organizations are ready to start deploying these for primetime. Like I think the foundation stronger than it was before. So I do think it's coming soon.
Greg Kilstrom
So what would your recommendation be then for those organizations that are, they know this, they agree with the sentiment here, but maybe not sure where to start in getting things moving. What should they be thinking about?
Isabelle Zidatny
Yeah, so I would say again, first of all, starting with the outcomes that you're trying to achieve. So if you're a CX professional, what are the metrics you're trying to move, what are the experiences you want to deliver, what's an initiative on your roadmap that you are trying to implement and then how can you bring AI in to help you execute on that? So again, rather than getting distracted, using it as a tool to help you do your job better. And then the other thing I would say is start using it yourself. I think there's a big difference between people who don't use these tools at all and use them a lot. They're not going to be good at everything. You don't know what they're good at, what they're bad at until you start playing around with them. And I think a lot of people are going to be surprised when agentic AI becomes mainstream and mature. And I don't think as professionals we want to be one of those surprise people. I think we want to be on the leading edge and be able to come to our organization. We're the closest to customer needs and opportunities and our work should be spanning a lot of the functions across the organization. So I think we should have some AI expertise that we can bring to the table to help our organization implement these.
Greg Kilstrom
And you know, the research, we didn't talk a lot about the employee experience specifically, but you know, the research touched on there's huge opportunity in cx, but also with ex, what's the relationship between those two or, you know, how should leaders be thinking about that?
Isabelle Zidatny
Yeah, it's a good question. And we actually, I should say for the executive study, we also asked about plans and ambitions around employee experience as well. And it was very similar to what we found on the SEAC front. I think on the short term, as I said earlier, the biggest value looks like it is going to come from those productivity gains from helping augment employees work. So I think that's where a lot of organizations are starting, is helping employees. It's also a little bit lower risk. Right. Internally. But I think the more you can free employees up and take away some of the routine, repetitive administrative tasks so that they have the bandwidth to make those genuine human connections with customers and do their jobs better, that then you're going to see the customer experience improve as a result of improving the employee experience.
Greg Kilstrom
Yeah, I mean the employee's happier doing more valuable work and the customer can only stand to benefit, right?
Isabelle Zidatny
Yeah. It's an interesting dynamic though. Like customers, employees and executives of employees do sit right at that intersection point where they have to use all the tools internally, but they're also noticing how it's helping them. As part of our EX Trends 2025, they were actually more, I think, confident in AI than customers were because they've seen the applications within their roles.
Greg Kilstrom
Well, as we wrap up here, just a couple things for you here. I know X4 is not done yet, but you wanted to get a sense of what's been a highlight so far of your experience here.
Isabelle Zidatny
Oh, it's such a good question. I have to say. I just love seeing everyone, I work remotely so talk to people a lot, all the time. And the opportunity to actually get to spend FaceTime with people, just connect with clients too, one on one and hear those kind of side stories and things that you wouldn't get in like more official conversations about what they're doing and thinking about is always really exciting to me.
Greg Kilstrom
Great, great. Love it. And last question for you. I know you were on the show, so I asked this to you before, but I'm going to ask you again. We'll see. We can compare answers here, but that's a research project of its own. What do you do to stay agile in your role and how do you find a way to do it consistently?
Isabelle Zidatny
Oh, I do think I'm going to answer this the same way. I think for me it's continuous learning and staying curious, especially if you think about something like AI, right. That's changing all the time. The ability to continuously be taking in information, synthesizing it, thinking about it, and just making sure that I, you know, Head of Thought Leadership, I need to be aware of where we're going to help kind of prepare people. Yeah, exactly. That doesn't sound kind of fascistic at all. But yes, I would say just continuous learning and staying very curious.
Greg Kilstrom
Wonderful. Well, again, I'd like to thank Isabel Zadatny, Head of Thought Leadership for XM Institute at Qualtrics, for joining the show here at Qualtrics X4 in Salt Lake City. You can learn more about Isabelle and Qualtrics 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.
Isabelle Zidatny
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Greg Kilstrom
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Podcast Summary: The Agile Brand with Greg Kihlström®
Episode #660: Enabling and Accelerating Customer Experience Improvements Using AI with Isabelle Zdatny, Qualtrics
Release Date: April 7, 2025
In Episode #660 of The Agile Brand with Greg Kihlström®, host Greg Kihlström engages in a compelling discussion with Isabelle Zdatny, Head of Thought Leadership for the XM Institute at Qualtrics. Recorded live at Qualtrics X4 in Salt Lake City, the episode delves into the transformative role of Artificial Intelligence (AI) in enhancing customer and employee experiences (CX & EX).
Isabelle Zdatny shares insights from a collaborative research effort between Qualtrics and McKinsey, revealing that strategic AI investments can unlock between $860 billion to $1.3 trillion in annual value across various industries (04:36). This substantial economic potential is categorized into three primary avenues:
Notable Quote:
"AI enabled customer experience is expected to drive an estimated $860 billion and possibly all the way up to $1.3 trillion in annual value."
— Isabelle Zdatny (04:36)
Isabelle identifies two critical missteps organizations often make when integrating AI:
Implementing AI for Its Own Sake: Companies adopt AI technologies driven by the allure of innovation or executive pressure without a clear outcome-oriented strategy.
Notable Quote:
"They're just like, we need to stand up these technologies rather than starting with what is the outcome that we are trying to achieve."
— Isabelle Zdatny (04:36)
Stagnating After Pilot Projects: Organizations initiate costly AI experiments but fail to scale them enterprise-wide, limiting potential value creation.
Notable Quote:
"They start small. They do very expensive experiments and then they don't really scale them more broadly across the organization."
— Isabelle Zdatny (04:36)
Transitioning from isolated AI initiatives to a cohesive, organization-wide strategy is essential. Isabelle emphasizes the importance of dismantling silos to maximize AI’s impact.
Key Points:
Centralized Governance: Establishing an AI governance council to oversee and monitor AI use cases ensures alignment and effective implementation.
Change Management: Facilitating a cultural shift where employees feel confident and competent in utilizing AI technologies.
Technical Infrastructure: Investing in robust data management systems, such as an enterprise data warehouse, to support scalable AI applications.
Notable Quote:
"AI compounds the garbage in, garbage out issue. So making sure it's all clean and good for powering your LLMs, it's a big undertaking."
— Isabelle Zdatny (14:46)
The conversation explores how AI can significantly enhance customer experiences, despite a recent decline in consumer comfort with AI technologies.
Insights:
Consumer Sentiment: A reported 11-point drop in consumer comfort with AI reflects a "trough of disillusionment" within the current hype cycle (15:29).
Effective Use Cases:
Virtual Assistants: Streamlining complex processes, such as claim submissions, reducing processing time from days to minutes.
Personalized Interactions: Enhancing customer satisfaction by meeting individual needs swiftly and effectively.
Notable Quote:
"Customers don't care about that [AI]. They care about being able to achieve what they want to achieve, you know, quickly, effectively, enjoyably."
— Isabelle Zdatny (15:29)
Isabelle highlights the symbiotic relationship between AI implementation in employee workflows and the resulting improvement in customer experiences.
Key Points:
Productivity Enhancements: AI tools free employees from routine tasks, enabling them to focus on creating genuine human connections with customers (22:13).
Employee Confidence: Employees exhibit higher confidence in AI applications within their roles compared to overall customer sentiments.
Notable Quote:
"The more you can free employees up and take away some of the routine, repetitive administrative tasks so that they have the bandwidth to make those genuine human connections with customers and do their jobs better, that then you're going to see the customer experience improve as a result of improving the employee experience."
— Isabelle Zdatny (22:13)
For organizations eager to harness AI effectively, Isabelle offers strategic advice:
Outcome-Driven Approach: Begin with clear objectives aligned with business goals rather than pursuing AI for novelty.
Hands-On Engagement: Encourage teams to actively use AI tools to understand their capabilities and limitations firsthand.
Develop AI Expertise: Cultivate in-house AI knowledge to lead and support AI initiatives across the organization.
Notable Quote:
"Start with what is your organization’s AI vision and strategy and value. So what are the outcomes you're trying to drive."
— Isabelle Zdatny (20:28)
Looking ahead, Isabelle anticipates that AI will seamlessly integrate into everyday business operations, potentially becoming so ubiquitous that the term "AI" may become obsolete as its functionalities become standard practice.
Notable Quote:
"I think in five years we may not even use the term AI, it'll just be doing stuff."
— Greg Kihlström (19:00)
The episode underscores the pivotal role of strategic AI investments in driving significant value across customer and employee experiences. By avoiding common pitfalls, fostering a culture of continuous learning, and prioritizing outcome-driven AI applications, organizations can unlock the full potential of AI to achieve long-term business growth and enhanced customer lifetime value.
Final Quote:
"Continuous learning and staying very curious."
— Isabelle Zdatny (24:28)
Economic Impact: AI's potential to generate up to $1.3 trillion annually through productivity, revenue, and process improvements.
Strategic Implementation: Importance of moving beyond pilot projects to enterprise-wide AI integration.
Customer and Employee Synergy: Enhancing employee experiences with AI directly benefits customer satisfaction and loyalty.
Future Outlook: AI poised to become an integral, unobtrusive part of business operations.
For More Information:
To learn more about Isabelle Zdatny and Qualtrics, visit the show notes. For additional episodes and resources, subscribe to The Agile Brand at theagilebrand.com.