 We were very, we were thrilled and humbled to have so many wonderful people who participated in that ad, and we do strongly believe that AI is a responsibility that we all have. And so I'm excited to be here with you today. Again, Michelle Bookoff-Bidek, most people call me Michelle Beebe, so that makes it a lot easier. Josh, thank you so much for having us into the entire ad week staff. I'd really like to thank you for convening what is an impressive group of leaders today as we talk about the power and the promise of AI. If I talk too fast, raise your hand. I just flew in from Germany, so I'm on a different time zone completely. But I'm really looking forward to this conversation, because there's a lot that we, as marketers, as stewards of our brands, need to understand about AI. But before we get there, I want to tell you one of my favorite stories. And you may not think that this is actually an AI story, but I promise you it is. I want to introduce you first to a stay-at-home mum in a small town outside of Lynchburg, Virginia. This mum defied the forces of nature and managed to protect both herself and her infant daughter by hiding under a mattress in the basement of her home when a deadly EF3 tornado sucked everything else away. Everything. In a matter of moments, her home and many others in her small town were gone. The tornado tour path that was 21 kilometers long and 366 meters wide with estimated max sustained wind speeds between 215 and 265 miles per hour. It was pretty impressive. The mum credits her life and that of her baby daughters to one thing, a mobile alert from a local broadcast station, WDBJ. A simple message pushed to her phone telling her that her home was in the path of destruction. A simple message developed using Watson, IBM's sophisticated and powerful artificial intelligence to ensure that she got the life-saving information she needed when she needed it most. I think that's a pretty powerful use of AI, would you agree? Now this same concept, this ability to make predictions and automate them at scale has much broader applicability. We believe it has the opportunity to change the way people work, how businesses fundamentally operate and how industries transform and of course always to help people. So as we move forward today I want to shift and talk a little bit about business or AI in the context of business. Here it's about using technology, truly advanced technology to solve some real-world problems. But I want to tell you a secret and it's probably not a surprise to any of you. The technology while it's essential is not enough. To truly take advantage of the power that AI offers, you have to be creative and you have to focus on what it is you are trying to achieve and in our world creating real business value from AI comes from understanding our customers like never before, leaning into the customer experience, really understanding what that customer experience should be and reimagining the ways in which we engage with those consumers who touch our brands every single day. In fact, I believe that AI has the potential to transform the relationships we have with our customers in ways we never thought possible. So for the rest of our time together, I want to talk about three things. I do want to talk a little bit about the market potential, I'll share some stats because I think they're pretty powerful and let's face it, the growth of AI is exponential. And then what I want to get to is some of the meat. I want to share with you some really exciting examples of companies that are putting AI to work today for their customers in very different industries. And then third, we're going to touch on the future because what we need to understand is not necessarily where AI is headed but what are companies doing now to prepare? How are they planning for the impact that AI will have on their business? Okay, so let's start with the potential. Last year, AI-related technology has contributed $2 trillion in U.S. dollars to the global economy and by 2030 it is anticipated that AI will contribute almost $16 trillion, $16 trillion with a T. The interest in AI is growing largely because it has the ability to solve one of the greatest challenges we face. Anybody know what that is? Data. We're drowning in it. 2.5 quintillion bytes of data generated every single day and yet we are still starving for insights. AI helps us take advantage of all of that data, much of which is still dark and inaccessible and use it to drive business results, improving decisions and outcomes. Now, despite the need, adoption has been rather slow. I guess, would you agree, do you see, we see it quite a bit that our customers are still trying to figure out how to apply AI in the business context but do it at scale and so while we understand the power that AI offers, many of us are still struggling to figure out how to unleash its potential and that's because, as my colleague Rob Thomas would say, AI is not magic. It is not magic. It's hard work. There is no one to be waived at enterprise inefficiencies and challenges. As I said before, the technology alone is not enough. At the enterprise level, AI is really about fundamentally three things. Predictions, automation and the optimization of business processes to drive decisions and improve outcomes. So let's talk first about predictions. Companies need to be able to forecast to predict what's going to happen in their business at both the macro level as well as at the very micro level. Second, automation. There is tremendous value in automating those business processes which right now are critically necessary but incredibly time consuming and still very manual. In customer service, for example, AI has the potential to answer basic customer questions like password resets. I talked to our CIO. We're deploying AI to help with basic help desk functionality. Password resets and account number lookup. First time call resolution. We are freeing people up by doing this to focus on higher value, more creative work and I think that's really important here. And then the third thing is optimizing business processes. Whether at the organizational level or at the individual, AI is helping businesses rethink complex processes like mortgage loan approvals. Think about that. A mortgage loan approval. How long does it take? Hours? Maybe days? We're reducing down the approval process to minutes. So now I want to shift and I want to talk about some of the companies that we're working with that are putting AI to work to solve customer problems and they're doing it in very different ways but all with one common thread. How is AI delivering improved experiences for the customer and thereby increasing satisfaction? And I'm so excited to be sharing with you four great customer examples. Okay, how many of you are familiar with Scott's Miracle Grow? Scott's, yeah, do you use their products at home? It's a great product. It's a wonderful product but think about it. Given the seasonal nature of that business, Scott's makes the majority of their annual sales in the first 100 days of the year. Why is that? Well, because that's when spring is approaching. People are thinking about stocking up on those lawn and garden supplies. It's a difficult task for Scott's though, think about this. They have to grapple with varying temperature and weather changes across the United States. We've got all of these different weather patterns. You'll notice a theme by the way of weather. I did prior to being the CMO of IBM Watson. I was the CMO of the weather company. So you may see a little bit of weather thrown in here. But when you're grappling with those different weather patterns and temperatures across the United States, that can be a challenge. Let's face it, I was not working on my lawn in February in New Hampshire. But anybody from like the South Florida? No, you're all local. They were probably already stocking up. So as such, Scott's needs to ensure that their products are delivered in time to meet the demand where it is to optimize sales. And so they turned to IBM Watson and the weather company. Because we're the source of AI driven weather data and insights delivering more than 25 billion with a B weather forecasts every single day. Now through a weather based demand planning tool, Scott's receives hyper local forecasts. And I want you to think about this hyper local forecasts four months out. As a result, they can accurately predict the impact that weather is going to have on their business. They can identify whether driven shopping trends and optimize both their supply chain as well as their marketing strategies. So they know when to start promoting certain brands, when those conditions become right for yard work, where those conditions exist. And that's going to drive sales across each unique market. And just so you know, as you can see up on the slide, this solution has helped them increase annual sales by $30 million. It's pretty incredible. All right, so we've discussed how AI can help us make predictions to inform when to run promotions and where and how to allocate retail stock. But what about using AI to actually develop advertising creative itself? All right, let's take a look at Lexus. It stops a little bit every time I see that. I think you've seen in the last 15 years a lot, right? Maybe none like that. What makes the good ones engaging, entertaining, memorable? I'll bet you'll remember that one, right? It can be difficult for auto manufacturers and their creative agencies to identify the most impactful thematic and visual elements that are going to best resonate with their target audience and, oh, by the way, make for a compelling ad. So then Lexus decided to turn to Watson and they used AI and the potential that AI has to offer to aid in the creative process. In fact, Lexus used Watson, I'm not gonna be able to say that, Lexus and Watson. Lexus used Watson to analyze 15 years of can award-winning footage, text, and audio for a range of automotive and luxury brand campaigns. Watson was able to identify and surface the common attributes of the best received content. Content that was both emotionally intelligent and also entertaining. Watson informed the script flow and the outline from which their creative agencies built the story and Lexus recruited Oscar-winning director Kevin McDonald, so think Last King of Scotland or Whitney, to direct the Lexus Driven by Intuition campaign. The result is what you just saw, a fascinating 60 second ad in which Watson helped to give the car a kind of personality and hero's story all its own. This is a great example of AI augmenting humans, not replacing them but augmenting humans to do some really creative work. Okay, so you've got brilliant creative, check. But now you need to make sure that you're delivering ads that are both engaging and personal. Consumers, as you know, just as well as I, don't respond well to a one size fits all message. They want it to be relevant to them and they want to receive it in the manner that they're gonna most resonate with. They also sometimes want to be able to access follow-up information and options. So first a question for all of you in the audience, how many of you use all of your vacation days don't lie? Anybody? Good, that's good. But I didn't see too many hands raised. Well, this may actually make you think about using some of them. Iconic German airline, Luft Hansa, wants to convince you to think about how you use those days. And they've turned to AI powered advertising to help. Recognizing the need to create personalized experiences for their prospective customers. Luft Hansa wanted to connect with people in a way that highlighted the airline experience, while also offering suggestions and tips for foreign travel destinations. They wanted to inspire flyers with exciting destinations, while positioning themselves as the ideal travel partner. All through an ad that could interact naturally. And that's where Watson ads came in. The solution allows consumers to have a conversation with the AI about what it's like to fly Luft Hansa. Building interest with the benefit of personalized interaction. But the digital ad goes a step further, as you can see, by actively highlighting vacation destinations to which Luft Hansa flies. It shows photos of beautiful European destinations like Paris, Rome, Barcelona, and I think what you're seeing up there is Prague. While also offering travel tips, vacation ideas, and yes, a link to the flight reservation page. Personalized experiences like this are the future of advertising. And AI is helping us get there. So hopefully you'll all go visit Luft Hansa and check them out. Finally, the fourth story that I want to share with you takes us a little bit away from the creative process, but one that I think is still fundamental to brands, to marketers, to those of us who work with customers every day. And that is ensuring that your customers get the information they need when they need it most. And this is most critical, I think, in a customer support environment. So let's think about that in the context of a complex industry that is so reliant on customer service, banking. The Royal Bank of Scotland, or RBS, is a 292-year-old bank that has undergone a massive digital transformation. The bank receives more than 100,000 customer inquiries every single month. And that can be challenging for not only the customer service representatives, but also the consumers who, in this day and age, expect round-the-clock accessibility and first-time problem resolution. This is the perfect problem for AI. With the help of Watson, RBS built Quora, a digital assistant that helps the bank better serve customers through that first-time problem resolution. Quora was trained on over 1,000 responses to more than 200 customer intents. And an intent is something like, how much money do I have in my account? Can you reset my password? Where is the nearest branch? What are your hours? Think about that. Quora had to be trained on all of those questions and intents, and they had to do it in natural language because some of us might say, what are your hours? Or what are the hours of the bank? Or when do you open? Quora had to understand all of that. And she's learning more every single day. And what, of course, doesn't know the answer to a question? I bet every one of you is called your bank or your insurance company at some point or another because you're just not getting the response you need either from a virtual assistant or online. Well, Quora will seamlessly connect you to an agent live, no bouncing around from menu to menu and that agent has your information right there visible. Building on the success of Quora, RBS used Watson to build an assistant for their agents called Marge. And Marge is great. They love Marge. They send Valentine's cards to Marge. I kid you not, I've seen them. She helps them address the more complex questions giving them all of the information they need in real time. She has been a lifesaver to them. These approaches demonstrate how we are moving beyond simple chatbots to true conversational solutions that can interact with humans naturally and then seamlessly escalate complex problems. So you can imagine the possibilities across industries and companies. Okay, so you've just heard four stories of how companies are putting AI to work. I wanna talk just a little bit about how we can think about successful AI strategies, how you can propel your organization forward and the keys to success. And there are three, I believe. First, and most importantly, focus on the problem you're trying to solve. If you try to broad brush AI, it's not gonna work. Each of the examples that I gave you, there was a specific and discrete challenge. And that's really important. The other thing is that you need to have your data in order to be able to really get the power of AI. After all, it's data that is fueling your AI. Again, as I shared those companies, they organized their data, they understood how to best use it, they knew what their customer problems were and what they wanted to accomplish. And since then, they've been deploying more and more solutions as they've gone on, as they've piloted, as they've seen success and realized true business value. And in all of these applications, this was not about AI for AI's sake. This was about innovating to create true value for their customers. Okay, I do wanna touch on something because I think this is probably something that we all think about, skills. What do you need to build an AI competency within your organization? After all, AI needs to be trained and managed, right? So you have to have the technical prowess. We know that that is critical. But you also need diverse teams of people that bring a sense of, an innate sense of curiosity and skill to the table. And that's important too. You don't necessarily have to have just technical teams and you probably don't want just technical teams. One banking client of ours has taken frontline customer support personnel and trained them to be conversational designers and conversational analysts. These are not experts in machine learning. Why would they do something like that? Well, guess what? When somebody says, what is the balance on my credit card or how much money do I have in my bank? They don't wanna just know the number. They wanna know if they can afford to buy something. Understanding how humans think is so critical and that's why those folks are doing these new roles in these new jobs. Another example comes from a company called LegalMation. Using Watson, they've built a tool that lets legal practitioners use simple drag and drop functionality to draft early phase response documentation. Now, I don't know about you, but having to sift through an entire legal document, not something I wanna do. It is something that usually takes an associate attorney at least a day. It now has come down to just minutes. Now, for Watson to be proficient in legalese, a team of lawyers had to train it though. Again, these are not technical experts, these are business people. And while that might seem like a daunting task for those legal professionals, believe it or not, in just a few hours, they were up and running on the system. Finally, and if I leave you with nothing else, I want you to remember this. We have to trust the systems we build. We're talking about AI here. And if you're infusing it into your business processes, you wanna be certain that the outcomes that your AI is generating are both fair and explainable. We still see companies that are very concerned about this AI black box. A recent IBM executive, I'm sorry, a recent IBM study of C-level executives, I think it was about 5,000, shows that 60% are still holding off on their AI journey because of concerns around data and insights ownership, concerns around trust in AI and compliance. Building trust in AI means that we're solving for things like algorithmic bias, right? And that bias might be societal like gender or race or it could be something as seemingly innocuous as a user's location. At IBM, we are building the tools to help companies detect and mitigate bias both in the training phase as well as in runtime because we strongly believe that safety, security and trust in AI is critical for driving widespread adoption. Okay, so before I go, and I know I'm running out of time, I just wanna leave you with three things, okay? Number one, whether you are starting on your journey, your customers are starting on their journey, always, always come back to your purpose because in most cases, and in my case in particular, it's gonna start with the customer, their needs and their pain points. Number two, think about how you can put AI to work at scale today just like the companies that you saw here. Hopefully in those examples that I shared, Lexis, Scots, Lufthansa and RBS, you saw what is possible and hopefully you're as excited by the possibilities as I am. And then finally, the future is now. Artificial intelligence is becoming increasingly important to overall business strategy and we're tackling challenges related to trust and bias as we see more and more companies deploy AI. Okay, and then I'll leave you with this. As the shepherds and the stewards of your own brands, you have a seat at the table during this exciting shift but you also have the responsibility to apply the technology for the good of your customers and we at IBM really look forward to seeing how you progress and with that, I wanna thank you for your time. I hope you enjoyed it.