Unlocking the X-Factor: A How-To on Accelerating Business with AI with IBM's Vice President of EMEA

Dawn Herndon, everybody. I'm thrilled to be here. Thank you for taking 15 minutes to spend with us and talk about the X factor. Any guesses what the X is? An X factor? Anybody? Does anybody think that AI is the X factor for your business and can lead to exponential growth? I'll see how many X's I can use throughout the presentation here in the next 10 or 15 minutes. How many words do I say that start with the word or the sound? Ex. So the first thing I want to do here is just show you what the dictionary says the X factor is. It's a variable that leads to a significant impact in the outcomes that you drive. So today we'll focus on different areas that AI can accelerate your business and different factors that you need to think about as you are building products and solutions that you want to take and sell to your clients. Now, I think we mentioned when I came up on stage that I'm with IBM. Sometimes people don't think about IBM in the mainstream aspect of being a technology company that develops AI technology, but just by show of hands, or even just yell it out, shout it out here in the audience. Does anybody know how long IBM has actually been focused on developing the AI technology that we have in market today? Let's just do a range. We started developing it in 1940. 1940. 40 years. Okay, 40 years. That's a good guess. You're close. Actually, it was actually a little bit longer than 40 years ago. It was in 1956 when what we believe is AI today was originally started from a development perspective. That's not to say, though, that what we're doing today is what we were doing in 1956. What we are doing today is two things we are focused on, first of all, helping organizations accelerate how they go to market with AI by providing the best of breed technology and innovation in the AI space available. And we do that through being very open, focusing on open source, focusing on developing AI, so that it fits the purpose of your company and it fits the domain or expertise that you need to deliver in how you sell to your customers and how you ultimately make money. Okay, so this slide here is to just give you something to think about. How do you leverage AI today to drive all of the outcomes that you need to as a startup, as a big organization or enterprise that has a startup organization within it? Really what you're wanting to do here is grow revenue, right? At the end of the day, every single company on the planet needs to figure out a way to make money. And every organization needs to figure out a way to attract new clients and to grow revenue streams or routes to market and sources of revenue in order to attract new clients. So we want to talk to you about how you could leverage AI technology just to do that exact thing. So when we talk about how do you accelerate your business, we really do look at a couple of different ways that organizations are looking at productivity enhancements through leveraging AI technology. And I will say that there's a lot of information and a lot of statistics here on the page. But when I think about how do organizations that I work with look at how to leverage AI technology, I would break it down into three different silos. In every company, for every organization or leader that I've spoken to, they look at how do I increase employee productivity. So that is leveraging and embedding AI into how my employees work, how they collaborate with each other, how my internal business processes and systems work, and leverage AI to make them optimized and more efficient to deliver better outcomes internally for my company. Number two is how do I appear to my customer base? How do I market my company? How do I take advantage of AI and technologies that allow me to interact with my customers on a more efficient, more cost effective basis? For example, in a call center, if you have customers calling into your support organization and you want to accelerate how quickly they can answer questions, provide responses to your customers to then reduce the amount of time that customers are working with you on customer support, that's one of the ways that you are externally interacting with your customer base. And then number three, the area that's very dear to my heart is how do you take advantage of AI in the products and the solutions that you sell to your customers? How do you leverage technology to attract new clients, enhance the products that you bring to market? How do you take that enhancement and drive new sources of revenue and new revenue streams by attracting and getting to new clients? So if you take all three of those different areas and you apply them, and you look at the different productivity challenges that we have here on this slide, you can correlate and you begin to see where you need to make investments from an AI perspective in order to accelerate your business. One of the areas I want to highlight here on this page is development and IT operations. I do believe this is one of the areas right now that we are still seeing a lot of organizations testing and experimenting with AI to decide where to start. If you take advantage of the large language models and the generative AI features that are today's mainstream AI conversation, how do you leverage those in the development cycle that you have of your products so that you can get to market faster, so that you can reduce the amount of time that your developers and your companies are working on adding enhancements to the products that you bring to market. So some of the different areas that you probably want to think about is that the product development lifecycle itself could take tremendous advantage of AI and then drive a significant outcome for your company and how quickly you get to customers and new customers. There are a number of barriers that organizations are dealing with and I think probably these are not a surprise to a lot of you. Integration and scaling challenges is one of the areas that people are really still trying to experiment with in the AI space. They are looking at how do I take advantage of AI and go from experimenting, which I've been doing for probably the last two to three years, since AI became such a mainstream topic of conversation in every company, and how do I scale that inside of my business? We're going now and what we're seeing trend wise happen is going from experimentation to really driving automation in the AI space. We used to talk about how important it was to get the data model correct, how important it was to leverage the correct large language model. And where we are today is moving toward how do you build models that are tuned and trained on a specific domain, a specific industry for a specific business need. So we are actually overcoming a lot of these barriers. And as we continue to go through this evolution of the AI technology roadmap, another area I want to point out here is governance. One of the biggest considerations that companies of all sizes need to make, not just big companies, but small companies as you're starting, and organizations that are going to leverage any kind of technology is how do you govern your data, how do you govern that technology being integrated or embedded into your solutions? I think that here in the, in the UK and leveraging some of the information and data that has come out from the EU AI act is very important. But if you're working with vendors that are providing AI technology and they're not focused on how do you govern and secure and keep compliant in how you deploy the AI technology or how you embed AI technology to accelerate your business, you are going to potentially be exposed because you can't control some of that data unless you know where data came from. So a really important piece of how do you drive business value and how do you exponentially grow and make a significant impact in your business around AI? The X factor is to really think about how well the data is governed and how well you know where the data came from. I'll skip through the rest of these for now, but I want to come here because I mentioned to you that one of the ways that organizations are looking for how do I leverage AI to drive an exponential impact to my company, the X factor, it really is moving toward AI assistance. Some of you may hear these things referred to as co pilots. It's very, it's not different. We call it AI assistance in our world. And the reason for that is because we believe that across all of the domains that you have and all of the functions that you have in your company, there's going to be a place for AI and there's going to be a way that AI will enhance that experience or the productivity of the person or the end user that is interacting with it. So if your assistant, your virtual agent, your digital assistant, your copilot, your ultimate end user, has the ability to have automation and integration with backend enterprise systems, your ability to increase productivity of your employees, the first example I shared a little while ago is going to increase with automation. We talk about the ability in the AI assistant or the virtual assistant or digital assistant to have a conversation, which is really common, a chat via a chatbot like experience in this digital assistant. And instead of just having a conversation where the large language models and the data models that are behind the scenes are driving, the answers that you see in that conversational AI interface really evolving to how do I take action or how do I execute a command inside of that AI assistant? Which is one of the reasons that we are calling it an assistant, because it is essentially going to become a person. For example, in the HR example on the page here, the ability for me as an employee of a company to go into an AI assistant for HR that's trained on the HR terminology and vernacular, that understands comments and commands like transfer this employee to John Smith, the new manager, give this employee a salary increase, and you do that through a chat in this AI assistant. And then behind the scenes, the workflows and the decisions and the integration and interaction with the data model will happen automatically through automation. So the future of AI and the evolution that we're in today is really driving toward making it more tangible and realistic to how you run your business. If I go back again and I talk about the other factor, the products that you develop and you sell to your customers, how do you enhance those with AI? Perhaps you're a fintech and you're working in the banking industry and you are creating a new loan and you want the loan processing agent to be able to talk to the underwriter and provide data and information directly to the underwriter through a conversational AI system. That's reality. And you could embed AI technology into your product, that is that loan processing software platform, if you will. And you could drive that outcome with AI and with AI assistance. You see a number of logos at the bottom of the screen. The logos are here to just give you an example of all of the companies that you're probably familiar with and you probably use inside of your company every day that are thinking about AI in this way and thinking about the future of AI. Being again, very focused on how do I go from experimentation to scaling in my company. So speeding up your AI ready business. I just want to summarize a couple points that we made here before because I think it's really important to think about multimodals. There's lots of vendors out there that are creating large language models. There are lots of vendors out there that do them in an open source kind of way. I'm very familiar with one of those. There are other proprietary vendors out there as well. But all of the models are about making sure that they're trained and tuned to the domain that is specific to your company or your functional area, how you leverage your data, how you govern the data, how you govern the technology and the implementation of the technology. Again, very important. How do you leverage and even more importantly, how do you fill the skills gaps that every company on the planet is dealing with right now by leveraging AI technology? And how do you create client ready use cases to leverage the best practices that are out there from some companies that have been in this business for a long time and some companies that are coming into the business over the last three to five years. And then most importantly to me, my favorite topic is how do you go to market and how do you drive new clients, how do you drive new business streams? How do you drive new routes to market so that you can ultimately grow your business by leveraging technology? I do believe that's the X factor. And when we identify the use cases that get us there and drive that significant impact, your businesses will grow exponentially. And again, I do thank you for your time here today and for listening to how you can accelerate your business through the X factor being AI. Thanks everybody.