Good morning. Good afternoon everyone. I'm genuinely grateful for your presence today as we embark on a journey into the AI frontier in the world of CMS. Your time and interest are greatly appreciated. I'm Paul Taylor, and I'm proud to lead the global pre-sales team at Crownpeak. By trade, I'm a software architect, a product strategist, and a product marketer. Today, I spend much of my time talking to customers and partners worldwide. Throughout my career, I've been fortunate to build and deploy teams using the many content management platforms that we see in the market today. Crownpeak is an AI led and fully composable digital experience platform that puts accessible content and commerce at the forefront of the buyer's journey. We have over 800 customers and 1100 brands across multiple industry verticals, and to support this, we have over 350 employees globally. Since 2016, Crownpeak has been on an acquisition journey, adding complementary products that empower customers to build their digital experience platform through a curated choice. We were fortunate to have acquired our own data science teams in our most recent acquisition. While the foundation of this team is our product discovery and merchandizing products. We have been able to harness this team's expertise to drive AI capabilities across our broader product portfolio to help customers recognize more significant revenues and operational efficiencies. So with those introductions, let's focus on today's agenda. First, we will focus on some of the current landscape and trends, discussing how AI is evolving in the market and how it is being used in our sector content management. Next, we will look at some real world applications of AI and how they can create significant benefits when deployed inside the organization. But it can be challenging. So we'll look at some of the common challenges that organizations see as barriers to adoption of artificial intelligence. Before we wrap up with your questions, we'll look at some of the future industry trends and strategies that you can adopt to help you leverage the power of AI as part of your everyday life. And if you have questions as we run through the content, please drop them into the chat and we'll answer them before we end today's webinar. So let's dive into the world of AI and explore some of the current landscape and industry trends that we're seeing. Artificial intelligence is nothing new to any of us. Ideas that formed the basis for AI were conceived during the 1930s, 40s, and 50s. Norbert Wiener's cybernetics described control and stability in electrical networks. Claude Shannon's information theory describe digital signals, and Alan Turing's theory of computation showed that any form of computation could be described digitally. But it wasn't until 1956, when a team of scientists got together to dive into the possibilities of creating machines capable of simulating human intelligence, that the term artificial intelligence was founded as an academic discipline. While academic research continued from 1956 onwards, it had relatively few commercial successes, primarily due to a lack of computing power capable of crunching and predicting tangible outcomes. During the 1980s, I started to be thought of as a solution to real world organizational problems, and while a boom happened between 1980 and 1987, ultimately it came crashing down in 1987 as the modern desktop computers manufactured by Apple and IBM grew in power, and this in turn ripped the market away from vendors that were championing AI research. Fast forward to 1993, and we start to see a resurgence of AI research and ultimately deployment into many of the everyday use cases we see today. And this trend has continued. Think of your everyday life. Think of all the tools and services that you use to get through the day, and all of them in some way, powered by the technologies that we conceived over three quarters of a century ago. Maps and navigation. Getting you from home to the office, from the office to the coffee shop, and from the coffee shop to the gym. Chatbots reducing or removing the need for customer service reps to staff phones. Facial detection and recognition giving you access to or keeping you out of services. Helping law enforcement and security services to keep us all safe. E-payments and fraud protection, identifying unusual patterns in your payment history and protecting your wealth and autocorrect. While intended to speed up communication, you often must explain yourself in a further message. So, considering the examples above, many of these have been around for many years, not just the past few. And so back to my previous point. I is familiar to us. And so we come to today and the newest of AI hypes. Over the past 10 to 12 years, the amount of data available to organizations has grown exponentially as customers swarm to interact over a growing set of digital channels. This has been referred to as the Big Data era. With such vast amounts of available data, organizations could deploy deep learning algorithms to make sense of the information they were awarded and to make machine learning decisions based upon it. However, the transform architecture proposed by Google in 2017 led to the development and scaling of large language models models trained on vast quantities of unlabeled data, and that in turn gave us the foundation of the generative AI that we know today. Generative AI has changed since its inception by OpenAI in 2020 with GPT three. GPT four, released in 2023, moves the needle further concerning its potential to transform organizations. And with the adoption rates we're seeing today, it will likely continue to evolve even quicker. As we think about the industry is close at heart to what we do. As marketing technologists. We're seeing more opportunities for the deployment of generative AI services. High inflation levels are forcing companies to reduce costs and to become more efficient daily. However, despite challenging economic situations, online sales continue to grow, which is predicted to grow from 20.8% in 2023 to 31% of all sales by 2026, and globally. Changes in regulations, such as the upcoming European Accessibility Act, are piling pressure on organizations. Across the world, organizations are finding themselves under significant pressure to adapt to these conflicting priorities or risk being left behind by their competition. And as a result, many organizations are turning to an increasing number of AI vendors to keep their heads above water. The generative AI vendor landscape is booming, fueled by organizations desperate to increase their output while reducing cost. Market valuations are in turn soaring, stable diffusion and image generation technology, with over 10 million daily users raised 101 million at an over 1 billion valuation. OpenAI, the US artificial intelligence research laboratory, is now valued at over $20 billion, and engagement with other generative AI vendors is also on the rise. Midjourney and Dall-E two image generation technologies. These see many users interacting with their platforms daily and ChatGPT, the conversational tool that many of us are familiar with, saw over 1 million users register and interact within the first week. To put it into scale, that is two and a half times the adoption rate of Facebook and Instagram. The power of the movement is apparent and will continue to accelerate. According to Gartner, by 2024, 40% of enterprise applications will have embedded conversational AI, up from less than 5% in 2020. By 2025, 30% of enterprises will have implemented an AI augmented development and testing strategy, up from 5% in 2021. In 2026, generative design AI will automate 60% of the design effort for new websites and mobile apps. In 2026, over 100 million humans will engage robotic colleagues to contribute to their work. And in 2027, nearly 15% of new applications will be automatically generated by AI without human in the loop. According to chief martech, in 2024 there will be over 14,000 marketing technology products globally. This is a 27.8% year on year growth compared to 2023. They say that anyone can create software in the cloud. Generative AI has only accelerated this by inspiring tens of thousands of developers to build new things on the back of large language models such as OpenAI, Gemini, Lama, and Anthropic, and secondly, by facilitating development with AI powered copilots. And so we'd expect the number of vendors to increase further over the next few years. But it's this increase of vendors that not only creates choices, but also creates organizational complexity. Regardless of the organizational complexity that increased choice creates, it's clear that organizations that adopt generative AI capabilities will have a significant advantage over their competition. Surveyed in 2023, only 1 in 4 organizations had implemented generative AI capabilities into their marketing operations, and less than half had a current plan for adoption before 2025. A similar survey in 2024, but this time to the German market, showed a 1 in 3 adoption rate of generative AI capabilities, with over half of those planning to increase their investments. Although the markets may be different in the time between the first and second surveys, we could conclude that organizations who adopted generative AI programs inside their organization saw positive outcomes, and that, in turn, will drive more significant levels of adoption. For those organizations that are early adopting generative AI, the boosts in efficiency and therefore return on investment are profound. A Deloitte research study from October 2023 says Gen Z powers a content marketing advantage for early adopters. They quote an average of 11.4 hours per week in time saved per content marketer, a 12% return on investment and a 1.5 x improvement in content demand. Now think about your team's customers and organization, and ask yourself whether it's time to adopt the generative AI frontier for yourself. 11.4 hours per week per content marketer. How large is your team? A 12% return on investment. Remember, these are early adopters and so is the market. And therefore cost stabilizes. Prices will likely fall and return on investment will further increase. And a 1.5 x content demand improvement. Has anything else in your organization over the past ten years led to a greater customer content satisfaction rate by getting on the generative AI frontier? Now you have a significant advantage over your competitors. Significant advantages exist in the organization's early adoption of generative AI capabilities. The pressure on content creators to generate more than they did yesterday is growing. Up 54% on average in 2023. And as consumers continue to demand more from their trusted partners, marketers will continue to feel pressure. 1 in 4 organizations has already implemented generative AI capabilities, and research shows us that these organizations are already seeing both productivity 11.4 hours per week and customer satisfaction benefits. Remember 1.5 x content demand. For those organizations who have not yet leaped. Now might be the time or the risk getting left behind. Let's look at some of our colleagues in the Content management and Digital Experience platform spaces to see how they are applying generative AI capabilities to boost productivity and customer satisfaction for their customers. Contentful has launched its AI Content Generator, an open, AI powered assistant that reduces repetitive tasks like SEO, keyword generation, and translation. Magnolia's AI accelerator speeds up content creation and then personalizes that content for your audience. Optimize. The AI sits across their entire marketing suite to give real time, prescriptive suggestions on types of content that will convert and drive revenue. And it then creates that content for you. Knossos AI engine powers every feature in its content experience platform, from automating repetitive tasks to content generation and experience optimization. And Bloom Reach. They launched Lumi as part of their AI for e-commerce platform. Lumi understands workflows and which KPIs to prioritize to create better customer journeys. With such a rapid rise in generative AI potential and the significant organizational benefits that exist, almost every single CMS or Dxp vendor is scrambling to win the race to drive their customers efficiencies. At Crownpeak. We've listened to our customers and to the market. We've launched our generative AI to build upon our current content creation and quality management expertise. Crownpeak's AI assistant suite powers productivity, improves quality standards, and increases customer reach. The Crownpeak AI assistant is constructed of three parts, all working together in complete harmony. Crownpeak's Content Assistant helps marketers plan and generate content across any digital touchpoint. Crownpeak's Image Assistant optimizes image usage for multiple user agents and generate search rich tags to make content more discoverable and Crownpeak's Analyze assistant ensures that content is performant, optimized for the specific use case, and meets corporate, brand, or regulatory standards. The Crownpeak AI Assistant suite is designed to give marketers and content creators back the bandwidth they need to do the one thing that I cannot yet replace creativity. And it's that creativity that Crown Peak believes will separate organizations from each other in a world of increasing customer demand. Complex content assistant can optimize marketing tasks throughout every part of the content lifecycle. Creating engaging content was historically taken a lot of effort from understanding the audience for a particular use case through content generation and the review and optimization process. With Crown Peaks content assistant marketers can describe their organization's brand guidelines for language and style before describing key audience segments to tailor content, and then instructing that content assistant to generate content appropriate to that use case. Whether it be an SEO friendly blog article, a product detail page, or a campaign landing page. Content creation is further accelerated by creating a series of one click shortcuts that eradicate historically repetitive tasks, ensuring that every content author or marketer in your organization has an assistant who knows their needs to ask to simplify each job role, and by comparing originally created content with AI, suggested improvements to allow content marketing to review them side by side. The Crown Peak Content Assistant natively integrates throughout each part of the content creation lifecycle to feel native to the author and to make content generation a dream. Many organizations use digital asset management platforms to manage their image asset lifecycles. While these platforms help organizations ensure a single source of truth for each particular asset. Maintaining consistency across the deployed world can be challenging with the growing number of digital channels, user agents, and technologies. Crown Peak's image assistant sits between your digital asset management platform and the content management system to help the organization drive efficiency in asset version creation and management. Image recognition builds search rich metadata tags to make your asset search and selection a breeze. You no longer must second guess the designer's keywords to find a piece of content. Auto cropping of images selects each image is optimal resolution, size, focal point. Before creating versions appropriate to each digital touchpoint, search rich keywords can be created and used within web page content to help discoverability, and alternate text. Titles and descriptions can be suggested for approval to help speed up digital asset publication. With or without an existing digital asset management platform, Crown Peak's image assistant can speed up asset search and usage tasks once and once content is published, help customers find exactly the content or product that they are looking for. Continual optimization is one of the significant benefits organizations can gain from using AI capabilities inside their content creation lifecycle. Able to analyze vast amounts of data from many sources, organizations can benefit from automated opinions on massive amounts of content from a performance, discoverability, and digital quality perspective. Crowned Peaks Analyze Assistant reviews your entire content inventory and creates intelligent recommendations for content performance. Content suggestion returns correct tone of voice alternatives based on corporate brand guidelines. Content recommendations can be optimized against historical touchpoint. Performance data and digital quality standards are applied to every content recommendation to keep content making money and saving money. Only through continual refinement can content become optimized for each customer and their journey with your brand. The Crown Peak AI Assistance Suite empowers organizations to reap the rewards at Lightspeed. The use of generative AI has the potential to transform organizations. Per the Deloitte research I showed you earlier, 1 in 4 organizations already use artificial intelligence. However, many unknowns, uncertainties and corporate risks are closely associated with using generative AI inside the organization. Let's spend a little time looking into some of these potential barriers to entry, and showcase some strategies to help reduce those barriers. Challenge one. Is it worth it? Many tech savvy individuals are turning to ChatGPT in everyday use, and I'm no different from helping me generate content for this webinar to making me less verbose in emails to my boss, ChatGPT has quickly become the tool that individuals use to make them more efficient daily. And that is not going to go away. But think about the content management vendors we've discussed today, specialists in creating and managing tooling to help make marketers more efficient with data from hundreds, if not thousands of customers over decades of working relationships, all anonymized and used to train AI models that will create efficiencies inside each industry. Vertical ChatGPT on its own is simply not trained nor designed to be greeted with that level of knowledge. Every one of the content management or digital experience platform vendors that we've highlighted today has built generative AI capabilities into their products to solve everyday challenges highlighted by their customers. The integrations from these vendors are pinpointed at specific issues felt by the organization today, and as such, a sympathetic to how an organization's teams need to function to drive customer value. Challenge two trust. Generative AI is new and therefore trust levels are immature. I remember ten years ago when software as a service or SaaS was new, an organization simply didn't trust having their data in someone else's data center. Ten years later, most organizations worldwide have embraced the major cloud data storage, such as Amazon, Microsoft, and Google, and deployed vast swathes of their everyday business criticality into other people's data centers. So I assert that trust levels of generative AI will be no different as more data is available and AI models are further trained, trust levels will naturally increase. Fast forward another ten years and will be wondering what all the hysteria was about, as we did with the SaaS boom. But for now, while generative AI must be adopted inside the organization or you risk falling behind, a critical lens should be applied to that generated content. Fortunately, most of the content management and digital experience platform vendors I've discussed today have done precisely that. They highlight where content has been generated or where recommendations have been applied, allowing the organization to use a human gate to accept, amend, or decline a particular change. Crown peak goes one step further by wrapping digital quality tooling around all generated content, which, coupled with content management workflows, will help keep every organization on the right side of corporate, brand or regulatory standards. Challenge three security. Similarly to the previous challenge, trust and security typically go hand in hand. For generative AI to be successful, organizations must be prepared to share their data to train the AI models. But if the organization is not prepared to share adequate data for AI model training, they risk falling behind their competition. This conflict between security and trust creates a real problem in current day to day organizations. This conflict is one of the most significant barriers to the early adoption of generative AI. At Crown Peak, we generally see security as a shared responsibility between the organization, vendor, and customer. With the deployment of generative AI capabilities into content management and digital experience platforms. This responsibility can be split equally as follows. The content management or digital experience platform vendor is typically responsible for data encryption, access controls, and compliance with global data privacy regulations. In almost all cases, regular operational control audits such as Soc2 or ISO 27,001, as well as information security certifications such as Fisma, moderate and 853 and vulnerability scans are maintained by vendors to protect customers. The organization, using the Content Management or Digital Experience platform must take responsibility for sharing and protecting their intellectual property, typically by ensuring access controls are designed and maintained within their platforms. But it's not just about the software themselves. They must design and implement a series of internal policies to keep their employees working within the framework that they have designed. Regular internal audits of information, employee security training, and a commitment to thoroughly test generative AI initiatives as they are deployed to the organization. As part of a shared responsibility model for generative AI, security, organizations should consider creating an AI operational framework to describe the acceptable use of generative AI across their employee and customer base. We've seen many real world examples of where and how artificial intelligence is being used, and we've examined how it's used in content management and digital experience platforms to drive efficiencies and engage customers. But what about the future? What should we all be thinking about when it comes to implementing our own AI strategies? As we discussed at the beginning of this webinar, Crownpeak is fortunate to have had data science teams for some years, and as such, we have seen the rise of generative AI and have been able to quickly adapt. In addition to the areas that Crown Pique has addressed today around content creation and delivery lifecycle. If you like the tip of the generative AI iceberg, we expect significant investments into four distinct themes over the next few years. Conversational digital experiences. We've already seen the demise of the traditional browsing experience in preference for the search bar. Consumers are impatient, and the expectation set by major search engine providers such as Google have led customers desire a search experience in preference for a browsing one. With the general use of ChatGPT across the consumer base on the rise, it's only natural to assume that this conversational interaction will become one of, if not the primary, way to interact with a brand. Requests to show me a product with X or Y property that is available in my area will result in the most appropriate products being automatically added to the consumer's shopping basket, ready for checkout. Over the next few years, chatbots will become one of the most effective lead generation and conversion channels. Multisensory digital experiences, digital touchpoints are expanding at a blistering pace. Consumers expect a 1 to 1 cohesive conversation with a brand over every touchpoint. Gone are the days when an organization could afford to forget a user's preferences on the in-store kiosk that they held via the website yesterday. Brands simply cannot afford to offer consumer any reason to feel disgruntled. Over the next few years, look to a further expansion of digital touchpoints to include those that 12 months ago we might not have considered. And of course, content marketers must adapt to these channels with limited further investment, and this in turn fuels the need to be more efficient with what they already have. Leap in efficiency, consistency, and scalability. Generative AI capabilities will continue accelerating as organizational adoption increases. For now, organizations can expect to automate repetitive tasks, so as adoption increases, they need to scale. Personalization and content production will increase, and as trust in organizationally trained models rises, so will consumer expectations for organizations to remain ahead of the competition. A focus from the mundane to the creative needs to be applied because as yet, this is the human trait that cannot be automated. And unlocking digital experiences for everyone. As consumer channel adoption continues to accelerate, it will be critical to ensure that all can consume that content. Never before has this been more important for global organizations with a global spending power of 8 trillion USD and with 71% of people using assistive technologies boycotting a brand that doesn't make experiences inclusive. It's not just the worldwide regulations that is going to keep leading organizations compliant. Our strategy for AI is based upon four AI's. And these are ones that every organization can build into their business to accelerate AI adoption. Accelerate, accelerate content workflows, drive efficiencies into the organization's content creation, distribution, and optimization process. There are many repetitive tasks that individuals and teams attack daily. Ask yourselves, can these be automated? The answer is typically an overwhelming yes for the majority. Although it may not always seem that at first glance. Augment, augment with content governance. Consumers want a 1 to 1 cohesive conversation with your brand, and if you fail to deliver that, they'll turn to your competition. So embrace generative AI to create consistent quality and tone of voice across every digital touchpoint, and this in turn creates a unified brand experience that your customers require. Amplify. Amplify your brand reach. Make your content work harder and smarter. Generative AI can help create keyword dense content that becomes increasingly discoverable in the race to the top of search engine rankings. And adapt. Adapt to evolving needs. Succeed fast and fail fast. Let the content creation efficiencies of generative AI empower your teams to be more creative. Try things out and adapt to market shifts in a world that you never thought possible. While any organization can achieve these four A's for artificial intelligence, there are some things that you should consider to make the adoption as efficient as possible. Remember, efficiency is what it's all about and so why would adoption be any different? First of all, human control generative AI is there to help, not replace. Don't lose control of your brand or your message. Use generative AI to accelerate workflows, but ensure that human beings are ultimately responsible for the go or no go decision. Don't just look to vendors who offer everything out of the box. Remember that every organization is different, and as such, so is every business problem. Find the middle ground between out of the box and designing a custom solution that meets your business needs. Interoperability. Many generative AI capabilities are provided by GPT four, but look for the potential to connect to other providers as they appear, or perhaps your own internally built, trained, and managed models. And don't rip and replace your entire technology platform stacks simply to introduce generative AI. Remember, it's about efficiency, and as such, changes little as possible while achieving the most significant gains. Before we finish, I invite you to ask any questions that you may have. Um, here's just one final thought on the Crown Peak perspective on generative artificial intelligence. And that is balance. As organizations on the AI frontier in the world of CMEs, we have an opportunity to embrace this growing capability to truly transform how we engage with our customers, to turn them from one time transactions into lifelong fans. We can re channel the historically lost time that we now have available again, and use it to do things that stand us apart. Creative thinking. I'd like to thank you for your time today. I hope you found the content of this webinar useful as you continue on your AI journey.