Upgrade to a Platinum Pass for your choice of two preconference workshops or access to Taxonomy Boot Camp, a co-located event with Enterprise AI World 2023. Workshops are also separately priced.

Join us for the Enterprise Solutions Showcase Grand Opening reception. Explore the latest products and services from the top companies in the marketplace while enjoying drinks and light bites. Open to all conference attendees, speakers, and sponsors.

Upgrade to a Platinum or Gold Pass for extended access to KMWorld2023, Enterprise Search & Discovery, Text Analytics Forum and Taxonomy Boot Camp, a series of co-located events happening alongside Enterprise AI World 2023. See the registration page for details.

Stop by the Enterprise Solutions Showcase after a full day of stimulating sessions to mix and mingle with other conference attendees, speakers, and our conference sponsors.

Our organizations have had a roller coaster ride with digital transformation over the last few years and most have embraced online work platforms. An organization's culture is created in the conversations between its members. But how do our enterprises encourage their people to interact, collaborate, and connect as they used to in a corporate building? How do they support learning, encourage deeper conversations and human relationships, and embrace and foster innovation? Speakers address these issues, discuss reclaiming conversations, share insights and experiences, and provide lots of tips and ideas for supporting KM joy, enhancing the flow of information and knowledge, and building stronger, more collaborative teams within the enterprise.

A long time KM practitioner and Deloitte’s Knowledge Capital Practice Lead, Eyal discusses how organizations can move beyond the tactical version of KM as a storage repository and view knowledge as source of growth for the organization and knowledge as its most important asset. He shares how connecting knowledge within the flow of work can drive better outcomes and benefits. Gain insights and ideas into how to get into the mindset to help you capitalize your organization’s knowledge.

Generative AI has real practical implications in search applications. This presentation discusses and demonstrates how generative AI, large language models (LLMs), and vector search can be used to create more natural and conversational search experiences, generate more comprehensive and informative search results, and personalize search results to individual needs and interests.

With the advent of advanced conversational AI, the cycle of learning through dialogue is digitalized. This AI not only serves as an interpreter, bridging the gap between novice queries and expert content, but also ensures continuous accessibility of vital institutional knowledge. Moreover, it offers organizations the desired control and oversight, providing insights about conversation effectiveness. This technology thus opens up opportunities for unlocking and safeguarding knowledge within organizations.

Machine learning, algorithms, and AI are all around us but what’s happening in our organizations? Hear insights from our expert on organizational and strategic transformation with scientific expertise in behavioral, cognitive, and learning systems, as well as a lifelong passion for synergizing human and machine intelligences. He shares real-world examples, industry trends, AI challenges and prepares us for the next steps in the uncertain future of AI. He will definitely get you thinking about how AI can create value in your organization.

AI enhances and amplifies human expertise, makes predictions more accurate, automates decisions and processes, optimizes employees’ time to focus on higher-value work, improves people’s overall efficiency, and will be key to helping humankind travel to new frontiers and solve what feels now like insurmountable problems. But—we’ve got to get AI right … Can you trust the decisions made by an AI? Just because a decision is made by an AI does not mean that the results are morally or ethically sound. Our popular and experienced speaker introduces listeners to very tangible and holistic steps that organizations and practitioners across diverse roles can take to nurture and develop truly responsible AI. Get lots of tips and ideas as she shares exciting and illuminating stories of responsible AI.

Evolution tends to reduce the energy cost of decision making, so is there a danger that growing use of machine learning (ML) will make us lazy? ML is only as good as its training datasets, so will growing use of ML increase the prejudices of the past at the expense of new ways of thinking? Diversity issues are already arising with ML in large companies. It enforces rather than disrupts existing ways of thinking, which is something we may need to do to deal with our uncertain and changing future. Will we end up meeting ML halfway? It will appear more intelligent than us because we have allowed our intelligence to be reduced by using it. Remember, our sense of smell is far worse than that of our immediate ancestors: If you don’t use something, it atrophies! What type of protocols do we need to put into place to ensure that the above-mentioned dangers do not come into play? How do we use ML to augment human intelligence and decision making rather than talking about replacing it? Our creative thinker and popular KMWorld speaker shares his insights and challenges our future with ML strategies and possibilities.

When search technologies moved from the web to the enterprise, the incorporation of knowledge models (taxonomies and ontologies) provided more accurate and complete search results. Now that we are looking to bring LLMs (large language models such as ChatGPT) and generative AI from the public web to inside the enterprise, there is again a role for knowledge models to provide better results. The subject domain and context can also make a difference. The advantages of combining a taxonomy/ontology with generative AI and limiting it to a subject domain is explained and demonstrated using real-world applications.

Our leaders in the developing AI field share their insights, predictions, and real-world stories about what’s happening in our world today and tomorrow. It is followed by Communities of Interest in the hotel bar; meet the speakers for more discussion! NICE discusses using Generative AI to help agents and consumers elevate knowledge and provide "conversational" responses to prompts that are trained on a customer's knowledge systems (their expert site). Kyndi shares how an enterprise-grade generative AI answer engine can optimize knowledge management and transform the way business users find answers.

AI and the internet are transforming our understanding of how the future happens, enabling us to acknowledge the chaotic unknowability of our everyday world. Back when we humans were the only ones writing programs, data looked like the oil fueling those programs. But now that machines are programming themselves, data looks more like the engine than its fuel. This is changing how we think about the world from which data arises, and that data is now shaping as never before. We’ve accepted that the intelligence of machine intelligence resides in its data, not just its algorithms—particularly in the countless, complex, contingent, and multidimensional interrelationships of data. But where does the intelligence of data come from? It comes from the world that the data reflects. That's why machine learning models can be so complex, we can't always understand them. The world is the ultimate black box. Weinberger looks at the implications of this for people who work with data, those who share knowledge and insights inside and outside the enterprise, and those looking for ways AI can assist their organizations in future success.

How do companies deliver AI capabilities across their organization? How can an organization build and leverage AI tools without having to develop multiple intelligent technologies for different applications? What’s the best way for organizations to build and evolve the large datasets needed to drive the most powerful, emerging AI tools? Centralizing AI capabilities into an enterprise data hub with reporting tools and advanced integration capabilities allows companies to leverage their investments more fully, bringing new and evolving AI capabilities into play quickly by leveraging a common data hub to build rich machine learning models. For KM, this means organizations can build powerful new capabilities. Hear how organizations are doing this today!

Hoeffel delves into the realm of KM and explores how generative AI can revolutionize the way organizations capture, organize, and utilize information. Discover how LLMs and AI can enhance knowledge discovery, automate content generation, and improve decision-making processes. Through compelling demos and practical guidance, gain insights into leveraging generative AI to unleash the full potential of search and KM efforts. Discover how this powerful combination can drive innovation and propel your business forward.

Discovery is a key factor for knowledge management, and helps people to find the right information at the right time. Knowledge graphs enable simple, intuitive discovery, but can be time-consuming to create and manage. Today, we are at the cusp of a new era in improving content discovery with automation. Traditional automation tools—such as auto-tagging, auto-classification, and inference-based rules—can now be used together with LLMs to make knowledge graphs easier to create and more powerful in powering content discovery. Get insights into how these new approaches can provide information of higher quality, accuracy and reliability, powering better content discovery and ultimately providing more effective use of organizational knowledge.

AI is a rapidly growing field that has the potential to revolutionize many industries. However, many people are still unsure of what AI is and how it can be applied to their environment. Earley shares new solutions to generative AI problems and compelling results justifying the use of a knowledge architecture in the enterprise. He discusses real-world examples from a life science firm that eliminated hallucinations. The company illustrated to management that their model was 83% accurate with a knowledge architecture vs. only 53% without and created a system that answered “I don’t know” when information was not part of the training content.

Hype or no hype, organizations have seen a significant spike in capabilities around advanced knowledge engineering and AI abilities thanks to advancements in higher computing and abundance of open source solutions such as OpenAI (ChatGPT), and other large language models (LLMs). Data fabrics are emerging as the most effective means of integrating knowledge throughout the enterprise, and experts agree these fabrics are the future of enterprise analytics and AI. However, many organizations continue to face challenges in realizing the promise of AI. For many organizations, one of the top reasons why AI projects get stalled, despite leadership support, is the lack of clear strategies for sourcing the right knowledge and data that AI requires, ultimately resulting in their inability to explain how AI arrived at a certain decision. Using real-world examples, our speakers share their experiences, ideas, and applications of knowledge graphs and semantics in AI, as well as the benefits they offer to organizations seeking to leverage the power of enterprise AI. Join this fast-paced session for lots of tips and ideas.

GenAI is the next make-or-break moment for KM leaders. However, GenAI alone won't reduce the significant challenges associated with content governance. Join this session to learn how search augments AI’s capabilities. Uncover 11 cutting-edge machine learning models (including generative answering) used by over 600 leading enterprises to deliver world-class digital experiences every day.

Rasmus examines the techniques employed under the hood by generative AI tools such as ChatGPT and the new Bing. He helps us understand why these tools still require human review of the outputs and why their art and language are racing not toward innovation but to mediocrity. He shares insights about the future of AI that look at the social, political, and economic factors that will determine how the technology will evolve—or not—in the future.

ChatGPT, Siri, Alexa, and Cortana are not knowledge managers or subject matter experts. Yet we use them regularly to quickly find answers—and often with little concern for the validity of the answer or its sources. In the explosive expansion of the data universe where fast and frictionless access to the right information makes the difference between success and failure, AI technology is being employed—sometimes unknowingly but increasingly as a desperate attempt—to help people do their work more efficiently. But often it results in havoc, confusion, and distraction: While the AI may be reaching wide and working fast, it is also indiscriminately creating questionable outcomes from the vast expanses of low-quality or outdated data. Enter the Guardians of True Knowledge: protectors of data, content, and information quality—using their skills and tools to expand the relevant “known knowns” across the content services realms. They have learned that to tame the AI, they must feed it with the right information—yielding extraordinary outcomes for the organizations they serve. Focused on achieving high knowledge productivity outcomes, this talk explores the inevitable adoption of AI in the way we produce outcomes and homes in on the tools, platforms, and strategies for the enterprise of the future to tame both the data and the AI to deliver the right outcomes. Hear about the risks of shadow-AI and of AIs producing useless/risky outcomes because the AI has access to too much data of little value.

Hear from current AI developers and experts about their thoughts and visions for the future of enterprise AI. Kalaci illustrates the use of AI for fast translations for law firms and other organizations around the world. Roy discusses the exciting new opportunities generative AI has created to elevate and automate customer service and KM. He shares practical customer service use cases for generative AI and looks at how it can be leveraged for KM.

The age of generative AI is changing the nature of work, and nobody is more impacted than the knowledge manager. While this transformation may seem overwhelming at first, GenAI offers knowledge managers an opportunity to play a mission-critical role in the automated future. Former knowledge manager and AI leader Sedarius Tekara Perrotta explains why knowledge management is evolving into a critical and strategic role over the next 2–3 years and provides specific advice on how to position KM expertise to take advantage of one of the biggest business trends in decades.

Join members of the KMWorld community as they provide insights, inspiration, key ideas, and innovations shared at this year’s conferences as well as what our panelists are seeing within the rapidly changing field of KM.