Knowledge managers have bravely navigated the world of corporate ontologies and taxonomies for decades—with many unaware of a parallel universe known as data. Thanks to the rapidly evolving world of GenAI, these worlds are now on a crash course, and professionals on both sides of the data and knowledge divide must prepare for impact. Hawker, industry expert and author of the Data Hero Playbook, explores the drivers of this convergence, outlines key data management practices, and addresses common roadblocks. Learn about opportunities for collaboration and what practical steps knowledge and data professionals can take to prepare their organizations for an AI-powered future together.

Whether you’re brand new to the world of taxonomy or are looking to solidify your foundational knowledge, this workshop equips you with the fundamentals to help you hit the ground running with taxonomy. Starting with a practical examination of what taxonomies are, learn how they fit into the information and content management landscape and the most common use cases, including dynamic content, search and discovery, and reporting. We go into the details of the taxonomy development process, covering how to develop your framework, selecting terms and labels, and building structures. To cap off the workshop, put your new knowledge into practice with a hands-on activity.

What happens when a digital asset management system (DAM) grows without guardrails? You get a taxonomy with over 2,000 terms—many of them redundant, inconsistent, or too vague to be useful. Martini’s case study of a federal agency’s DAM describes how she audited the taxonomy and tackled the sprawl. Learn from her practical strategies for auditing and governing taxonomies, especially for decentralized environments where user-generated tagging is common, including how to make recommendations for taxonomy cleanup and how to propose a style guide framework that will prevent future disorder.

Taxonomies and search have sometimes been considered as different, competing tools for information findability. Yet taxonomies can support search in multiple, invaluable ways. Hedden covers all the main areas in detail and with real examples, including use of synonyms, autosuggest, and search expansion and refinement using taxonomy terms. Find out too how AI can be used with search and taxonomies to provide even more tools for users and search managers alike.

Taxonomies promise to bring order to sprawling content ecosystems—but true transformation requires more than organizing terms. Large-scale efforts such as standardizing templates, information architecture, and UI patterns also demand alignment across silos. Hobbs explores how successful taxonomy and content strategy work begins with a clear, shared vision, demonstrating techniques for defining strategic intent early, securing executive buy-in, and communicating the value of change across teams. Learn how to use tools such as depth scales to break down complex problems and frame discussions about broad organizational transformation.

The process of developing a taxonomy does not often start from a blank slate; rather, it is often a process of gathering and curating terms from various internal or external sources, such as repositories, archives, translations, or industry standards. Degler describes the process of “reconciliation” in which taxonomists analyze these disparate terms in order to merge them, codify them as preferred and non-preferred, or tease them apart as unique. For example, it could be as simple as recognizing that “New York City” may have the synonyms “Big Apple” (nickname) and “New Amsterdam” (historic placename). Even with the help of AI, it is still a human skill, and an essential taxonomist skill, to identify the appropriate language for each use case.

Semantic technologies are transforming how organizations connect people to knowledge, illuminate expertise, and fuel digital transformation. Hear two case studies where taxonomy and knowledge graphs act as the backbone of smarter knowledge management. Roth shows how at Amgen, the Enterprise Web of Knowledge integrates siloed information to reveal hidden insights across products, clinical studies, and people. Two flagship tools demonstrate how lightweight, semantic-powered interfaces can accelerate learning and improve decision making across a complex biotech enterprise. Denton describes how taxonomy at Mott MacDonald has quietly evolved into a strategic framework that connects employees to content, communities, and each other through tools like Viva Engage, SharePoint, and Microsoft Search. By supporting governance, content curation, and knowledge discovery, taxonomy now powers intelligent collaboration and cultural transformation across the organization.

Taxonomists often explore content and datasets through trial, error, and recontextualization—much like learning a new board game. Gameplay mirrors how we interact with taxonomies and data structures: by experimenting with filters, facets, and search terms. Games like Wingspan, Carcassonne, and Azul reveal their underlying models gradually, just as metadata and structures shape digital experiences behind the scenes. This panel uses board games to illustrate as an example of applied information modeling, demonstrating how taxonomies are embedded in systems, often surfaced only in part, and understood through repeated interaction. Panelists explore how these models guide behavior and learning, offering insights into applied information modeling through play.

Celebrate the grand opening of the Enterprise Solutions Showcase. Enjoy drinks and light bites while visiting with conference sponsors.

Why should information architects (IA) care about taxonomies and ontologies? The link between IA and taxonomies and ontologies is not always recognized, but Levenson explains how these “collections of words” shape and enhance the work of an IA in a talk suitable for everyone who wants to understand how to leverage semantic artefacts. Learn how more advanced standards like SHACL and RDF can complement and strengthen information architecture strategies.

LLMs offer exciting new ways to support taxonomy and ontology work. Learn how to get started in three core areas: content creation, building knowledge graphs, and enriching existing data. LLMs can generate structured content from unstructured input; they can identify key concepts and relationships (subject–predicate–object triples), and can enrich existing controlled vocabularies by suggesting synonyms, related terms, and hierarchical relationships. Hill brings practical tips and real examples that can be applied straight away with no technical background needed and also covers the essential skills for taxonomists to evaluate quality and identify where human input is required to ensure smooth integration of AI into workflows and products.

Application profiles provide a framework for structuring information related to a particular application. These can include two types of vocabularies—schema and value vocabularies. Schema vocabularies such as SKOS, RDFS, Dublin Core, FOAF, and Schema.org specify the properties and attributes related to the application, while value vocabularies (ranging from simple controlled vocabularies to taxonomies and ontologies) specify the valid instances for those properties and attributes. Busch provides an accessible overview of how these two vocabulary types combine in application profiles in order to deliver consistency across structured content.

It is widely held that AI models and tools deliver significantly more reliable results when they incorporate as input from factually grounded data with explainable origins and explicit meaning, such as from a knowledge graph. Ontologies which describe valid relations and data types are one element; taxonomies are another, as they supply terms and categories. Drawing on real-world case studies from the pharmaceutical industry (and other sectors), learn more about how taxonomies fit with ontologies and knowledge graphs to provide meaning and flexibility to enterprise data models, using for example the gist upper ontology and the SKOS taxonomy standard.

As AI-powered systems demand more precise and scalable knowledge models, traditional taxonomy management struggles to keep up. Explore how organizations can use AI not just to build, but to audit, refine, and evolve taxonomies continuously. Drawing on real-world insights from the Inter-American Development Bank and advances in tools like Graphwise’s Taxonomy Advisor, hear how AI can detect inconsistencies, enforce editorial standards, and suggest improvements—creating a feedback loop where improved models fuel better AI outcomes, and those outcomes guide further model refinement. Blumauer demonstrates a “recursively self-improving” approach that combines automated suggestions with expert validation, reducing manual effort while improving quality and consistency. Mora and Arakaki discuss practical workflows, technical considerations, and the critical role of the human in the loop in turning AI from a static assistant into a dynamic partner in taxonomy governance.

Zichettello and Egan describe how taxonomies and ontologies underpinned improvements in knowledge management for Honda. The company was faced with challenges such as content stored in siloed systems, inconsistent terminology and metadata, unstructured content, and missing context, and a semantic foundation became a vital component of good knowledge management. Learn about the taxonomy and ontology development process, from initial discovery and content analysis to design and evolution through the coordination of the semantic modeler and domain expert. Discover how to use industry standards, best practices for taxonomy and ontology design, and semantic models to drive scalable, sustainable knowledge management solutions.

Celebrate the grand opening of the Enterprise Solutions Showcase. Enjoy drinks and light bites while visiting with conference sponsors.

Kon, a global leader in enterprise-grade language AI, explores how organizations can effectively harness the power of AI to transform KM, accelerate decision making, and unlock new levels of performance across sectors. From transforming financial institutions with productivity and efficiency gains to streamlining clinical workflows in healthcare and supporting secure, high-stakes applications in the public sector and national security, he highlights real-world use cases and lessons learned from the frontier of AI deployment. Kon shares insights into how enterprise-ready AI systems can be customized, governed, deployed, and scaled with confidence, helping to realize a world where technology commands language in a way that’s as compelling and coherent as we are. He shares his views of the landscape and frontier of AI progress with the goal of solving cutting-edge scientific problems, making research breakthroughs with continuous learning, empowering different perspectives that ensures responsible innovation, and building a body of knowledge for all.

GenAI and intelligent agents are fundamentally transforming the landscape of enterprise operations by enabling unprecedented levels of automation, personalization, and efficiency. These technologies are breaking down traditional data silos, allowing for seamless integration and real-time access to information across various departments. In finance, for instance, GenAI is revolutionizing risk management and compliance by automating complex processes and providing actionable insights from vast datasets. Selz walks the audience through a step-by-step process of how to set up and guardrail the system to make it enterprise-ready. He focuses on lessons learned, pitfalls to avoid, and how success of such an initiative can look like.

There is no question that GenAI has reignited interest in KM. Gartner predicts that 100% of GenAI virtual customer assistant and virtual agent assistant projects that lack integration to modern KM systems will fail to meet their CX and operational cost-reduction goals by 2025. As businesses experiment with GenAI, they are realizing that robust KM is foundational to its success. Roy discusses how KM and GenAI can accelerate and ensure mutual success, creating transformational business value at warp speed. He shares stunning success stories from clients. Get insights and ideas for your enterprise.

Learn how leading organizations are revolutionizing their knowledge management with GenAI Workflow – and achieving measurable ROI. See how companies are leveraging GenAI and orchestrating the lifecycle of content creation through depreciation. Discover strategies that are transforming real world organization's approach to KM.

AI needs structure to reason, yet many enterprises skip the foundational work of taxonomy and ontology when deploying LLMs, semantic search, or knowledge graphs. McLean shows how missing knowledge models, inconsistent terminology, and a lack of traceable source stall AI efforts. She outlines tactics to align taxonomies with business goals, identify structural gaps, and use knowledge modeling to boost retrieval precision and reduce hallucination. McLean makes a clear case: Knowledge management is not outdated, rather, it is essential infrastructure for trustworthy, context-aware AI. Competitive advantage lies in managing existing knowledge and making it usable by both humans and machines.

GenAI and agentic AI are rapidly changing the way taxonomy and ontology practitioners work, and it's clear that embracing AI is becoming crucial for success. Clarke explains how taxonomists can upskill with AI tools in order to drive productivity and quality gains for their organization. Explore LLM-based information extraction processes and see a demonstration of how to automatically expand and enrich the structured knowledge captured in taxonomies and ontologies.

When Expedia set out to unify its global content operations, it found the answer in flexible, ontology-driven taxonomies. Learn from Bradley and Mehta how Expedia partnered with TopQuadrant to scale taxonomy management across teams, boost metadata consistency, and elevate content governance. The work improved search filtering, enabled automated tagging, and made partner content scoring faster, smarter, and more reliable.

Successful taxonomy projects depend on more than good planning. They require shared understanding, clear communication, and well-defined scope and expectations. Schweizer shares insights from 20 years of taxonomy, schema, and data projects. Learn how to spot common failure points, and how to avoid them with strong project sponsorship, project management, and stakeholder engagement. Monsalve and Duncan examine how evolving language around taxonomy—terms like “enterprise,” “system,” “framework,” and even “taxonomy” itself—can cause confusion before a project even begins. Explore shifts in vocabulary in the last 20 years and their impacts on communication, alignment, and adoption. Leave with concrete strategies to communicate clearly and effectively, get buy-in, avoid scope creep, manage expectations, and boost your taxonomy's chances of adoption and success.

Taxonomy and data governance share more than just a focus on structure—they both aim to transform fragmented information into valuable, usable assets. This session explores the intersection of enterprise taxonomy work and data governance, highlighting how skills in metadata strategy, classification, and stakeholder alignment transfer across domains. Fulvio shares her experience being asked to start a data governance team for Disney, describing data governance basics from a taxonomist's perspective, how they are similar, and offering tips on how to make a career or role shift. Rodriguez shares how HealthStream uses taxonomy to transform inconsistent, scattered data into unified, valuable assets. Through real-world examples, Rodriguez highlights the role of cross-functional collaboration in creating a gold-standard taxonomy—especially for challenging user profile data.

Join us to celebrate the 20th edition of Taxonomy Boot Camp by exploring original conference abstracts from the first edition in 2006, reflecting on how the discipline has evolved. Thought leaders will share time capsule predictions for the next 20 years of taxonomy work, offering insights into future challenges and opportunities. Audience votes agreeing or disagreeing with each prediction are likely to spark lively debate about whether our AI overlords are taking over. This special closing event features a special cake-cutting ceremony, honoring our community’s growth and achievements.

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