Sessions

With the explosive popularity of ChatGPT, organizations are paying increased attention to the implementation of AI technologies and the use of large language models (LLMs), chatbots, semantic search, and recommendation systems. Making these solutions work for the enterprise can deliver competitive advantage and open up new solutions and business opportunities that were never before possible. The possibilities are endless, but so are the opportunities for error, risk, and project failure on both a technical and operational level.

Guillermo and Chris have collectively been making AI work at an enterprise level for the better part of the last decade. Long before it was the hot new trend, they were leading organizational transformation. In this talk, they will provide practical, proven guidance for leveraging your organization’s information architecture on your path to your AI-based solution. As an introductory step, we will provide EK’s unique view of Information Architecture featuring the presentation, navigation, structure and storage of information. This helps with better decision making, improved productivity, and the ability for people to discover information and use it in a meaningful way.

From there, we will help develop AI Literacy by explaining some basic topics and concepts related to AI. This will enable attendees, regardless of technical acumen, to understand the basic components of AI, the required resources, and skill sets in order to leverage AI safely and ethically. As part of this process, we will discuss the “feedback loop” between IA and AI and how each impacts the other.

In the main section of the talk, we will present a series of practical, easy-to-follow steps that will help prepare your content and data for future AI solutions while leveraging your current information architecture. Besides detailing and explaining the step, we will provide real world examples of how we’ve implemented the step in our past client work.

Examples of topics we will discuss include:

• “Chunking” your content in a logical manner to enable optimal performance with AI tools

• Maximizing the use of taxonomies to ensure consistency in data

• Introducing ontologies and semantic technologies to model your knowledge domain

• Enabling effective governance to ensure that IA remains aligned to your organizational objectives

In conclusion, we’ll share an AI-readiness checklist that you can use to plot your successful journey to AI mastery.