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Knowledge Engineering, Knowledge Management and Chatbots

Recorded - available as on demand webcast

How AI leverages knowledge assets for customer experience, conversational search, retrieval and commerce

There are a lot of questions about how artificial intelligence supports knowledge management and how knowledge management supports AI programs. On the one hand, chatbots are a channel to knowledge, content and data and therefore needs to be correctly structured, tagged and curated to support a set of use cases. On the other, AI can be used to improve content access and retrieval through semantic processing.

In either case, fundamental information management principles still apply:

  • the source of data and content needs to be reliable;
  • the information accurate and suited to the application;
  • a framework for organizing the information – whether embedded in the AI program or developed outside of it – needs to be applied.

While some programs can begin to make sense of messy and unstructured data and content, the data cannot be of poor quality. In the case of chatbots, semantic processing of user questions is applied to understand the user’s objective with a rich enough set of signals and cues to allow the bot to return a meaningful answer. Machine learning can, in some cases, derive dialog structures from large sets of chat log data, however this still needs to be cleansed and normalized by a knowledge engineer.

In this executive roundtable, our panel will explore foundational concepts of knowledge engineering that need to be considered in your AI project.

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Seth Earley
Seth Earley
Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.

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During our webinar, "Omni-channel Virtual Assistants - The Next Frontier in Voice and Text for Customer Service guest speaker Chris Featherstone, who leads business development for AI and speech recognition services at Amazon Web Services (AWS) and Seth Earley, CEO of Earley Information Systems (EIS) discussed ways to design omni-channel virtual assistants to optimize their use across voice and text. When supported by an appropriate information architecture and designed with a deep understanding of the customer, virtual assistants can access enterprise knowledge efficiently, saving time and money. The key to success is to structure the underlying information so it can be retrieved and used by any channel, including humans, to deliver the responses that customers need. Here's a recap of the conversation.