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Published on: February 13, 2024
Author: Anand Subramaniam


ARTIFICIAL INTELLIGENCECUSTOMER SERVICEKNOWLEDGE MANAGEMENT


GENERATIVE AI AND KM FOR CUSTOMER SERVICE: BFFS THAT ASSURE MUTUAL SUCCESS

Generative AI has reignited interest in knowledge management (KM). KM is not
only a BFF for gen AI but a foundational one at that!


GEN AI HELPS KM

Gen AI accelerates each step of the KM lifecycle on a modern knowledge platform.

 * Discover: Identifying likely questions is the first, often-ignored, step to
   an effective knowledge base. Gen AI can extract questions from interaction
   history using best-practice, contextualized prompts in the knowledge
   platform.
 * Create/curate: Gen AI can draft knowledge content, using long-form, complex
   documents, and other enterprise sources. It can adjust content for brand
   voice, interaction channel, and consumer persona. Finally, it can propose
   knowledge taxonomy based on question patterns and user profile.
 * Deliver: Enterprises have boatloads of documents with “correct” content, but
   they are not “consumable” by users. With an irate customer on the line, no
   agent wants to read a tome! Gen AI generates consumable answers, referencing
   multiple knowledge articles and documents.
 * Optimize: Knowledge must be measured and managed for business impact. Gen AI
   identifies knowledge gaps in accuracy and ease-of-use, suggesting
   alternatives for improvement.


KM HELPS GEN AI

Gen AI can transform business, but it also poses significant risks. Among them
are hallucination, loss of trust in answers and in the technology itself,
knowledge fragmentation, and compliance risks. A modern KM system implemented as
a hub—like the eGain Knowledge Hub—helps safely operationalize gen AI by
offering:

 * Trusted content: KM can ensure that correct data and content are used to feed
   and train gen AI. Without this foundation, the initiative is likely to fail
   with disastrous consequences for the brand.
 * Controls and governance: A modern knowledge hub comes with controls to
   determine which queries to process with gen AI and which ones not to. The
   knowledge manager can control its “creativity,” as the situation warrants and
   configure additional accuracy checks.
 * Closed-loop analytics: KM provides insights and actionable recommendations on
   the use, effectiveness, and improvement of gen AI actions.
 * Process orchestration: Gen AI is an exciting building block of KM, but not
   the only one. A knowledge hub also includes other AI technologies like
   reasoning and machine learning, plus critical components such as content
   management and conversational guidance. The hub orchestrates these
   capabilities to deliver effective journeys to agents, business, and
   customers.


CONCLUSION

The symbiosis between Gen AI and KM is powerful. Without robust KM, Gen AI
remains a prototype. Without Gen AI, KM struggles with building and maintaining
knowledge in a fast-changing operation.

Download PDF


RELATED LINKS

 1. The Best Use Cases for Generative AI in Digital Customer Service
 2. Harnessing generative AI for customer service: KMWorld webinar
 3. Generative AI For Customer Service: Best Practices For Success
 4. Blog: 10 Use-Cases for Leveraging Generative AI for Better CX and AX (Agent
    Experience)
 5. Try generative AI for customer service
 6. eGain Knowledge Hub
 7. eGain AssistGPT

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