Generative AI and KM for Customer Service

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.

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