Cultivating a symbiosis of GenAI and KM in the enterprise

As GenAI only continues to garner interest from businesses in a myriad of industries, its application to knowledge management offers unique opportunities. With the ability to break down knowledge silos and automate a variety of tasks within the KM lifecycle, the benefits of GenAI implementation for KM are obvious. Just as GenAI serves KM, robust knowledge management serves as a foundation for successful GenAI implementation. The meaning is clear: A mutualistic harmony between the two concepts can radically alter the way business is conducted, for the better.  

Sanjeev Sahni, senior director, product marketing at eGain, and Eric Anderson, director, product management at eGain, joined KMWorld’s webinar, Knowledge Revolution with Generative AI: Megatrends and Success Stories, to discuss the “sweet spot” of GenAI and business impact—particularly within the realm of customer service—by exploring big trends and real-world successes.  

GenAI is transforming the world, Sahni examined, and the rate of adoption is exponential.  

According to Gartner’s 2023 Survey of 1400 Executive Leaders, 80% of executives reported that the focus areas for GenAI investments are growth initiatives, cost optimization, and customer experience. Furthermore, 55% of executives reported that their organization is piloting GenAI or has gone live with solutions; and 47% of executives reported that their enterprise’s GenAI initiatives are in customer-facing functions. Undoubtedly, the focus on GenAI is top of mind for many business leaders, with an emphasis on enhancing the end-user experience without breaking the bank.  

However, there are perils for GenAI, Sahni expressed. At the top of the Gartner hype cycle, fears that GenAI may fall into the trough of disillusionment as companies fail to deploy this technology effectively are a real concern. While the productivity potential is huge, IP and brand risk, low technology transparency, and non-existent rules and regulations inspire significant fear for many companies.  

GenAI and KM are “BFFs for success,” noted Sahni, where without robust KM, GenAI remains a simple prototype. In tandem, without GenAI, KM struggles with building and maintaining knowledge in a fast-changing operation. GenAI helps accelerate the KM lifecycle through: 

• Discovery 
• Creation/curation 
• Delivery 
• Optimization 

In the same vein, a modern KM system that is implemented as a hub—such as the eGain Knowledge Hub—helps safely operationalize GenAI by delivering: 

• Trusted content 
• Controls and governance 
• Closed-loop analytics 
• Process orchestration 

Anderson then focused on a specific product offering from eGain that helps propel organizations on their journeys toward a mutual GenAI/KM architecture. eGain AssistGPT offers GenAI capabilities for agents, authors, and analysts in their flow of work. Offering out-of-the-box GenAI features with a best-practice prompt library, users can define business specific GenAI prompts, measure, manage, and optimize AI usage, as well as add custom use cases using APIs.  

Anderson further delved into real-life success stories with enterprises leveraging eGain to strike this GenAI/KM sweet spot, each with different challenges that sparked a unique solution.  

To listen to these success stories and the full discussion of striking the balance between GenAI and KM in your enterprise, you can view an archived version of the webinar here.