Impact of AI on KM Strategy: A Two-Way Street

The Rocket Value Realization Dashboard and AI Traffic Controller connect every AI initiative to measurable business impacts. “Too often, KM initiatives have not been able to prove that they have produced better business outcomes,” commented Palermo. “Among the metrics we use are mean time to resolution, satisfaction ratings, and cost savings.” Initially focused on IT service issues, NewRocket now implements ServiceNow solutions for processes throughout the enterprise, including CRM, HR, and a broad range of customer service management functions.

AI has elevated the use of self-service by allowing conversational interactions and more intelligent automation of service tickets. In addition, it can improve the quality of the knowledgebase on which it relies, for example, by looking iteratively at patterns of interactions and case logs and by automating the creation of new knowledge assets. “Resolution of an incident might require access to four or five other incidents,” Palermo pointed out. “AI excels there, quickly seeking out information across sources and then generating responses. There is a human in the loop to assess it initially, but as we tune the model more and more, new knowledge is getting accepted into the knowledgebase.”

“For the past 20–25 years KM was often an afterthought,” commented Yus. “Only companies that needed specialized knowledge like R&D or regulated industries provided the attention and budget needed for fully implementing KM.” He believes that the advent of AI will be a catalyst for knowledge to be managed more pervasively in enterprises. “KM and AI will become one and the same,” according to Yus. “Within a few years, companies will realize that to compete, they will need to focus time and attention on KM, provide a budget, and develop a company-wide strategy for a fully integrated AI/ KM capability.”

AI’s impact on KM strategy is omnipresent and includes recognizing its potential, particularly for enhancing existing knowledgebases and automating existing processes, while acknowledging the critical role of accurate, clean data to which organizations have access. Consider it a two-way street when setting organizational strategies.