AI for KM: Unlocking the future with a human-centric focus

Through our recent “Emerging Technologies for Knowledge Management” survey, the American Productivity & Quality Center (APQC) found that KM is increasingly taking center stage as a valuable partner and ally for digital transformation. For example, more than a third of our respondents said that their KM teams are very or extremely involved in their organization’s digital strategy. Almost all respondents (95%) said that KM teams have at least some involvement. 

See: Level of involvement KM teams have in an organization’s digital transformation strategy, road maps, and implementation

KM’s deep involvement with digital strategy means that KM teams are often well-positioned to play a foundational role in the implementation of new technologies such as AI. After reviewing some of our key findings about the current state of AI for KM, we focus on change management and partnerships with IT as two critical success factors for AI implementation.

Current state adoption and use cases for AI in KM

Exploring, adopting, and rolling out AI are significant priorities for many KM teams. For example, when we asked respondents to identify the technologies they think will be most important to KM during the next 3 years, four of the five technologies that respondents identified were related to AI:

• AI to recommend content or knowledge assets (49%)

• Generative AI (GenAI) to create new artifacts and content (37%)

• AI to identify and surface expertise (29%)

• Intelligent/AI-driven search (25%)

• Team collaboration/digital workplace apps (25%).

KM teams expect that these tools will bring a wide range of benefits to KM. More than a third of our respondents said that AI will help reduce redundant and siloed work and streamline or simplify processes. Nearly another third believe AI will provide better decision making, improve taxonomies and content management, and improve information management overall.

See: Top five expected benefits of AI/generative AI deployment for KM

Given the benefits that respondents expect from AI, it’s no surprise to see adoption growing across industries. Specifically, we found that 44% of our respondents are either piloting, implementing, operating, or optimizing AI, while nearly the same percentage (42%) say they are evaluating these technologies. By contrast, only 15% of respondents are not considering AI at all.

AI and GenAI use cases largely the same—for now

Our respondents don’t see radically different use cases between traditional AI and GenAI in KM. For example, respondents said that automating data analytics was the top potential use case for both forms of AI. It makes sense to see analytics as a top use case: KM teams can use analytics for a wide range of different purposes, whether to discover trends in how tools are being used, assess completion rates for training, make data-driven decisions about content, or something else. Respondents are also looking to both AI and GenAI to help KM teams personalize content, auto-tag or auto-classify content, and improve customer support.

KM teams do see a unique role for GenAI in creating new content (a use case for 47% of respondents), which is something that only GenAI can do. It is likely that use cases will grow more diverse between the two technologies as GenAI becomes more widespread and KM teams become more familiar with the technology.