The APQC Blog

Knowledge Management, Experts, and AI

Knowledge Management, Experts, and AI

In today’s landscape, the airwaves resonate with discussions about Artificial Intelligence (AI) (see Emerging Technologies for Knowledge Management Survey Report | APQC) – and rightfully so. As someone who embraces emerging technologies, I’ve witnessed how they elevate knowledge management (KM) efforts. From the early days of portals and expertise location to the collaborative power of wikis and shared spaces, technology has consistently given KM a much-needed boost.

I recently had an enlightening conversation with Jean-Claude Monney Jean-Claude Monney | LinkedIn, a long-time friend and colleague of APQC. Jean-Claude shares our belief that AI isn’t just impacting KM; it’s reshaping the entire business landscape. His mission? To demystify AI for knowledge managers, business leaders, and beyond. His wealth of experience and expertise is already leaving a mark on the intersection of AI and KM.

During our discussion, we delved into the role of experts. How will they fit into the AI equation? The possibilities are vast: knowledge creation, capture, and seamless transfer, to name a few. Jean-Claude reminded me of APQC’s research from a decade ago. I did a quick review and it provided me with a great (and forgotten) context for thinking about experts and what they know.   

Here's a quick overview of the research, “How Smart Leaders Leverage Their Experts” How Smart Leaders Leverage Their Experts: Strategies to Capitalize on Internal Knowledge and Develop Science, Engineering, and Technology Expertise and the model developed from the findings.

  1. Research Focus: The research centered around how smart leaders harness their experts. During that time, industries grappled with shortages of experts in the scientific, technology, engineering, and mathematics (STEM) fields. This challenge remains relevant today. Rather than rehashing traditional STEM recruitment efforts, APQC posed a novel question: How can organizations leverage existing experts while accelerating learning for new hires and mid-career employees?
  2. Key Questions Explored: We focused on several critical focus areas:
    • Where do scientific, technical, and engineering organizations face expertise gaps?
    • What drives the urgency to close these gaps?
    • How do organizations bridge the knowledge divide between experts and mid-career employees?
    • How does this differ from approaches used for novices and newcomers?
  3. Identified Knowledge Gaps: Our research highlighted three essential knowledge gaps:

The model below was created from the research and gives more context to how and when to enable using AI.

Creating New knowledge chart

Remembering the research findings and model prompted me to contemplate how artificial intelligence (AI) could bolster our efforts, particularly in accelerating the creation of new knowledge. Even a decade ago, research indicated that technology and markets are evolving at breakneck speed, resulting in a scarcity of both new knowledge and expertise. 

When we surveyed our audience about their reasons for seeking out and cultivating experts, the prevailing responses centered around emerging technologies and shifts in product compositions—not merely the aging workforce or the demands of globalization and expansion. The expertise required by these organizations cannot be seamlessly transferred from departing experts; instead, it must be rapidly developed, sometimes by tapping into talent and content from other disciplines.  Given observations from today’s breakneck speed of business, the challenges have only gotten more daunting and the need for tapping into expertise is needed even more.

Amidst the ongoing buzz, experiments, and real-time AI applications, we must not overlook the essential human factor. In my view, AI truly “sings” when combined with what APQC chairman, Dr. Carla O’Dell, aptly termed “two AIs”: Artificial Intelligence and Appreciative Inquiry. Carla posits that AI’s potency amplifies when paired with appreciative inquiry—a methodology for uncovering organizational strengths and leveraging them. I propose that when these two forces converge with the expertise of your professionals, a third AI emerges: “Amazing Insights.”

These remarkable insights materialize when experts harness AI’s capabilities, resulting in novel knowledge creation beyond our previous imaginings. Consider the following examples of how experts can leverage AI’s power:

  1. Training the Machines: Experts can fine-tune AI models, ensuring they learn effectively and adapt to specific contexts.
  2. Evaluating Outputs: By critically assessing AI-generated results, experts refine and enhance the quality of outcomes.
  3. Content Enrichment: Experts infuse AI-generated content with their domain knowledge and experiences, adding depth and context.
  4. Innovative Thinking: Most crucially, experts contribute fresh perspectives to emerging concepts, bridging them with established principles and foundations.

In the dynamic interplay between human expertise and AI, we unlock the potential for groundbreaking insights that lead us into uncharted territories of new knowledge. As we navigate this synergistic landscape, both seasoned experts and the knowledge management programs that bolster their efforts must seize the opportunity to capitalize on their collective wisdom. Those who work smarter, fearlessly embracing collaboration with AI, are poised for success. 

Explore APQC's Emerging Technologies for Knowledge Management Collection for the latest research and thinking on the role of new technologies in KM.