The Next Evolution of KM: From Service Provider to Enterprise Capability
Suppose a critical employee with expert knowledge has announced her retirement after 20 years with your organization. What happens next to ensure her critical knowledge is retained?
1. A centralized KM team is responsible for scheduling interviews, capturing knowledge, and preserving as much of her expertise as possible before she leaves.
2. The announcement triggers an established knowledge transfer process: Her manager establishes knowledge transfer priorities, successors begin mentoring with her, critical processes are documented, and her expertise is incorporated into training and knowledge resources.
In the second scenario, the KM team designed the framework, methods, and governance behind the knowledge transfer and capture processes without having to perform every step. That difference illustrates the current evolution of KM from a specialized service delivered by the KM team to an enterprise capability embedded throughout the business.
Have We Been Asking the Wrong Question?
This transition has changed how organizations think about KM’s role. Rather than focusing primarily on how to structure the KM team or where it sits on the org chart, there is now more interest in how to get knowledge work embedded in the day-to-day flow of the business.
In fact, when APQC conducted its 2025 KM benchmarks and metrics research (apqc.org/resource-library/resource-listing/2025-km-program-benchmarks-andmetrics-survey-report), we stopped asking whether KM was centralized, decentralized, or hybrid. Instead, we asked about the scope of KM and whether the capability supports the enterprise, supports a functional/business unit, or leverages a federated model level.
Chart: KM Program Organizational Model
‘Centralized’ Does Not Necessarily Equal ‘Enterprise’
APQC’s benchmark surveys help illustrate an important distinction between the scope of a KM program and how it is organizationally structured. Our research compares enterprise-level and local programs separately from its analysis of centralization. That’s important because some understand the terms “enterprise KM” and “centralized KM” to mean the same thing. They don’t.
An enterprise-focused KM program looks at the knowledge needs of the entire organization. A centralized model describes where KM resources, responsibilities, and decision making reside within the organization.
You can therefore have a strong, central KM team and still distribute KM responsibilities throughout the enterprise at a more localized level. Or, you can have embedded KM resources and still operate with enterprise standards and governance. Simply having a corporate KM team does not automatically mean the program is truly enterprise-focused.
Why KM Is More Important Now Than Ever
KM activity 20 years ago primarily centered on capturing and storing knowledge. The discipline has steadily expanded to cover communities, collaboration, expertise, and knowledge sharing.
Today, knowledge is embedded in almost every major enterprise transformation, including AI and digital initiatives, business process reengineering, and learning and workforce transformation.
APQC’s 2026 KM priorities and trends research (apqc.org/resource-library/resource-listing/2026-knowledge-management-priorities-and-trends-survey-report) underscores the importance of KM in supporting business goals around technology, productivity, and strategic capability.
Respondents focused on elevating KM as a strategic business partner make up 31% of those surveyed. AI in particular has become a forcing function because it has brought long-standing KM goals such as trusted knowledge, quality content, expertise, findability, reuse, and governance into the spotlight. Today, these factors are no longer mere housekeeping issues—they determine whether AI can deliver reliable answers that employees trust.
The need for integrated operating models that connect KM, data, and AI has never been greater as organizations seek to align governance, workflows, and collaboration across functions that increasingly depend on one another.