2026 KM Priorities & Trends | Executive Summary
What KM leaders need to know about AI readiness, enterprise knowledge strategy, and the future of knowledge management.
Knowledge management enters 2026 with stronger visibility and higher expectations. APQC’s research shows KM is being pulled closer to AI adoption, operational efficiency, productivity, and digital transformation, even as many programs are still maturing their systems, governance, and measurement practices.
How is AI changing knowledge management in 2026?
AI is changing knowledge management by making trusted, structured, and reusable knowledge more critical to business performance. Incorporating AI and smart technology is the top KM priority for 2026, selected by 49% of respondents.
The implication is straightforward: AI can accelerate KM, but it also exposes weaknesses in content quality, governance, taxonomy, and ownership. KM teams should start by identifying business-critical knowledge domains and preparing those assets for AI-enabled search, recommendations, and reuse.
What are the top knowledge management priorities for 2026?
The top KM priorities for 2026 are AI adoption, critical knowledge identification, KM maturity, collaboration, and participation. These priorities show that organizations are trying to modernize KM while still strengthening the fundamentals that make knowledge easier to find, trust, and apply.
For leaders, the priority is not simply adding new tools. It is building a KM environment that supports how work actually happens, with knowledge embedded into workflows and connected to enterprise goals.
How can KM leaders prove business value and impact?
KM leaders can prove business value by linking KM measures to business priorities such as efficiency, productivity, decision quality, and reduced rework. APQC found that KM’s impact is difficult to measure for many organizations, which complicates funding and buy-in.
A practical starting point is to define what success means to senior leadership and align KM measures to key business measures. This helps KM teams move from activity reporting toward clearer evidence of business contribution.
KM’s next phase will be defined by whether organizations can turn AI-driven momentum into mature, measurable capability. The teams that make the most progress will strengthen the knowledge foundations beneath AI, embed KM into work, and connect impact to the business outcomes leaders already care about.
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About this Content
This content can include median values sourced from APQC's Open Standards Benchmarking database. If you're interested in having access to the 25th and 75th percentiles or additional metrics, including various peer group cuts, they are either available through a benchmark license or the Benchmarks on Demand tool depending on your organization's membership type.
APQC's Resource Library content leverages data from multiple sources. The Open Standards Benchmark repository is updated on a nightly cadence, whereas other data sources have differing schedules. To provide as much transparency as possible, APQC will always attempt to provide context for the data included in our content and leverage the most up-to-date data available at the time of publication.