What Knoco International’s latest global survey tells us about KM maturity, value, governance, technology, learning, and artificial intelligence
Knowledge Management is entering a consequential period.
Organizations are being asked to make faster decisions, retain critical expertise, improve access to trusted information, learn from experience, adapt to workforce change, and introduce artificial intelligence into increasingly complex operating environments.
The question is no longer whether organizational knowledge matters. The more important question is whether organizations are managing that knowledge systematically enough to improve performance, reduce risk, and support sound decision-making.
The Knoco International Global Survey of Knowledge Management 2026 Report provides a detailed global view of how organizations are responding to these challenges.
This is the fifth Knoco Global Survey of Knowledge Management, continuing a research series conducted in 2014, 2017, 2020, 2023, and 2026. Together, the five surveys span 12 years and include nearly 1,270 valid responses to the core demographic questions. The 2026 survey received 141 initial responses, with records reviewed through quality control, validation, and deduplication processes before analysis.
The result is a practical, longitudinal view of how Knowledge Management is evolving across industries, regions, organization sizes, technologies, and levels of maturity.
Knowledge Management Is Maturing, Not Being Replaced
One of the clearest conclusions from the report is that Knowledge Management is experiencing a period of consolidation, expansion, and maturation rather than radical reinvention.
The essential components of KM remain recognizable:
- Learning from experience
- Improving access to documents and knowledge
- Managing documented knowledge
- Creating and applying good practices
- Connecting people through communities and networks
- Capturing lessons
- Retaining critical knowledge
- Transferring expertise
- Reusing organizational knowledge
Artificial intelligence is changing how some of these activities are performed, but it is not eliminating the need for them. Organizations still require trusted knowledge, accountable owners, effective learning processes, clear governance, and people who know how to apply knowledge in context.
This finding matters because organizations can be tempted to treat every new technology as a replacement for the management disciplines that came before it. The survey suggests a different path.
Technology can accelerate the movement, discovery, analysis, and application of knowledge. It cannot compensate for weak content, unclear ownership, poor processes, organizational silos, or a culture that discourages learning and knowledge sharing.
Six Major Findings from the 2026 Global Survey
1. Leadership remains the strongest influance on KM success
Leadership support continues to be the most important organizational factor affecting Knowledge Management.
In the 2026 results, the absence of leadership prioritization and support was the highest-ranked barrier to KM. At the same time, support from senior management was the highest-ranked enabler.
Support from KM teams and champions, effective KM processes, and easy-to-use technology also ranked highly. However, these elements are difficult to sustain without visible leadership commitment.
The findings reinforce a practical lesson: Knowledge Management cannot succeed as an isolated staff activity. Leaders must establish expectations, assign accountability, connect KM to organizational priorities, and reinforce the behaviors required to make knowledge flow across boundaries.
A KM program may have capable practitioners and advanced technology, but it will struggle when leaders do not make knowledge sharing, reuse, learning, and retention part of normal organizational performance
2. KM creates greater value when it is embedded into normal work
The survey continues to show a relationship between KM maturity, organizational integration, and reported value.
Organizations where KM is integrated into routine work report higher average monetary value than organizations where KM remains a non-routine activity, a temporary initiative, or a one-time intervention.
Integration most commonly includes:
- Workflows
- Defined roles
- Supporting technologies
- KM processes
- Routine operational activity
Integration into incentives, rewards, and performance systems remains less common.
Only a minority of respondents were able to provide a monetary estimate of KM value. Among those who could, some reported benefits reaching tens or hundreds of millions of dollars, especially in larger organizations and organizations with longer-established KM programs. These figures should be interpreted as approximate indicators rather than universal financial benchmarks.
The broader lesson is more important than any single financial number. KM creates the strongest value when it changes how work is performed, how decisions are made, and how experience is reused.
3. Human learning processes remain central to performance
The survey demonstrates that Knowledge Management remains fundamentally connected to people, learning, experience, and structured conversation.
The KM processes receiving some of the highest weighted-value scores in 2026 included:
- After Action Reviews
- Coaching and mentoring
- Project lessons capture meetings
- Peer Assist
- Knowledge Retention interviews
- Storytelling
- Knowledge-sharing roundtables
These are not passive information storage activities. They help people examine experience, ask questions, understand context, identify lessons, transfer expertise, and apply knowledge to future decisions.
This is particularly important in an AI-enabled environment. Artificial intelligence can help locate and summarize information, but organizations still need structured processes through which people interpret experience, challenge assumptions, validate lessons, and determine what should be done differently.
4. Technology delivers the most value when it supports practical KM needs
The strongest reported technology value continues to come from practical, operational Knowledge Management use cases.
These include:
- Document collaboration
- Knowledge article and good-practice repositories
- Enterprise content management
- Enterprise search
- People and expertise search
- Semantic search
- Lessons management systems
- eLearning
- Artificial intelligence
Searching for documents remains the most commonly reported technology-enabled KM function. Publishing good practices, collaborating on documents, managing enterprise content, and enabling people to ask questions also remain important.
SharePoint continues to be the most commonly reported technology family. Microsoft Teams and other elements of the broader Microsoft ecosystem are increasingly visible, while organizations also use platforms such as Confluence, Salesforce, SAP, Google Workspace, Slack, Jira, Moodle, and Power BI.
At the same time, documented knowledge remains scattered across multiple repositories in many organizations.
This reinforces an important distinction. Purchasing a platform does not automatically create a functioning knowledge environment. Organizations still require information architecture, metadata, taxonomy, content ownership, records management, curation, lifecycle controls, and processes for maintaining the quality and usefulness of knowledge.
5. Governance and measurement remain areas of concern
Governance is one of the strongest recurring themes in the report.
Senior management support, clear direction, assigned roles, accountable ownership, and an understandable business case are consistently associated with stronger KM implementation.
However, relatively few organizations report having all of the following in place:
- A formal KM business case
- Documented KM success stories
- Mature KM performance measures
- Clear evidence connecting KM to business outcomes
- Incentives aligned with desired knowledge behaviors
This creates a difficult cycle. Leaders want evidence that KM is creating value, but KM teams may not have established the measures, baselines, or success stories needed to demonstrate that value.
Knowledge reuse and value created through KM are among the most valuable forms of measurement. User numbers, participation levels, and community membership are more commonly tracked, but these activity measures do not always demonstrate organizational impact.
An effective KM measurement system should therefore distinguish among:
- Activity, such as participation or content contributions
- Capability, such as improved search, knowledge access, or lesson reuse
- Behavior, such as greater collaboration or knowledge sharing
- Performance, such as reduced cycle time, lower cost, improved quality, or reduced risk
- Strategic impact, such as stronger innovation, resilience, readiness, or decision advantage
6. Artificial intelligence is moving rapidly into KM
Artificial intelligence is no longer only a future consideration for Knowledge Management.
In the 2026 survey, 56 percent of respondents to the initial AI question said their organization had already introduced AI, including machine learning, as part of KM. Another 29 percent reported plans to introduce it. Only 7 percent reported having no current plans.
The most frequently reported current and planned AI applications included:
- Search and content recommendations
- Data analytics and insights generation
- Automation of knowledge workflows
- Preparation of reports and responses
- Customer support
- Knowledge discovery and retrieval
However, the most significant implementation challenges were not limited to the technology itself.
Respondents identified user adoption and change management as the most frequently reported challenge. Data and content quality, content availability, and integration with existing systems were also major concerns.
This is one of the most important findings in the entire report.
Organizations should not begin their AI journey by asking only which platform they should purchase. They should first examine whether the organization has:
- Trusted and current content
- Clear ownership and accountability
- Appropriate access controls
- Defined knowledge workflows
- Effective information architecture
- User adoption and change plans
- Measurement mechanisms
- Ethical policies and controls
- Processes for validating AI-supported outputs
AI readiness is therefore closely connected to KM readiness.
The survey concludes that successful AI-enabled KM depends on the same organizational foundations that have always mattered: trusted content, effective knowledge flow, clear ownership, user adoption, governance, measurement, and ethical controls.
Culture Remains More Than a Knowledge-Sharing Problem
Cultural issues were the second-highest-ranked barrier to Knowledge Management in the 2026 survey.
The most frequently reported cultural barrier was a lack of openness to sharing. Short-term thinking was also prominent, along with limited empowerment and concerns related to secrecy or confidentiality.
These findings show that KM culture is not simply about persuading employees to upload more documents.
The cultural environment also determines:
- Whether people feel safe admitting mistakes
- Whether teams learn from unsuccessful outcomes
- Whether knowledge can move across organizational boundaries
- Whether employees are empowered to challenge existing practices
- Whether long-term organizational learning is valued
- Whether people receive time and recognition for contributing knowledge
- Whether knowledge is treated as an organizational asset or a source of individual power
Organizations where KM is embedded into normal work report fewer cultural barriers on average than organizations in earlier stages of implementation.
Culture does not change through communications campaigns alone. It changes when leadership expectations, management systems, workflows, incentives, accountabilities, and daily behaviors reinforce the value of learning and knowledge reuse.
The Future of KM Is Both Human and Digital
The 2026 survey shows a discipline that is adapting to a new operating environment while retaining its core purpose.
Knowledge Management remains the systematic management of knowledge, learning, experience, content, people, processes, and technology in support of organizational performance and better decisions.
Artificial intelligence expands what organizations can do with their knowledge. It can improve discovery, recommendation, analysis, automation, and access. However, AI also increases the importance of content quality, knowledge ownership, governance, validation, ethics, and human judgment.
The organizations that gain the greatest advantage will not be those that simply deploy the most technology.
They will be the organizations that know what knowledge matters, manage it intentionally, connect it to work, and create an environment in which both people and technology can use it responsibly.
Discover What the Global KM Community Is Telling Us
Explore the complete findings, comparisons, charts, and conclusions in the Knoco International Global Survey of Knowledge Management 2026 Report.
Access the complete report and use the findings to evaluate your organization’s KM maturity, governance, technology, learning systems, Knowledge Retention practices, and readiness for artificial intelligence.