AI Propels KM to Center Stage
Knowledge management (KM) had a breakout year in 2025. Once relegated to the background as a support function, KM has surged into the spotlight, propelled by company demand for AI-driven innovation, cloud scalability, and real-time decision support. Vendors across CRM, contact center-as-a-service (CCaaS), workforce engagement management (WEM), and enterprise resource planning (ERP) are embedding and expanding KM capabilities, positioning it as a foundational business application. With cloud-first deployments dominating, these platforms enable agile rollouts and accelerate adoption across industries.
The expanding role of KM is unmistakable. It powers artificial intelligence, reduces training costs, boosts productivity, and augments both customer and employee experiences across the organization. KM is no longer confined to contact centers or technical support; it now spans human resources, marketing, and operations.
Knowledge in Motion
In today’s companies, knowledge is not just stored; it’s dynamically orchestrated. Modern KM platforms act as both a framework and integration layer across customer experience (CX), employee experience (EX), CRM, and AI systems, accelerating resolution and tailoring guidance to context and intent. They fuel self-service portals, guide agents through complex workflows, and streamline employee onboarding. By integrating platforms, workflows, and departments, KM creates a unified ecosystem that dissolves silos, adapts to user behavior, and evolves with organizational needs.
AI at the Core
AI has redefined KM’s role by elevating it from archival storage to real-time, decision-ready intelligence. Modern KM platforms use machine learning, natural language processing, and predictive analytics to surface insights, anticipate needs, and tailor responses on the fly. They learn from interaction patterns, feedback loops, and behavioral signals, transforming knowledge into dynamic, context-aware guidance that evolves with the company. Search, formerly a passive task, is now a proactive experience. KM platforms deliver semantic discovery, predictive surfacing, and multimodal ingestion by pulling knowledge from documents, conversations, and narratives to ensure the right content reaches the right user at the right time.
Generative AI capabilities accelerate this transformation by auto-generating structured responses, summarizing complex content, and delivering cited answers with conversational clarity. KM platforms now ingest unstructured data, extract key insights, and convert those insights into reusable, governed knowledge assets. They detect contradictions, flag duplicates, and support version-aware publishing—ensuring that knowledge remains current, compliant, and contextually relevant. Together, AI and genAI are reinventing KM as a proactive, trusted, and extensible enterprise guidance framework.
Stewardship of AI
As AI adoption accelerates, KM is evolving beyond a delivery layer into a governance core, curating trusted sources, enforcing compliance, and managing AI system inputs and outputs to ensure explainable, auditable, and traceable organizational intelligence. Modern KM governs the flow of information as well as delivers answers. It serves as the scaffolding for trustworthy automation, anchoring version control, flagging contradictions, and enforcing policy across dynamic content ecosystems. As genAI accelerates content generation, KM provides the guardrails: validating sources, preserving context, and ensuring that every response is traceable and accountable. In this role, KM becomes an ethical compass for AI adoption, balancing speed with stewardship and innovation with integrity.
Innovation Wave
KM vendors are entering a new period of accelerated innovation, fueled by rising company demand, AI integration, and the need for trusted real-time guidance. R&D investments have surged: Vendors are embedding genAI capabilities, strengthening governance frameworks, exploring agentic AI to automate multistep tasks, and reimagining delivery across channels and contexts.
This current wave of innovation clusters around five key themes: AI-driven content creation, intelligent discovery, quality assurance, conversational delivery, and multi-channel publishing with feedback loops. These enhancements reflect a deeper commitment to solving longstanding KM challenges: creating articles, maintaining content, avoiding siloed knowledge, and keeping user experiences consistent, while laying the foundation for context-aware, ethically guided AI adoption. KM is no longer just keeping pace—it is setting the pace, transforming into an extensible, intelligent framework that cultivates clarity, trust, and connection across the enterprise.
Signals of Acceleration
Knowledge management is accelerating on multiple fronts. AI has become the great enabler, transforming KM platforms into real-time, context-aware tools that reduce friction and accelerate resolution for customers and employees alike. GenAI is not only reshaping the life cycle of knowledge from creation to summarization and retirement; it is also serving as a guardrail against hallucinations by curating trusted sources and enforcing compliance. Agentic AI is making knowledge actionable, triggering real-time workflows and transactions, while automation is reducing reliance on administrators and lowering costs.
The expansion of KM beyond the contact center is equally striking. HR teams are using it to streamline onboarding and training; marketing departments are leveraging it to support websites; and the wider organization is migrating away from siloed repositories toward unified ecosystems that span the entire customer journey. Usability improvements are making KM substantially easier to adopt, while integrations with third-party platforms extend its reach across the company. Even KM’s search capability is evolving from keyword-based retrieval to concept-driven discovery that proactively guides users with context-aware suggestions. Together, these signals point to a market in motion: KM is becoming critical company infrastructure, enabling AI governance, CX orchestration, and EX empowerment.
Headwinds
Yet momentum does not eliminate all challenges. The most pressing concern is data integrity. As genAI accelerates content creation, companies must ensure that outdated, redundant, or conflicting information does not seep into the knowledge base. Without disciplined governance, the risk of misinformation grows, eroding trust in both KM and AI systems. Fragmentation remains another barrier, with many organizations still trapped in legacy SharePoint sites, departmental intranets, and homegrown repositories. DMG estimates that 9 out of 10 enterprises need to upgrade to enterprise-grade KM platforms to achieve a unified source of truth.
Human factors also loom large. Even the most advanced platform falters without a knowledge-sharing culture. Adoption depends on training, gamification, and usability improvements that motivate employees to contribute and engage.
Meanwhile, the vendor landscape is crowded with overlapping narratives that blur differentiation, with vendors touting AI, genAI, and agentic AI benefits. Success depends not on chasing claims but on selecting providers aligned with company strategy and culture. KM is also a long-term journey and commitment, requiring continuous adaptation as AI accelerates innovation. A human-in-the-loop approach remains critical for validation, governance, and contextualization, and administrators must evolve into AI-literate stewards of data governance and cross-functional collaboration.
Finally, the measurement gap persists: KM’s contribution to business outcomes is real but remains difficult to fully quantify. Together, these challenges remind us that KM’s promise is inseparable from its discipline. The signals are clear but cautionary: Knowledge management is indispensable, but only when paired with governance, cultural buy-in, and human stewardship.
The Bottom Line
Fueled by AI, KM is evolving into a strategic lever for agility, trust, and responsible transformation. This trend points to acceleration: Adoption is surging, innovation is clustering around AI and automation, and KM is expanding across functions. The challenges remind us that success depends on governance, culture, and skills. For enterprises, the message is clear: KM is no longer optional. It is the infrastructure of intelligence, a system that orchestrates knowledge, governs AI, and delivers clarity at scale. The next two years will determine which companies harness KM as a competitive advantage, and which fall behind in the race for trusted, real-time intelligence.
Donna Fluss, founder and president of DMG Consulting LLC, provides a unique and unparalleled understanding of the people, processes, and technology that drive the strategic direction of the dynamic and rapidly transforming contact center and back-office markets. As the foremost analyst and visionary dedicated to the contact center and back-office markets, Fluss has provided expert guidance for more than 30 years to technology leaders as well as disruptive newcomers, investors, and enterprises that want to build next-generation AI-enabled contact centers She can be reached at Donna.Fluss@dmgconsult.com.