The Next Edge in Knowledge Management: KM for the Modern Workforce and the Era of AI

Consider the example of global energy provider, TechnipFMC, when facing a wave of retirements. The KM team developed customized knowledge transfer plans for each departing expert, interviewing them and their colleagues, creating an inventory of at-risk knowledge and actionable plans to close gaps. This process preserved critical, operational knowledge; accelerated onboarding for new leaders; and honored the legacy of their departing experts.

♦ Capturing lessons learned is another powerful tool. When teams reflect on past projects and experiences together and document what worked (and what didn’t), those insights become reusable guidance for the entire organization. NASA’s “Pause and Learn” sessions are a model for this approach. It holds regular team reflections and then documents insights into a central repository, helping teams learn from both failures and successes.

♦ Expertise location systems remain an essential capability. A global pharmaceutical company, for instance, built an expertise locator that catalogs technical experts and pairs it with a dedicated answer service. This system, developed with input from communities of practice, enables project teams to quickly find the right expert, saving time, boosting collaboration, and ensuring easy access to critical knowledge.

Reskilling and Preparing the Future Workforce

KM is a catalyst for organizational learning, but in the modern era, it must go beyond formal training. Today’s organizations need learning ecosystems that blend human expertise with AI-driven insights, enable peer-to-peer exchange, and move knowledge across boundaries in real time.

♦ Communities of practice are a proven way to augment formal learning. Rather than relying on informal networks, Framatome, a global energy services organization, established structured communities with clear charters and alignment to business objectives. These communities became trusted spaces, both virtual and in-person, where employees could ask questions, share artifacts, and co-develop standards. The result was greater agility where knowledge moved quickly from discovery to standard practice, and community activities directly supported the company’s strategic goals.

♦ Applying lessons learned creates real impact when best practices identified by project teams are actively integrated back into processes, playbooks, and training and not simply stored in a repository. By closing the loop and making learning visible, KM leaders can ensure that knowledge is not only captured, but that it is also applied and continuously evolves as the organization grows. This is where the true value of reuse happens, driving ongoing improvement and resilience.

♦ Recognizing participation in communities, capturing or reusing lessons, and mentoring as performance-relevant behaviors help embed learning into the culture. When employees see their contributions valued, they’re more likely to participate and invest in the collective intelligence of the organization. Over time, this builds a more resilient and adaptable learning culture.

Embedding AI Into Everyday Work

AI is already reshaping KM by automating routine tasks, enhancing search and retrieval, and enabling proactive knowledge enablement. APQC’s research into KM priorities and trends also reveals that incorporating AI and other smart technology remains the top priority for KM teams to focus on. But technology alone isn’t the answer. KM leaders must ensure that AI solutions are ethical, transparent, and designed around real user needs and that the underlying knowledge is validated and trustworthy.

Infosys, for example, faced a challenge when critical knowledge was scattered across internal sites, personal devices, and individual experts. By developing an AI-powered search platform built on LLMs—and embedding these capabilities into everyday tools— Infosys enabled consultants to reuse project artifacts, collaborate across silos, and respond faster to client needs. The platform reduced search times by 50%, boosted user satisfaction by 80%, and helped to mitigate knowledge loss from employee turnover.

Graph - TOP 7 KM Business Priorities 2026