Over the past year, we have seen a meaningful shift in how workplace learning and support tools are evolving. Historically, employees relied heavily on memory and periodic reference materials to do their jobs. Today, organizations increasingly are adopting artificial intelligence-powered knowledge tools that place information at employees’ fingertips—or even serve it proactively—making memorization far less critical than before.
These modern job aids are no longer static references. They are dynamic, AI-enabled search tools embedded into daily workflows, helping employees complete tasks, access information, and respond more effectively in real time. This represents a significant shift—from memorizing information to retrieving it instantly. Employees no longer need to retain every detail; instead, they need immediate, context-aware support on demand.
REAL-TIME RETRIEVAL ENTERPRISE-WIDE
In call centers, for example, AI copilots listen to conversations live, suggesting responses, surfacing relevant product details, and automating notes. Most platforms now include these tools, and new AI-native systems are emerging. The result is faster onboarding for agents and less time spent remembering or asking others to clarify policies during live customer interactions.
This kind of real-time retrieval also is expanding across the enterprise. Sales teams now use it to surface product knowledge quickly. HR teams use it to help answer policy questions quickly. Field technicians pull up troubleshooting guidance on-site. At Accenture, we also use various knowledge bots connected across repositories and datasets to help access information fast—whether it was covered in training but forgotten, needed unexpectedly, or is simply new learning for a role. This saves tremendous time spent memorizing and hunting for knowledge sources when needed.
TEACHING EMPLOYEES TO USE THE TOOLS
Learning teams are starting to incorporate these new job aids into their learner support tools and experiences. Rather than frontloading every detail during training or sending employees to lengthy manuals, these types of job aids reduce the pressure to remember and make knowledge recall seamless. This shift also is creating a new training need—teaching employees how to work effectively with these systems. Skills such as asking clear questions, refining searches, and interpreting AI-generated suggestions are becoming core competencies.
Still, not all learning can be retrieved on demand. Skills such as communication, empathy, and decision-making require development through practice. Many organizations are addressing this through AI-powered role-plays and simulations—tools that scale one-on-one coaching and give learners space to practice and build confidence using natural, conversational language.
For Learning professionals, this evolution calls for both upskilling and reframing their role. Beyond designing learning programs, they are curating knowledge for both employees and AI, working with subject matter experts to codify expertise and help build the knowledge bases that support tools such as bots and copilots. Leading teams are embracing this work as knowledge stewardship, ensuring institutional knowledge is captured, searchable, and sustained. In doing so, they contribute to what many call a “digital brain”—a centralized knowledge ecosystem that underpins AI tools and supports performance at scale.
L&D’S CHANGING ROLE
The shift from memorization to retrieval is redefining how L&D drives impact. It is no longer just about designing content but about enabling real-time performance through intelligent, embedded support. Learning professionals are helping structure knowledge for AI search tools, refining content to reflect real-world tasks, and ensuring employees can access critical information without delay. Those who lean into this transition will help their organizations truly perform better and faster, as well as stay agile for whatever comes next.
