For years, “learning in the flow of work” has been one of those ideas that everyone in L&D could agree with, but few organizations could fully deliver. The premise was compelling: instead of asking people to interrupt their work whenever they needed to learn something, bring learning closer to the problem they were trying to solve. In practice, however, the technology often lagged behind the ambition.
Traditional learning systems were designed primarily around destinations. A learner recognized a knowledge gap, opened the LMS, searched for the right course or resource, completed some training, and then returned to the task. That model remains valuable for structured development, particularly when organizations need consistent onboarding, certification, compliance, or formal skills development. But it is less effective at addressing the hundreds of smaller learning needs that appear unexpectedly throughout the working day.
AI is beginning to close that gap. But it is also pushing the idea of learning in the flow of work further. A new concept is emerging: dynamic enablement. Rather than treating every moment of uncertainty as a learning need, dynamic enablement focuses on giving people whatever support will help them perform in that moment. Sometimes that means learning something new. Sometimes it means answering a question, exploring a topic, accessing organizational expertise, practicing a skill, or checking what someone already knows. The goal is not simply to deliver more learning. It is to connect people with the knowledge, guidance and development they need to perform.
Source: CYPHER Learning; Source: Josh Bersin
The learning moment rarely starts with a course
Think about how people encounter gaps in their knowledge at work.
- A new employee is handling a process independently for the first time and needs to confirm the next step.
- A sales representative is preparing for a customer conversation and realizes they do not fully understand a product's capability.
- A manager is about to handle an unfamiliar situation and wants to strengthen a particular skill.
- An experienced employee takes on a new responsibility and needs enough understanding to begin confidently.
The natural response in these situations is rarely, “I need a course.” It is usually a question. What does this mean? How should I approach this? What do I need to know before I start?
This is particularly important for employee training. Development does not stop once onboarding or mandatory training is complete. Employees encounter new systems, processes, responsibilities, customer situations, and skill requirements continuously. When the only route to learning is returning to a course catalog, even a relatively small knowledge gap can interrupt work.
The opportunity is to make learning available at the point where that gap appears.
This is what makes dynamic enablement a useful way to think about the role of AI in learning. The right experience depends on what the employee is trying to accomplish. Someone might need a direct answer from trusted organizational knowledge. Another person may need to explore a subject more deeply. Someone else may benefit from assessing their understanding or practicing a skill before applying it.
CYPHER Agent supports this more responsive model through Learn, Assess and Practice. Rather than assuming that every knowledge or performance gap should lead to the same learning experience, organizations can give people different ways to build capability depending on what they need at that moment. Learning becomes one part of a broader enablement experience designed around performance.
That is where learning in the flow of work becomes more than a convenient phrase. The learning experience begins with the learner’s immediate need rather than with the content an organization happened to package into a course months earlier.
The real challenge is making organizational knowledge usable
Most established organizations already have enormous amounts of useful knowledge. It exists in product documentation, procedures, training materials, policies, playbooks, presentations, and the expertise captured across the business. The problem is that possessing knowledge and making it useful at the right moment are two very different things.
When someone needs an answer quickly, asking them to search through several documents or remember which course covered a particular concept creates distance between knowledge and application. The more complicated that journey becomes, the more likely people are to rely on memory, ask a colleague, or simply make their best guess.
AI creates an opportunity to shorten that journey. CYPHER Agent can use resources that administrators make available to its knowledge base, allowing learners to explore organizational knowledge conversationally. Instead of needing to know which resource contains the information, the learner can begin with the question or topic they are trying to understand.
There is an important distinction here. Learning in the flow of work should not simply become enterprise search with a conversational interface. Finding information is useful, but learning requires people to understand, connect, and ultimately apply that information. The opportunity is to make organizational knowledge easier to turn into capability, not simply easier to retrieve.
In the moment learning should build capability, not dependence
There is a potential weakness in any conversation about instant AI assistance. If every knowledge gap is solved by producing an immediate answer, are we helping people become more capable or simply making them better at asking an AI?
For L&D leaders, that distinction matters. The objective should not be to remove the need to learn. It should be to remove unnecessary barriers between the learner and meaningful development. Sometimes a concise explanation is exactly what someone needs. At other times, the learner needs to explore a concept more deeply, test what they know, or practice applying it.
This is where the broader CYPHER Agent experience becomes important. can help someone build understanding around a topic. can help establish what they already know and identify areas that need more attention. can provide an opportunity to apply knowledge and receive feedback. Skills associated with learning content can also give learners a clearer starting point for development.
Together, these experiences create a more useful interpretation of learning in the flow of work. The goal is not simply to deliver answers faster. It is to give people different ways to move from uncertainty toward greater knowledge and skill, depending on what the moment requires.
Formal learning and learning in the flow of work are complementary
The arrival of AI does not make structured learning obsolete. In fact, organizations will still need formal courses and learning paths whenever consistency, sequencing, assessment, or certification matters. The mistake would be assuming that formal learning and in the moment learning are competing models.
A stronger learning strategy connects them. A course can establish the foundations of a subject, while AI can help a learner investigate something they do not fully understand. A structured pathway can define the capabilities required for a role, while conversational learning can provide support when one of those capabilities becomes relevant in practice. Formal assessment can validate knowledge, while practice can help someone develop confidence before applying it in a real situation.
CYPHER Agent can also be accessed within courses through Learn, Practice, and Assess. This creates an important connection between structured content and responsive learning. If someone encounters a difficult concept during a course, the answer does not necessarily have to be another generic resource or a repeat of the same material. They can explore that particular area more deeply while remaining connected to the learning experience.
For employee training teams, this creates a model that can support development across the employee lifecycle. Structured learning can provide consistency during onboarding, compliance, and role development, while in the moment learning can support employees as new questions, responsibilities, and skill needs emerge during their work.
L&D needs to design for the questions it cannot predict
This may be the most important implication of learning in the flow of work. Traditional learning strategies depend heavily on predicting what people will need to know. L&D identifies a requirement, creates content, assigns it, and measures the result. That approach works when the learning need is known in advance, but modern work produces countless situations that cannot be anticipated so neatly.
As roles evolve and skill requirements change, organizations need a learning environment that can respond to both planned and unplanned development needs. LinkedIn’s 2025 Workplace Learning Report found that 49% of learning and talent development professionals said executives were concerned that employees lacked the right skills to execute business strategy. That pressure makes it increasingly difficult for organizations to rely solely on periodically produced learning content. Source: LinkedIn
The strategic question for L&D therefore becomes broader. Teams still need to decide what people should learn, but they also need to create an environment in which people can continue building knowledge when an unexpected need emerges. That means thinking about the accessibility of organizational knowledge, the relationship between formal learning and practice, and the tools available to learners when they encounter something they do not yet know.
Learning in the flow of work is becoming dynamic enablement
The next evolution of learning in the flow of work may be dynamic enablement: reducing the distance between a performance need and whatever knowledge, guidance, practice or learning will help someone address it.
That distinction matters. Not every problem at work requires a course. Not every question requires a learning pathway. Sometimes people need an answer. Sometimes they need to understand why. Sometimes they need to practice, assess their knowledge or explore a subject in greater depth.
AI makes it increasingly practical to support those different moments within the same learning environment. Learners can engage with approved organizational knowledge, explore concepts conversationally, assess what they know and practice skills without every interaction having to be anticipated and manually designed by a training team.
For learning teams, this expands the opportunity considerably. Their role is no longer limited to deciding what people should learn and creating the training to deliver it. They can increasingly think about how the knowledge and expertise across the organization can dynamically enable better performance.
Formal learning remains part of that strategy. But it sits alongside a much broader set of experiences that can help people move from “I don't know” to “I can do this” when the need actually appears.
That is the real promise of dynamic enablement: not learning everywhere, but capability available when and where performance demands it.
Ready to bring learning closer to work?
CYPHER Agent helps organizations extend learning beyond the boundaries of traditional courses by giving learners personalized ways to Learn, Practice, and Assess when they need support. By connecting AI-powered learning with organizational knowledge and skills development, learning can become a more continuous part of how people build capability.
Discover how CYPHER Agent can help your organization bring learning into the flow of work and turn everyday knowledge needs into opportunities for development.
Schedule a demo with CYPHER Learning
References
- Source: CYPHER Learning - https://www.cypherlearning.com/faq/cypher-agent-for-learners
- Source: Josh Bersin - https://joshbersin.com/2026/03/the-world-of-corporate-training-lurches-toward-enablement/
- Source: CYPHER Learning - https://www.cypherlearning.com/resources/guides/cypher/cypher-agent
- Source: CYPHER Learning - https://www.cypherlearning.com/resources/webinars/cypher-live-proprietary-data-in-cypher-agent-for-learners
- Source: CYPHER Learning - https://www.cypherlearning.com/ai-360/cypher-agent-for-learners
- Source: LinkedIn - https://learning.linkedin.com/resources/workplace-learning-report
