The learning world is changing a lot because of AI. It's been three years since we started experimenting with this technology, first cautiously and without seeing much promise. Now, it seems almost inevitable that AI will be used at all stages of creating a learning solution. The biggest benefit it has brought so far has been an efficiency boost. Many of us have learned to do our work faster. Theoretically, this means there's more time for deeper, more creative work. But is that really happening?
The AI efficiency paradox in learning design
AI speeds up many tasks, especially around content creation, summarization, and structuring. Some teams report saving anywhere from 10% to 30% of their time—that's at least four to twelve hours a week that could go into improving learning solutions. But instead of using that time to rethink and refine learning experiences, many teams just create more content. This means the efficiency boost is mostly economic: more output, but not necessarily better quality. At worst, it feels like AI isn't helping at all—just making it possible to churn out more learning materials every month than before.
There has to be a better way to use this extra time. Without a shift in strategy, AI could push learning professionals towards an assembly-line approach where speed trumps depth. So, what should learning professionals be doing with this extra time?
Shifting focus: From content production to learner-centric design
What has worked for my team members and me is shifting the focus back to the learners and their journey. That is reflected in several activities we now regularly practice: learner persona creation, learner journey mapping, and skills mapping. The journey map allows us to put both the persona and the skills mapping inside of it. The idea of creating a learner journey map is not new—it just hasn't become extremely popular because it's a time-consuming thing to do. It requires gathering as much data about the learner as possible: not only the knowledge and skill gaps-related data but also their motivation, pain points, previous learning experiences, goals, and even what excites or frustrates them.
Before AI, deep learner research and mapping often felt like a luxury. With AI handling the time-consuming parts of content creation, this level of thoughtful design is possible.
Learner journey mapping: Key benefits
You might wonder why this process is necessary. If you already understand how learning works, why take the time to visualize it? To my team and me, this is what journey maps helped with:
Enhanced understanding
Visually organizing a learning journey helps uncover connections between different elements, making it easier to grasp dependencies and interactions. This broader perspective aids in better decision-making by identifying areas for improvement and overlooked challenges.
Highlighting hidden issues
Assumptions about how a learning experience unfolds may not always align with reality. By mapping it out, potential issues become clearer. For instance, our team once designed a mentoring program we were confident in, but mapping exposed gaps in time allocation and learner experience that required adjustments.
Promoting team collaboration
Building a map is an interactive process that invites team members to collectively contribute their insights, brainstorm solutions, and refine ideas. This shared effort fosters alignment, ownership, and a more well-rounded learning experience.
How to create an effective learning journey map
Building a learner journey map doesn't have to be overwhelming. Here are actionable steps to create a structured and effective map:
- We always start with step 0: Preparation. It includes creating a learner persona, diagnosing a skill gap, taking stock of all available resources, and digging deeper into the skill issue we are solving.
- Define the scope: Determine where the learning experience begins and ends. Is it a full program, a single module, or a specific learning interaction? Setting boundaries ensures clarity and focus. For example, I like starting with the “Discovery” stage, where we analyze how learners find our solution and decide to commit, then I usually put “Adaptation” for when students get used to the new process, which might be followed by “Active Learning “ and “Measuring Learning Results.”
- Identify key components: Choose what elements to map. Consider:
- Learner actions & emotions: What do learners do, and how do they feel at each stage?
- Touchpoints & support: How do facilitators, technology, and resources interact with learners?
- Challenges & opportunities: Where do learners struggle, and what improvements can be made?
- Skills: What gaps do learners start with? When do they practice skill building? How do they receive feedback?
- Balance perspectives: Ensure the map is realistic and balanced. Identify what the learner needs at each stage and how the learning experience supports those needs. For example, one thing we normally notice here is that we idealize the learner's emotions and they will always be happy, or that there are not enough skill practice activities to get to a desired skill level.
- Collaborate with stakeholders: Involve colleagues, stakeholders, and possibly even learners in discussing and correcting your map. Different perspectives help create a more accurate and effective learning journey.
- Refine & iterate: Use real learner feedback and performance data to update the map continuously. Regular reviews ensure that the journey remains relevant and impactful.
You can use a basic template, like the one shown below, to kickstart the process and try out mapping. The number of components might be too big for the start, so you can always customize them as needed.
Our experience: Implementing learner journey mapping
My team went through this shift firsthand. We adopted AI early on, leading us to create more and faster, which we learned to dislike quite quickly. We then went back to strategizing and discovered the learning design phase is where we all would love to spend more time—researching, prototyping, and mapping.
One example is a program designed for career switchers moving into IT. The original program was created under tight deadlines, with limited research beyond the prerequisite knowledge, learning preferences, and available time for studying. The program blended self-paced courses, live instruction, and project work, but we knew there were gaps.
Recently, we finally had the chance to build a proper learner journey map for this program. AI helped along the way: it acted as a simulated learner persona, helping analyze survey data and reviewing our journey drafts. We mapped out the learner's experience from start to finish, matching learning stages with real student feedback, completion rates, and performance data. We also examined how well different touchpoints—communication, assessment, and support—lined up with learner needs.
The insights were eye-opening. The journey map quickly showed where the experience was off-balance, where learners needed more encouragement, and where adjustments were needed.
After seeing the impact of this process, we made learner journey mapping a standard part of our learning design. Now, after needs analysis, we survey and interview learners more deeply. AI helps process and categorize this data into learner personas. Then, we build a journey map that includes learning activities, milestones, touchpoints, learner emotions, and communication strategies.
It's still early, but the results have been promising. While long-term data will take time to gather, one redesigned program has already shown a two-fold improvement in engagement and completion rates.
Conclusion: Designing for humans in an AI-powered world
AI is a powerful tool, but efficiency alone won't improve learning. The real value comes from using AI to free up time for what really matters—designing engaging, empathetic, and effective learning experiences. Instead of just producing more, learning professionals now have the opportunity to create better, more meaningful learning journeys.
The question isn't just how AI can speed things up but how it can help create learning that truly resonates with people.
Image credit: Flashvector