From Content to Capability: AI’s Real Role in L&D

Learning and Development (L&D) teams have been creating content for decades. This includes creating content for a workshop, an e-learning module, or a quick microlearning video. We measure success by completion rates and course ratings. But as professionals responsible for building capabilities, we need to introspect: does ticking the “completed” box and the completion certificates tantamount to an increase in workforce performance? Can text-heavy learning solutions be enough for experiential learning?

Most LMS tools only report completion as a proxy metric. They state that “completion rates alone don’t provide real insight into whether employees are applying knowledge or skills on the job” (eLearning Industry, 2023). Even when digital learning is common, only about one in three learners reports that the learning is effective and supports daily job activities (360Learning, Global L&D Survey 2023).

A text-heavy training approach just does not fit anymore. It is not sustainable. The Global Talent Shortage Survey 2024–2025, conducted by ManpowerGroup, reports that 75% of employers globally are struggling to find the skilled talent they need. Similarly, the ManpowerGroup 2025 Talent Shortage Survey highlights that nearly 77% of employers in the Asia-Pacific region (APAC) are experiencing similar talent scarcity, with global averages hovering around 74%.

How do we bring about the change that makes learners feel capable, not just knowledgeable?

AI-Driven Capability Building

“Content Builds Capabilities” is an important concept when creating well-crafted and engaging learning materials. The effectiveness of content delivery depends less on the content than on how the content is experienced by learners. In short, we need to pay attention to how we design the user experience.

I recently had the opportunity to work on a course on Project Management. The previous course was considered too short and lacked conceptual depth based on internal feedback. So, the revised version was designed to explain the methodology in detail, with more case studies, examples, and data. However, this revised course design became too heavy on text, pictures, charts, graphs, and lengthy assessments. The focus of the course shifted from enabling learning to just delivering content. As a result, learners became overwhelmed with too much to read and process, all at the same time. The screens went on and on till the end. The learners struggled to grasp key concepts and failed to internalize their application in real-life scenarios. This highlights the importance of creating immersive learning solutions that prioritize user engagement and retention. After seeing results below expectations, the learning solution was redesigned. The content was cut to focus on key points, and smaller microlearning modules were designed to break the monotony, including real-life scenarios, case studies, and assignments.

Ways We Used AI to Help Redesign the Course

AI helped in analyzing the content and formulating SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) learning outcomes that were aligned with Bloom’s Taxonomy. The course was originally designed in HTML5 format and had to be repackaged and transferred to the client’s LMS. The built-in xAPI tools within the AI-powered LMS helped analyze learner engagement, such as how many learners took the course, how many completed it, where most learners struggled, and how they performed on assessments. Such extensive data helps enhance courses and improve learner engagement.

How to Begin Using AI Within Your L&D Today

AI is here to make learning solutions stronger and more impactful. Let’s look at the following ways in which AI can enhance learning and its application:

• Personalized User Journeys: AI can suggest specific content or strategies for a learning solution, tailored to skills, role in the organization, and overall business goals.
• Learning in the Flow of Work:  AI can deliver quick tips or resources right at the moment they are needed.
• Real-Time Feedback: From role-play bots to skill simulations, AI can give immediate, actionable feedback to the learners.
• Future Skill Insights: AI can help L&D teams identify which capabilities will be most important in the future and assist in creating scalable courses for users based on prior learning.

Utilizing AI technologies can enhance the accessibility and effectiveness of learning solutions by tailoring them to individual learning styles and well-defined learning outcomes. By doing this, we in L&D can optimize content delivery and ensure that learners not only acquire knowledge but also develop the necessary skills and capabilities to succeed in their professional endeavors.

From One-Time Events to Continuous Growth

Capability building isn’t about a single learning solution; rather, it is about creating continuous opportunities to learn, apply, and improve. AI is here to act like a co-author supporting learners, nudging them to keep moving forward, and making sure nothing falls through the cracks. This means:

• Shorter, more frequent learning moments
• Practice is built into tasks related to real work
• Measuring impact based on skills applied, not just attendance or completion numbers

When AI Misses the Mark

AI’s benefits are significant, but poor implementation and following blindly can undermine outcomes. Common pitfalls include:

• Bias in Algorithms: Flawed training data can lead to recommendations that may be irrelevant or unfair.
• Over-Automation: Excessive reliance on AI can strip away the human connection, leaving learners feeling disconnected and disengaged.
• Privacy Risks: Collecting large volumes of learner data without strong governance can erode trust.
• Lack of Context: Generic AI models may ignore organizational culture or specific job realities, reducing relevance.
• Opaque Decisions: If learners can’t understand why AI makes certain recommendations, trust in the system diminishes.

The Human-AI Partnership

There is a constant worry in the workforce that AI will take over L&D roles. But the truth is, AI is here to make our lives simpler, better, and more efficient. The future of L&D lies in blending human insight with AI efficiency. One example of a human-AI partnership is when AI helps automate repetitive tasks such as content curation, freeing L&D leaders to focus more on the human side, which includes designing meaningful experiences, connecting with learners, and aligning training with business goals. It is about how well we integrate AI into our work, make it more productive, and create scalable solutions. AI is simply the bridge between information and transformation.

Content gives knowledge. Capability transforms performance. And that is where the real “Magic” happens.