Today we’re speaking with Ling-yi Tsai, our HRTech expert, who brings decades of experience assisting organizations in driving change through technology. With her deep specialization in HR analytics and the integration of technology across the entire employee lifecycle, she offers a unique perspective on the critical intersection of human connection and digital innovation in corporate training.
In our conversation, we will explore the significant gap between the demand for and delivery of personalized digital learning. Ling-yi will shed light on why instructor-led sessions continue to set the standard for engagement and trust, and how we can translate that human element into our digital strategies. We’ll also address the common pitfalls of asynchronous learning that leave employees feeling unmotivated and unsupported, and discuss the strategic dilemma of investing in advanced AI versus ensuring every employee has the basic tools to succeed. Finally, we’ll look at how a thoughtfully designed blended learning model can offer the best of both worlds.
Learners overwhelmingly value personalization, yet it is often missing from digital training. What are the primary barriers causing this disconnect, and what are the first practical steps L&D teams can take to integrate meaningful personalization into their digital platforms?
The disconnect is a classic case of scale versus substance. Organizations push for digital solutions to train thousands efficiently, and the easiest way to do that is with a one-size-fits-all model. It’s faster and cheaper upfront. But we see the cost in engagement, as a staggering 94% of learners are telling us they want personalization, and 64% feel it’s extremely important. The primary barrier is often a fear of complexity. A practical first step is to stop thinking of personalization as creating a unique course for every single employee. Instead, start with personalized pathways. Use a simple pre-assessment to sort learners into three groups based on existing knowledge—novice, intermediate, and expert—and give them different starting points or curated content libraries. Another easy win is to offer choices within a single module, letting learners select case studies or examples that are most relevant to their specific roles.
A large majority of learners report paying closer attention in live, instructor-led sessions. What specific elements of human-led training foster this motivation and trust, and how can L&D leaders begin to replicate those qualities in a digital or blended environment?
That powerful statistic—84% of learners paying closer attention in live sessions—really gets to the heart of it. The magic of human-led training is rooted in presence and accountability. When you’re in a room with an instructor and peers, you feel seen. There’s an implicit social contract to be attentive. The instructor can read the room, notice confused faces, and adjust their pace or explanation in real time. This dynamic feedback loop builds incredible trust and psychological safety. To replicate this digitally, you must intentionally engineer human connection points. For example, instead of a pre-recorded lecture, host a live virtual session with mandatory cameras-on for smaller groups. Use breakout rooms frequently for peer-to-peer problem-solving. Also, assign a “learning buddy” to each participant for the duration of a course so they have a dedicated person to check in with, which fosters accountability and a sense of shared journey.
Asynchronous digital learning is often rated as the least motivating and psychologically safe format. What specific factors contribute to this experience for learners, and what design changes can immediately improve engagement and a sense of safety in self-paced modules?
The feeling of being alone in the digital void is what kills motivation in asynchronous learning. When only 16% of learners say it motivates them a great deal, it’s a clear signal that the design is failing them. Learners feel they’re just clicking through slides with no one to turn to if they get stuck. There’s no one to validate their understanding or celebrate a small win. This isolation can create anxiety, making it feel psychologically unsafe to admit you don’t understand something. A simple but powerful design change is to embed a human touch. Instead of just text, start modules with a short, informal video of the instructor explaining what the learner will accomplish. Another key is building in structured reflection points where learners must post a thought to a moderated discussion board. The goal is to show them that even though the learning is self-paced, they are not on their own. A great metric for success here would be tracking the completion rate of voluntary, interactive elements within the module.
With over a fifth of learners lacking adequate tech tools and many companies adopting AI, how should organizations balance investing in new AI learning tools versus ensuring foundational “tech readiness” for all employees? What are the key risks of prioritizing one over the other?
This is a critical balancing act. The fact that 22% of learners report having inadequate tools is a huge red flag. The risk of prioritizing shiny new AI tools over foundational readiness is creating a two-tiered system of learning. You’ll have a segment of your workforce that can leverage these advanced, adaptive AI pathways, while another segment can’t even reliably access the basic digital training. This breeds resentment and widens skills gaps, completely undermining the goal of L&D. On the other hand, ignoring AI means falling behind competitively. The solution is a phased approach. First, establish and fund a “minimum viable tech readiness” standard for all employees. This means ensuring everyone has the necessary hardware, internet access, and basic digital literacy. Once that foundation is solid, you can begin layering in AI-powered tools, starting with pilot programs for specific teams to prove their value and work out any integration kinks before a wider rollout.
Thoughtfully designed blended learning is seen as a promising bridge between personalization and scale. Can you walk me through a step-by-step example of what an effective blended program looks like in practice, from initial design to final evaluation?
Absolutely. Let’s take a leadership development program for new managers. The first step, design, would involve surveying the cohort to identify their biggest challenges and confidence levels, creating personalized learning paths from the start. The program would kick off with an asynchronous module covering the foundational theories of management—things they can learn at their own pace. This module would include interactive quizzes and short assignments. The second step is a live, instructor-led virtual workshop. This isn’t a lecture; it’s a session focused on application, using role-playing scenarios based on the pre-work. Here, managers get real-time feedback in a safe environment. Following this, we introduce a peer-coaching element where managers are paired up to work on a real-world project, applying their new skills on the job. The final step, evaluation, isn’t just a test. We’d use a 360-degree feedback tool to see if their direct reports have noticed a change in their management style, providing concrete business impact data.
What is your forecast for the future of corporate learning and development?
My forecast is that the future of L&D lies in what I call “intelligent blending.” It’s no longer a binary choice between human or digital. Instead, the most successful organizations will use technology, especially AI, not to replace human instructors but to amplify their impact. AI will handle the heavy lifting of personalization at scale—analyzing performance data to recommend the perfect micro-learning module or connecting an employee with the right mentor. This will free up L&D professionals to do what they do best: facilitate deep, meaningful, and transformative human-to-human learning experiences. The focus will shift from content delivery to connection, coaching, and creating a true culture of continuous development.