Designing Learning with Intention: How Technology and AI Can Support Performance in 2026

As organizations head into a new year, learning and development teams are facing a familiar tension: expectations are rising, timelines are shrinking, and technology—especially AI—is advancing faster than many teams can comfortably absorb. Across recent episodes of Powered by Learning, one theme consistently emerged from guests: technology works best in learning when it serves performance, not when it simply speeds up production.

Rather than asking what tools should we adopt next?, the more productive question may be how do we use technology to help people do their jobs better?

AI in Learning Content Creation: Speed Helps, but Instructional Design Still Matters

AI has quickly become a powerful accelerator for content creation, and learning leaders are already feeling the benefits. Sheldon Thomas, Director of Learning and Development at Transcarent, sees clear advantages in using AI to reduce production time, especially for media-heavy assets. “Using the AI tools where you can do the voiceovers very quickly, you can create images very quickly—it really does help us get to market faster with a lot of the courses that we need to create,” he said.

But speed alone doesn’t guarantee impact. Thomas cautioned that ease of creation can blur the line between design and mere assembly. “Some of these tools have almost made it too easy to create things, and things don’t feel as designed as they necessarily could have or should have been,” he noted. Without intentional structure, courses risk becoming “a glorified PowerPoint or a glorified PDF.”

Looking ahead, learning teams will need to resist the temptation to equate faster production with better learning—and instead use AI to support thoughtful design, not replace it.

Action Before Information: Designing Learning Around What People Do

Another strong signal from podcast guests was a shift away from information-first training toward experience-first design. Author and educator Karl Kapp described this as “Action First Learning”—an approach that prioritizes what learners need to do, not just what they need to know.

“I don’t really care if it’s a game or not,” Kapp explained. “What I care about is whether or not learners are engaged and learning in meaningful activities.”

Technology now makes this approach more scalable than ever. Simulations, branching scenarios, and even low-tech tools like card games can create the kinds of “desirable difficulties” that help learning stick. When learners struggle productively—solving problems before receiving answers—they build deeper understanding and confidence.

As Kapp put it simply: “Don’t ask the question, ‘What do learners need to know?’ Ask the question, ‘What do they need to do?”

AI as a Practice Environment: Role Plays, Simulations, and Feedback

Some of the most promising uses of technology discussed on the podcast involved AI as a practice environment, not just a development shortcut. At Transcarent, Thomas described how AI-driven role plays are helping health guides practice nuanced, emotionally complex conversations—at scale.

“AI allows us to create a scenario literally within 10 to 15 minutes,” he explained. “It can evaluate whether the person used the right words to express empathy, to show concern, and to guide the member effectively.”

These simulations also solve a long-standing challenge: limited access to live practice. Instead of relying on peer role plays that “can fall a little flat,” AI can adapt, fill in backstories, and respond realistically—giving learners a safer space to build confidence before working with real customers.

Looking ahead, Thomas sees even more potential in real-time, personalized feedback. “I can see a world where, as soon as a call ends, AI provides immediate coaching—what you did well and what you could do differently next time,” he said.

Meeting Learners Where They Are: Mobile Learning for Deskless Teams

For organizations with dispersed or deskless workforces, technology is also reshaping where learning happens. At Flagger Force, a company with thousands of employees working in active roadways, training is delivered through mobile-first microlearning and field communication tools.

“The idea was to meet people in the place that most suits them to learn,” said Luke Lazar, Vice President of Risk and Safety. “They’re already accustomed to using their phones to solve problems, so we deliver learning in that same environment.”
Short, focused lessons—often three to five minutes long—are pushed directly to employees, reinforced with real incidents, and followed by quick knowledge checks. The result has been remarkably high voluntary participation, particularly for safety training, which is traditionally difficult to sustain.

AI & Data in L&D: Personalization Guided by Human Judgment

Across episodes, guests agreed that the future of learning technology lies in personalization—but not at the expense of human judgment. On the 100th episode of d’Vinci’s Powered by Learning podcast, Dr. Kristal Walker described AI as “more of an accelerator than a replacement,” freeing teams to focus on storytelling, application, and coaching.

Others pointed to data as a critical enabler. Personalized recommendations, skills assessments, and adaptive learning paths can help L&D move beyond one-size-fits-all solutions—if teams are prepared to interpret and act on the insights responsibly. As Learning Strategist Robyn DeFelice noted in that same episode, technology alone isn’t the transformation. The real shift comes when learning teams use data and tools to become stronger business partners, aligning learning with performance outcomes.

Looking Ahead: Using Learning Technology with Intention

Heading into the new year, the message from Powered by Learning guests is clear: technology is no longer optional in L&D—but intention is what makes it effective. AI can accelerate creation, simulations can deepen practice, and mobile platforms can expand access. Yet none of these matter without clear goals, thoughtful design, and a relentless focus on performance.

The challenge for learning leaders in the year ahead won’t be finding new tools. It will be deciding how—and when—to use them to create learning that truly changes behavior.

 

Listen to these related podcast episodes:

Smarter Call Center Training: How AI Is Changing the Learning Experience with Sheldon Thomas

Rethinking Learning with Karl Kapp’s Action-First Design

Microlearning That Drives a Culture of Safety, with Luke Lazar and Leslie McRobbie

Episode 100: AI, Data, and the Future of Learning & Development with Robyn DeFelice and Dr. Kristal Walker 

By Susan Cort, Director of Marketing & Public Relations