In today’s tech-driven world, knowledge is just a click away. As a result, learning has never been more accessible. Whether it’s listening to a podcast on personal finance or watching a video on networking tips, we have endless opportunities to learn something new every day. In the workplace, learning can come in the form of formal training programs or more informal moments — such as a conversation with a peer about helpful shortcuts in a spreadsheet or a sales manager offering feedback to a team member after a client call.
Although employees are constantly absorbing new information, turning knowledge into improved behaviors isn’t easy. Without ongoing reinforcement, much of what we learn fades over time, making it difficult to turn new knowledge into new habits and behaviors.
Here, we’ll consider how artificial intelligence (AI) can help support learning reinforcement to drive sustainment and, in turn, behavior change.
Learning Reinforcement: What It Is and Why It Matters
Chris Knotts, knowledge engineer at SoftEd and the instructor of Training Industry’s AI for Training Managers Certificate, says that in the adult learning world, learning reinforcement refers to “any mechanism or tool that helps to internalize and solidify what has been learned at an intellectual level.” Acquiring information can happen “very quickly,” Knotts says, but true learning is about developing the skills and habits necessary to apply that knowledge effectively. This takes time and requires continuous reinforcement. Knotts explains, “People are creatures of habit, and so learning reinforcement is all about shaping new habits or changing old habits to create new behaviors [and] new patterns of thinking.”
Samantha Straede, CPTM, a certified professional coach and learning and development (L&D) leader, says reinforcement is about finding ways to strengthen the knowledge that employees have gained during training.
Learning reinforcement ensures that employees can consistently apply what they’ve learned on the job. In this way, reinforcement helps drive training’s return on investment (ROI): After all, Straede explains, L&D is an “intentional investment” in business success. Even if training’s business impact isn’t always immediate, L&D often influences key factors, such as managerial performance, that are essential for long-term business growth, Straede says.
Knotts agrees that reinforcement is essential in driving long-term behavior change — especially as today’s world is “a dynamic place that’s full of change.” L&D isn’t focused on learning for learning’s sake. Rather, “In our world, we’re interested in learning as a tool for enterprise and business outcomes, and if you’re in a nonprofit sector, maybe [for] a mission-driven outcome.” Thus, “being able to build the muscle of behavior change, especially to be able to change behavior quickly and competently, is a super necessary skill at the organizational level.”
4 Ways to Use AI for Learning Reinforcement
Here are a few ways you can leverage AI to support learning reinforcement in your organization:
- Personalized and Adaptive Support
Recent Training Industry research found that 39% of learning leaders are using AI for personalization, making it a top use case for AI in L&D. AI tools can personalize reinforcement by analyzing learner behavior and data to provide adaptable learning paths, tailored feedback and relevant resources.
For example, Straede explains, AI-powered learning platforms and systems can track learners’ progress in quizzes or modules, recognize when a learner is struggling and recommend additional training or resources to improve their skills.
The conversational nature of generative AI tools also supports a personalized learning experience. This is key for reinforcement, as Knotts explains, “If you’re really going to reinforce [learning] and engage with a learner, you have to understand what is really important to that learner, and I think a lot of times we make assumptions about that.” AI can engage in direct conversations with learners, gathering information about their priorities and challenges. This allows it to recommend more relevant learning materials, resulting in more targeted — and effective — reinforcement.
- Role-Play and Simulations
Another way to leverage AI for learning reinforcement is through AI-powered role-play and simulations. These immersive learning opportunities allow learners to practice their skills in a low-stakes, yet realistic, environment. Role-playing with an AI-powered avatar can also feel less intimidating than practicing with a human, helping learners feel more comfortable as they develop new skills.
Many learning providers now offer AI-powered role-play and simulation training solutions. For example, Unboxed Training & Technology’s “Mentor” tool allows learners to practice having conversations based on real-world scenarios, and provides instant, real-time feedback. And with Attensi’s AI-powered simulation and role-play solution REALTALK, users can practice and improve their skills across three key areas: coaching and feedback conversations, customer experience and sales conversations.
- Microlearning, Reminders and Nudges in the Flow of Work
Microlearning is another way AI-powered tools can support reinforcement. AI can identify knowledge gaps and deliver targeted, bite-sized learning in employees’ moment of need.
AI can also deliver nudges and reminders to reinforce learning by prompting employees to apply new skills and revisit important concepts. Leveraging spaced repetition and behavioral insights —such as understanding learner preferences and when learners are most likely to forget information — AI can help support reinforcement and on-the-job application.
- On-the-Job Coaching
According to Training Industry’s e-book, “The AI Advantage in L&D: A Strategic Guide,” AI-driven coaching tools “enable the seamless integration of video-based evaluation models, allowing trainers to simply drop in a video and generate data on various attributes such as engagement, persuasive arguments, information sharing and eye contact” to offer learners immediate, targeted feedback. This real-time support can help learners identify areas for improvement and receive personalized guidance.
AI-powered coaching tools — such as ELB Learning’s Rehearsal, Synthesia, Lepaya and others —provide learners with opportunities to practice and grow their skills for increased retention and on-the-job application over time.
Coupling AI With Human Support and Connection
AI can undoubtedly help support learning reinforcement efforts — especially at scale. However, if possible, consider supplementing AI-driven reinforcement with a human component. Straede often sees one-on-one and group-based, in-person reinforcement efforts have a higher impact because “people don’t feel alone” in the challenges they’re facing.
When learners collaborate to discuss challenges, ask questions and brainstorm solutions, they gain essential support and a sense of community, both of which enhance the learning experience.
Final Thoughts
From personalized support to immersive simulations and on-the-job coaching, AI is a powerful tool to support learning reinforcement and drive behavior change. By pairing AI-driven reinforcement with human-focused efforts, L&D leaders can create a well-rounded approach that reinforces learning, builds connection and drives long-term behavior change.
View the brochure for Training Industry’s AI Essentials for Training Managers Certificate program to learn how to integrate AI in your training programs.
