You may not be surprised to learn that 60 percent of Learning and Development (L&D) teams are using generative artificial intelligence (genAI) in some capacity, whether to create content, aid with performance support, or identify skills gaps. And an even larger portion of the industry is considering using AI but maybe hasn’t made the jump yet.
But as we’re seeing AI’s popularity and adoption continue to grow, we’re also seeing its role shift beyond simple content production. Many L&D and HR teams are realizing that AI can help you not only create content more efficiently but also create higher quality content.
For those who haven’t jumped onboard with AI quite yet, appreciating the ways AI enhances personalization, efficiency, and scalability is crucial in overcoming the most common barriers to AI adoption within L&D.
And as we continue to see the technology improve, genAI will pave the way for more immersive and dynamic learning experiences within L&D, ultimately allowing organizations to train, upskill, and reskill their talent more effectively.
Overcoming AI Adoption Challenges Within L&D
Although we’ve seen a rise in L&D teams leveraging AI in their content creation processes, adoption isn’t at 100 percent. We typically see this hesitancy for a few reasons.
First and foremost, the nature of AI can make some teams nervous—understandably so. The complexities of AI’s long-term implications remain largely unknown, generating both intellectual intrigue and uncertainty.
However, our current AI solutions should be viewed as an enhancer rather than a replacer. AI allows L&D teams to make higher-quality content faster and more efficiently, in addition to making their content more interactive and engaging than ever before. It’s a tool that can help your team succeed, and the more you understand how it can be used, the better prepared you are for a future in which these tools are commonplace.
Secondly, the question of data security can be a limiting factor for some teams looking to add an AI tool to their tech stack.
That said, it’s possible to onboard new AI tools while still remaining committed to high ethical and data privacy standards. For instance, many AI video tools have strict standards when it comes to who’s allowed to create AI avatars. Additional regulation in this space—such as the EU AI Act—will continue to ensure transparency and ethics within the industry at large. Further, leaders in the AI video space don’t train AI models on your input data, and don’t allow anyone else access to the content you create.
Finally, the last challenge that can limit adoption is concerns about content quality and authenticity. The top priority of most L&D teams is to create high-quality learning content that drives positive skill development, knowledge acquisition, or other learning outcomes. However, the idea of adding AI avatars to content can create concerns about the impersonal nature of the material, since viewers are learning from an avatar rather than a human instructor.
I’d argue that, in many ways, AI breaks down the boundaries for personalization imposed by traditional video production—actually allowing for higher levels of customization. After all, traditional videos require a one-size-fits-all approach to content creation. But with AI, you can create videos with scripts customized to different audiences at scale. You no longer have to create the same content for everyone. Instead, you can personalize video scripts on a hyper-individual level, while still producing content at a rapid pace.
Benefits of AI in Workplace Learning
Adding AI into your workplace learning tech stack has numerous benefits, both immediate and in the long term.
On an immediate level, implementing a software such as an AI video solution will lead to a direct reduction in your video production costs, increased efficiency for your team, and more accessible training, since you now can add subtitles and translations at no additional cost.
Let’s say it costs your team around $1,000 to produce a minute of video, taking into consideration the costs of filming, editing, and other expenses. Furthermore, creating a single video might take two to three weeks of work, since you’ll need to find a filming location, hire actors, and manually edit the footage.
Instead, an AI video tool allows you to create content of the same professional caliber in minutes. However, since you won’t need to rent equipment, hire actors, or secure a filming studio, your fixed costs involved in creating content are a fraction of what they were before. Once you have a license to an AI video tool, that’s your only expense, making the entire process a lot cheaper.
The State of New Mexico experienced these benefits firsthand after implementing AI video tool Colossyan, as they began saving 70 percent of its content production costs and 50 percent of its time.
When we take a step back and examine the long-term benefits, adding AI into your L&D tech stack gives you access to more scalable learning solutions that support more dynamic skill development. AI avatar video features such as branching scenarios allow for more dynamic learning experiences, and video analytics provide more insight into how you can optimize your content for maximum impact.
This is just the beginning: As AI avatar technology continues to evolve, the benefits and use cases will only continue to expand.
Looking Forward: 2025 and Beyond
Since the inception of AI video, solution providers primarily have been focused on delivering one-way video communication capabilities. In 2024, we saw these videos become more interactive, as some platforms began adding features such as branching scenarios or built-in video quizzes.
But in 2025, we’ll begin to see AI video content that’s not just interactive but also immersive. This is likely to start with conversational avatars—in other words, avatars capable of responding to you in real time.
Although static video has numerous possibilities and use cases, conversational avatars would unlock an endless set of possibilities for avatar use. And the technology is nearly there—the capabilities of genAI video have reached a point where the cost of computation and generation speed are getting closer to real time. Once we’re at that point, we’ll be able to have conversations with these digital humans instead of passively watching them.
Imagine you’re able to receive tutoring in another language with a 24/7 always-on AI avatar who can answer any question in real time. Or envision a training program where everyone is assigned a personal AI avatar assistant, who they can talk to or get feedback from at any point. Both soon will be possible.
Not only will this mark a major advancement in the accessibility of active learning methods, it also will provide a risk-free environment to practice skill acquisition. Just think of all the parts of your job that you find challenging, such as providing difficult feedback to a direct report. Soon there might be a way for you to practice those interactions with a digital human equipped with the knowledge of a large language model to provide guidance.
This isn’t just the next generation of AI chatbots, it’s the next generation of immersive experiences more broadly. And as the technology becomes more immersive, we’ll continue to see adoption grow, resulting in better learning outcomes than ever before.
