ICharter’s recent playbook, “AI Educators: Transforming Manager Development with Artificial Intelligence,” outlines strategies and tools for adopting AI to foster proficiency-based learning among workplace leaders and prepare them for the complex array of challenges facing mid-management roles today.
Egle Vinauskaite is co-founder of Nodes, an AI learning consulting firm. Recently, Vinauskaite and co-author Donald H. Taylor published a white paper on adopting AI in learning and development (L&D), based on a survey of over 300 respondents and case studies from global companies such as Bayer, Ericsson, Leyton, and HSBC.
We reached out to Vinauskaite to learn more about the report's findings and understand the most promising use cases for AI in workplace learning. Below are excerpts from our conversation, edited for length and clarity.
For a recent white paper, we spoke to employees and leaders about how they are using AI to learn in the workplace. What were the most common use cases?
The most common use cases for L&D are, unsurprisingly, content-related. The top three were content creation, learning design, and topic research. Translation wasn't in the top three, but it was still very popular. None of these use cases are particularly surprising. Typically, when finding use cases for AI, especially generative AI, you map out the process to find the parts that consume time and resources.
Content creation has historically taken up a huge amount of L&D time. When we think about using AI for learning, content is commonly used in all kinds of learning, from workplace L&D to higher education. In the workplace, content is used as a proxy for skill development and performance support. When we think about the content we create in organizations, on the one hand, we want people to develop skills. For example, if they don't know how to give feedback or how to interview, content is provided to help them learn that.
And then on the other end of the spectrum we have performance support, which is not a skill that you need to learn, but something you just need to do and get the job done. So in real life, your computer breaks so you might Google “why does it make that noise?” This would be performance support because you wouldn't need to learn how to fix a computer at work. Other examples would be things related to administrative tasks, like accessing a database or how to request time off – things you don't necessarily need to learn.
What is the potential role of AI in skills development and performance support?
AI gives us the opportunity to move away from content because it can do certain things that content no longer needs to do. Before generative AI, we used content for everything. So, if you need to learn how to interview, we have content on that. Videos here, or articles here. If you need help onboarding new employees, we have courses that will give you everything you need to know.
This isn't a good thing, because in skill development, content is just the first step. You need to practice the skill, get feedback, reflect on it, and repeat this process over and over again until you can master it and execute it. Content was an escape route. Because if you give a hiring manager some interview questions but don't follow up afterwards, you're not really good. Whereas for performance support, employees typically Google these questions; they're not going to the company's learning management system (LMS) to find a course on what they need help with. So the content that was created previously generally didn't serve either need very well.
What AI does is not force people with loads of content, but instead gives them opportunities to practice, such as creating little coaching buddies to help them think through certain decisions or practice having difficult conversations. For example, if I'm a salesperson, I might teach a bot to play a difficult customer and try to solve their questions. So AI can do a lot of the heavy lifting on the skills side.
On the performance support side, Copilot allows you to actually do performance support where you can ask any question that's on your mind, and you get inside information about the company, just like Chat GPT does. You get those answers when you need them. That's true performance support.
In your research or reporting, have you come across any particularly interesting case studies related to manager training?
One case study was capturing and making useful in-person training events conducted by a global events company. The company primarily does in-person training and ran a pilot with senior leaders. Typically with in-person training, even if you have a great facilitator, once the training is over, that's it. The content is gone, people go back to work, and the transfer of learning becomes questionable. The fun continues, but that's it.
They decided to use AI to capture a live, in-person event where people sat in a classroom. After the event, they set up the AI to send each managing director a summary of what was discussed and a list of action items. Managers also received a summary so they could pick out some of the themes that emerged from the discussion. This way, the themes don't just stay in the classroom, but are something they can actually take into the real world.
We've also started building a knowledge base with the captured content submitted at the live events, which becomes part of our corpus. Similar to ChatGPT, you can actually start a dialogue. You can start with simple questions like, “What was the sentiment in the room? What were people's main concerns?” You can also ask them to do more complex tasks, like deep analysis of the conversation. This is where we stopped because the case studies are still new, but we can speculate and imagine where it might lead. You can then reuse the content and the questions people asked to create different courses and nudges for people in your function. In fact, that content is searchable and useful, both for persistence and for continuing to learn through iteration.
Download Charter's full playbook Explore more case studies, frameworks, and advice for incorporating AI into manager learning and development. ValenceThanks to for sponsoring this playbook.
