Here’s a look at what we learned from their discussion.
It turns out that L&D teams are not just dabbling with one or two AI platforms. They're exploring a wide range of tools to supercharge their workflows. Our PowerMembers shared their experiences with everything from the familiar ChatGPT and Copilot to specialized tools like Beyond for video and Articulate's own AI functionality.
One interesting point came up: the interface and user experience of these tools matter. One attendee mentioned a preference for older AI interfaces, citing they offered more flexibility and control over the generated images compared to newer, more restrictive systems. This reminds us that as AI evolves, we need to paay attention not just to what a tool can do, but how it feels to work with it.
When it comes to creating content, AI isn't just for writing first drafts. Our group discussed a variety of approaches for using AI to jumpstart the creative process.
Some prefer a conversational style, treating the AI like a brainstorming partner. Others find more success with structured prompts, using frameworks like Role-Task-Format (RTF) or Content-Ask-Rules-Examples (CARE) to get more precise outputs. The consensus? Being intentional with your prompts, and even giving the AI a specific persona—like "a marketer creating content following Seth Godin's philosophy"—can dramatically improve the results. This moves us from generic outputs to targeted, high-quality content that still reflects a specific vision.
One of the most thought-provoking discussions centered on a critical question: should we disclose the use of AI tools in our e-learning courses?
On one hand, there's concern that transparency might devalue the content in a learner's eyes. Will they think the course is less authentic or high-quality if they know AI was involved?
On the other hand, a compelling argument was made that disclosure could show a company’s commitment to innovation. It demonstrates that the L&D team is on the cutting edge and leveraging the best tools available.
There's no single right answer, but this conversation highlights the importance of not only what we create but how we create it. Perhaps the solution lies in specifying which sections were AI-generated and then challenging learners to improve upon them, turning transparency into a learning opportunity.
Of course, it’s not all sunshine and perfect first drafts. Our discussion also touched on the real challenges of using AI. For small teams, AI can be a game-changer for productivity, but questions about ROI and accuracy, especially in highly specialized fields like healthcare, remain. One participant noted the difficulty in getting AI to generate accurate clinical images for training, a stark reminder that these tools aren't a one-size-fits-all solution. Another noted how AI bias can creep into content through generalizations, leading to biased outcomes.
This is a new frontier, and we're all still learning how to navigate it. The conversations we have today will shape the L&D landscape of tomorrow.
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