Closing the GenAI Data Hole in L&D: Webinar Insights from Brandon Corridor Group and Litmos

In a latest webinar with Brandon Corridor Group’s Senior Vice President and Senior Analyst, Claude Werder, leaders from Litmos mentioned the influence of generative AI (GenAI) on Studying and Improvement (L&D). The webinar, titled “Pressing: Shut Your GenAI Data Hole Earlier than It’s Too Late,” explored the potential of GenAI, tips on how to mitigate AI-related dangers, and the trail to success for L&D groups as they adapt to this new period.

Tommy Richardson, Litmos’ Chief Product and Know-how Officer, centered on the significance of creating and following clear organizational AI insurance policies, and utilizing AI to enhance private workflows. Dr. Jill Stefaniak, Litmos’ Chief Studying Officer, mentioned how L&D professionals can proceed to heart learners whereas leveraging AI instruments, and the significance of incorporating suggestions from all stakeholders when implementing AI in L&D applications.

To observe the complete webinar, view the recording right here. Learn on for key takeways…

Takeaway #1: AI is right here to remain – L&D professionals must adapt to its presence.

Generative AI is making a big influence on Studying and Improvement (L&D) methods, with 89% of organizations anticipating vital influence on L&D from AI. Regardless of the considerations about price, complexity, ethics, and information safety, most studying professionals are snug with the concept of AI-generated content material. Dr. Stefaniak and Richardson each emphasised that this know-how is “right here whether or not we prefer it or not” and that L&D professionals ought to discover the potential of AI.

Dr. Stefaniak highlighted the significance of protecting learners at the point of interest of educational design whereas exploring AI. She mentioned, “Our learners aren’t going to care if the content material was generated by AI. They’re going to care. Is it related? Is it helpful? Is it serving to them?”

Then again, Richardson steered that one of the simplest ways to combine AI into one’s L&D technique is to depend on present distributors who’re probably already utilizing AI. He mentioned, “Decide a vendor that’s in that house that’s already solved these issues. I feel what you’ll discover is that they’ve dealt with all that for you.”

Takeaway #2: AI can deal with L&D ache factors and personalize studying.

AI has the potential to handle a number of L&D ache factors, from content material creation to learner engagement. It could actually assist create extra environment friendly coaching, expedite educational design processes, and provide extra personalised content material. Particularly, generative AI can be utilized for content material creation, personalised studying suggestions, and even high quality checks for accessibility and plagiarism.

“I feel that my key takeaway,” Richardson acknowledged, “is unquestionably apply it to your private aspect. AI looks like it was kind of made for L&D. And actually, whether or not you’re a learner or a supervisor or an admin or a content material creator, no matter what your function is, you’re probably going to have some optimistic makes use of [for AI tools] sooner or later.”

Dr. Stefaniak added that “We’re nonetheless comparatively within the infancy section of utilizing generative AI to help L&D,” however agreed concerning the rising reputation of AI instruments for studying. “We see increasingly more organizations and firms counting on generative AI for content material creation.”

Takeaway #3: Adopting AI in L&D requires cautious planning, collaboration, and the best insurance policies.

Efficiently integrating AI into a corporation’s L&D technique requires correct planning, intra-organization collaboration, and the best insurance policies. Addressing points equivalent to price, complexity, information privateness, and moral issues upfront can stop potential issues down the road. Furthermore, getting suggestions from totally different stakeholders can result in a stronger infrastructure to help AI initiatives.

Richardson suggested, “It’s vital to outline what these insurance policies are, outline what these workflows are, and collaborate throughout departments to ensure everyone is aware of what these insurance policies are.” Likewise, Dr Stefaniak steered scaling efforts and doing pilot testing to determine what works and what doesn’t. She mentioned, “Don’t be afraid to get suggestions. [Get] suggestions from totally different stakeholders as you’re experimenting with other ways you would possibly be capable of undertake AI into your organizational technique.”

Need extra insights from this dialog? Watch the complete recording of “Pressing: Shut Your GenAI Data Hole Earlier than It’s Too Late“.