In case you missed it, here’s the AI-generated summary of our first Community of Practice.

During the first session of AI + Talent Development Community of Practice, there was active participation and engagement of the community members in exploring the intersection of AI and talent development in the context of L&D. Facilitators shared the conversation themes and questions from their respective breakout rooms. 

Breakout group #1

Frank Calero shared that his group’s discussion mainly focused on implementing AI and maintaining a laser focus on specific outcomes while addressing security concerns. The key question that was raised was “How to ensure that AI tools are directed towards achieving secure and specific outcomes?”

Markus Bernhardt acknowledged the broad spectrum of AI applications and their varying uses. He emphasized the importance of identifying a specific problem to address and then selecting the appropriate AI or machine learning tool to achieve the desired outcome securely. Markus highlighted the need to engage in deep discussions with team members and vendors, asking relevant questions and seeking convincing answers. He stressed the significance of exploring multiple providers and learning from each conversation to build knowledge and find the right tool. Markus also mentioned the importance of considering security features and not succumbing to hype when implementing AI.

Danielle further built upon Markus’s response and asked for examples of critical questions that should be asked. Markus explained that the questions would depend on the specific AI application being considered, such as chatbots or adaptive learning systems. He mentioned the need to inquire about information requirements, input and output processes, data storage, and utilization. However, he cautioned that it’s essential to tailor the questions to the specific context to ensure they are helpful to as many people as possible. 

Breakout group #2

Xaviera Sanchez’s group shared two questions with Markus from their AI + Talent Development Community of Practice breakout room. The first question focused on how to handle client information while utilizing AI tools to generate content and voice-over products. The second question addressed strategies for companies to implement and adapt faster than current legislations and regulations. Markus emphasized the importance of understanding how AI operates within systems, including data storage, server locations, and feedback loops. He also discussed the potential biases embedded in AI systems, highlighting the need for discussions on biases and the opportunity for societal progress. Markus mentioned that training data sets inevitably contain biases due to the nature of the internet.  

Breakout group #3

During the discussion, Jelena Marjanovic’s AI + Talent Development Community of Practice group raised the topic of customization in AI and learning content. She questioned how far we are from using AI to automatically adapt learning solutions to meet the changing needs of learners. 

Markus responded by distinguishing between adaptive learning and generative AI. He explained that adaptive learning engines currently personalize the learning journey by selecting and delivering content from pre-designed materials, while generative AI, such as large language models, can create new text and images but still lacks the ability to apply the signaling principle and integrate words and images effectively. Markus emphasized that human-level design remains the gold standard in learning and that AI tools can support tasks like answering questions, creating summaries, or building slide decks, but they cannot replace the importance of good learning design, contextualization, and practice. Danielle acknowledges Markus’s points and highlights the role of instructional design, mentioning an example where AI was used to create a fake article and image, illustrating that AI should be viewed as a tool rather than a substitute for human involvement.

Breakout group #4

Luke Goodwin shared that his team had a positive discussion in the AI + Talent Development Community of Practice. He discussed various topics, including trying out new things and the importance of generative learning. One key question that emerged was how to shape learning and development (L&D) to stay ahead of AI and maintain control over AI-driven learning. Luke emphasized the need for humans to take the lead in designing excellent learning experiences.

Markus highlighted the rapid pace at which AI and learning technologies are advancing, emphasizing the urgency for individuals to stay updated and engage in conversations with experts and vendors. He stressed the importance of seeking out learning opportunities, networking, and having meaningful discussions to understand the current landscape of AI in learning. Markus mentioned that neglecting to explore AI tools and technologies would result in falling behind in the future of work.


Danielle acknowledged the significance of the AI + Talent Development Community of Practice in fostering collaborative discussions and sharing ideas. She expressed excitement about the valuable questions raised by participants and the need to generate further meaningful inquiries within the group. 

During the conversation about AI and talent development, Raymundo Jimenez expressed his skepticism and asked for updated questions to explore AI further. Markus acknowledged the need for critical questioning and emphasized the importance of aligning AI solutions with specific goals and contexts. He advises questioning vendors and innovators and encourages informed decision-making. 

Danielle highlighted the ongoing nature of the conversation and invites participants to continue engaging in future sessions and accessing relevant resources. Markus expresses gratitude for the discussion, offers support, and encourages networking within the AI + Talent Development Community of Practice. Danielle echoes the sentiment and emphasizes the collective effort to enhance understanding and embark on the AI journey in learning and development.