Gen AI Promise for Associations Depends On a Learning Culture Revolution
In today’s rapidly evolving landscape, associations face the dual challenge of adapting to technological advancements while upholding their commitment to member service and industry leadership. Generative AI (Gen AI) presents both an opportunity and a challenge in this context. A true Gen AI learning culture within an association transcends mere training programs. It’s about weaving a deep appreciation for continuous growth and development into the very fabric of the organization – impacting staff, volunteers, and even members. This means fostering an environment where learning about and leveraging Gen AI is integrated into daily operations and viewed as essential for both individual and collective success. Such a culture fuels curiosity, innovation, and adaptability – crucial traits for associations navigating the complexities of the digital age and setting standards for their respective industries.
Five Pillars of a Gen AI Learning Culture Tailored for Associations
Building a robust Gen AI learning culture, especially one designed to empower associations to leverage the transformative potential of this technology, requires a strategic approach. Here are five key pillars:
- Strategic Alignment with Association Goals: Gen AI learning initiatives must be inextricably linked to the association’s overarching mission and strategic plan. Simply introducing Gen AI tools without a clear understanding of how they contribute to member value, operational efficiency, or industry leadership will result in limited adoption and minimal impact. For instance, if an association aims to enhance member engagement, Gen AI learning programs should focus on using natural language processing for personalized communications, sentiment analysis for understanding member feedback, and AI-powered tools for creating engaging content for chapter meetings and section-specific initiatives. This connection between Gen AI learning and tangible association outcomes motivates staff and volunteers, demonstrating the value of their development and fostering buy-in across the organization. When staff and volunteer leaders see a clear link between mastering Gen AI and the association’s strategic objectives—such as increased member retention, innovative program development, or enhanced advocacy efforts—they are more likely to engage fully in the learning process. This alignment creates a sense of purpose and direction, making Gen AI learning more meaningful and motivating while managing risks.
- Leadership Advocacy and Participation: The executive director, board members, and top staff must champion Gen AI learning from the top down. Active participation in Gen AI workshops, public endorsement of Gen AI initiatives, and open discussions about the potential and ethical considerations of Gen AI send a powerful message that continuous improvement in this critical area is a priority at all levels. When association leaders actively participate in Gen AI learning initiatives, perhaps by exploring prompt engineering techniques to improve board communications or discussing the implications of large language models for industry codes of conduct, it demonstrates that learning is not just an expectation for staff but a shared value. This visible commitment from leadership encourages rank-and-file staff and chapter-level volunteers to follow suit, as they see that Gen AI learning is valued across the entire association ecosystem.
- Collaborative and Inclusive Learning Experiences: Gen AI learning should be a shared and collaborative journey, involving staff, volunteers, chapters, and sections. Creating opportunities for cross-functional teams to learn from each other through peer-led Gen AI workshops, collaborative projects involving staff and chapter leaders, and internal Gen AI hackathons fosters a sense of community and shared purpose. This collaborative approach enhances learning by allowing staff and volunteers to share Gen AI knowledge, discuss implementation challenges, and learn from diverse perspectives. Consider creating special interest groups within sections or larger chapters focused on Gen AI applications relevant to specific member demographics. Learning about Gen AI should be a collective endeavor where everyone within the association can support and learn from each other.
- Accessible Resources and Knowledge Sharing: Providing easy access to relevant Gen AI resources is essential for a thriving learning culture. This includes online courses on prompt engineering, fine-tuning models for association-specific tasks, and deploying Gen AI solutions ethically and responsibly. Access to documentation, research papers, and industry best practices related to Gen AI should also be readily available. Internal wikis or knowledge bases dedicated to Gen AI can serve as central repositories for information, code snippets, and reusable prompts tailored for association use cases. Regular knowledge-sharing sessions, perhaps featuring chapter leaders who have successfully implemented Gen AI solutions, empower staff and volunteers to learn at their own pace and find the information they need. These resources provide a platform for staff and volunteers to ask questions, share insights, and access information relevant to their roles and development within the context of Gen AI, fostering a culture of continuous learning across the association.
- Recognition and Celebration of Gen AI Achievements: Acknowledging and celebrating Gen AI learning achievements reinforces the value of continuous development in this critical area. This can range from simple shout-outs for innovative Gen AI use cases during staff or chapter meetings to formal awards recognizing individuals, teams, or chapters that have successfully implemented Gen AI solutions that benefit the association and its members. Recognizing and celebrating successes and milestones in Gen AI learning is a powerful way to reinforce the value of ongoing education. These celebrations do more than just reward those who have made significant strides in their Gen AI learning; they also highlight the association’s commitment to growth, development, and innovation in this vital technological area, inspiring others to engage more deeply with Gen AI.
Case Study: Implementing a Gen AI Learning Culture at a Medical Association
As a consultant specializing in organizational development and Gen AI implementation, I recently partnered with a national medical association seeking to integrate Gen AI into its operations and member services. The association was facing challenges in leveraging Gen AI to enhance its educational programs, advocacy efforts, and member engagement. They were also struggling to get both staff and their extensive network of volunteer leaders on board with their Gen AI initiatives. My role was to guide them in building a sustainable Gen AI learning culture that spanned across the national office, chapters, and sections.
My approach began with a comprehensive needs assessment, involving surveys and interviews with staff, board members, chapter leaders, and section representatives to identify skill gaps, learning preferences, and opportunities for Gen AI application. Based on this assessment, we developed tailored Gen AI learning paths for different roles and levels within the association. Staff members received training on using Gen AI to streamline administrative tasks, analyze member data, and create personalized content. Chapter leaders participated in workshops focused on using Gen AI to enhance local events, recruit new members, and engage existing ones through targeted communications. Section members explored how Gen AI could be used to advance research and best practices within their specific areas of expertise.
I worked closely with the association’s executive director and board to ensure their active participation in Gen AI workshops and strategic discussions. The executive director and board members engaged in prompt engineering workshops and discussed the ethical implications of using Gen AI in medical advocacy and member communications, demonstrating their commitment to the initiative. We established Gen AI learning circles involving staff, chapter leaders, and section representatives, along with an online forum to facilitate knowledge sharing and collaboration on Gen AI-driven projects across the association. We also developed resources that chapter leaders could use to facilitate similar workshops at the local level. Finally, we implemented a system for recognizing Gen AI learning achievements through digital badges, features in the association’s newsletter, and an annual awards ceremony showcasing innovative Gen AI applications developed by staff, chapters, and sections.
Over 12 months, the medical association experienced significant improvements. Staff members became more proficient in using Gen AI tools, leading to increased efficiency in operations and more personalized member services. Chapter leaders reported improved member engagement and satisfaction due to more targeted communications and locally relevant programming facilitated by Gen AI. Section-driven initiatives leveraging Gen AI resulted in the development of innovative resources and best practices for members. Staff time devoted to administrative tasks was reduced by 25%, allowing for more focus on strategic initiatives. Member engagement, measured through event attendance and online interactions, increased by 28% across the association, while member retention increased by over 20%. Leadership’s visible commitment and the alignment of Gen AI learning with the association’s strategic goals fostered a culture of continuous improvement and innovation. The collaborative environment facilitated by Gen AI learning circles and online forums led to the development of member-centric solutions powered by Gen AI, further solidifying the association’s position as a leader in its field.
Key Takeaways for Association Leaders
Building a sustainable Gen AI learning culture is not a one-time project but an ongoing journey that requires commitment, investment, and adaptability. Association leaders must prioritize Gen AI learning by making it a strategic imperative and allocating resources accordingly. They must also lead by example, actively participating in Gen AI learning activities and championing development programs related to this technology across all levels of the association, including chapters and sections. Fostering collaboration by creating opportunities for staff, volunteers, and members to learn from each other about Gen AI is equally crucial. Finally, leaders must measure the impact of Gen AI learning initiatives, tracking their effectiveness and making adjustments as needed to ensure alignment with the association’s evolving needs and goals. By embracing these principles, associations can create a culture where Gen AI learning is not just valued but also drives innovation, enhances member value, and ensures long-term success in the age of intelligent machines.
Key Take-Away
The Gen AI promise for associations lies in fostering a learning culture where leaders, staff, and volunteers align strategy, collaboration, and innovation to drive member value, adaptability, and long-term success. Share on XImage credit: Pavel Danilyuk/pexels
Dr. Gleb Tsipursky was named “Office Whisperer” by The New York Times for helping leaders overcome frustrations with Generative AI. He serves as the CEO of the future-of-work consultancy Disaster Avoidance Experts. Dr. Gleb wrote seven best-selling books, and his two most recent ones are Returning to the Office and Leading Hybrid and Remote Teams and ChatGPT for Leaders and Content Creators: Unlocking the Potential of Generative AI. His cutting-edge thought leadership was featured in over 650 articles and 550 interviews in Harvard Business Review, Inc. Magazine, USA Today, CBS News, Fox News, Time, Business Insider, Fortune, The New York Times, and elsewhere. His writing was translated into Chinese, Spanish, Russian, Polish, Korean, French, Vietnamese, German, and other languages. His expertise comes from over 20 years of consulting, coaching, and speaking and training for Fortune 500 companies from Aflac to Xerox. It also comes from over 15 years in academia as a behavioral scientist, with 8 years as a lecturer at UNC-Chapel Hill and 7 years as a professor at Ohio State. A proud Ukrainian American, Dr. Gleb lives in Columbus, Ohio.