Your Association’s Survival Hinges on This Gen AI Tactic for Learning
As Generative Artificial Intelligence (Gen AI) reshapes industries, associations face unique challenges and opportunities in adopting this groundbreaking technology. For associations that guide their fields, serve diverse member bases, and support chapters and sections with volunteers, integrating Gen AI strategically can be transformative. A phased learning approach enables associations to empower staff and volunteers, streamline operations, and set industry standards, while mitigating risks and maximizing impact. You can implement a phased Gen AI learning program tailored to your own association’s complex structures, ensuring success through thoughtful planning, execution, and continuous improvement.
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Why a Phased Approach Works as a Gen AI Tactic for Learning
Associations operate at the nexus of diverse stakeholders: staff with varying technological competencies, chapters and sections with distinct needs, and members relying on the association for leadership in their industry. Implementing a Gen AI learning program across these layers presents inherent complexities. A phased approach, beginning with targeted pilot programs, allows for incremental adoption and refinement, ensuring that the rollout is as effective as it is equitable as it scales.
Pilot programs serve as controlled environments to test Gen AI tools and training methods while facilitating risk management. Associations might select staff from departments with immediate Gen AI applications, such as membership services or education, to start. For example, membership teams could use Gen AI to personalize communications, while education departments might develop AI-assisted educational resources.
By gathering feedback and iterating during the pilot phase, associations can address challenges early. Adjustments may include tailoring training materials to different roles, providing more hands-on learning opportunities, or clarifying ethical guidelines around AI use. This iterative process ensures that subsequent rollouts build on success, fostering confidence among staff and volunteers.
Key Considerations for a Phased Gen AI Learning Program
For associations, implementing a Gen AI learning strategy requires careful alignment with organizational goals and member expectations. Here’s how to do it effectively:
- Assess Technological and Cultural Readiness: Before launching the program, assess both the technological infrastructure and the openness of staff, volunteers, and members to embrace AI. For example, do chapters have the digital tools to support Gen AI initiatives? Are there concerns among members about AI disrupting their professions? Understanding these factors helps identify potential barriers and opportunities.
- Set Clear Objectives and Metrics: Define specific, measurable outcomes for the Gen AI learning program. These might include reducing staff workload by automating administrative tasks, enhancing volunteer leader support through AI-driven insights, or improving member engagement through AI-powered personalization. Clear KPIs will help evaluate the program’s success and guide adjustments.
- Develop Role-Specific Training: Create training tailored to the diverse roles within the association. Staff may need workshops on using Gen AI for operational efficiency, while volunteers might require simpler tools to improve event planning or communication with local members. Tailored content ensures relevance and practicality, encouraging adoption across all levels of the organization.
- Foster an Inclusive Learning Culture: Encourage staff and volunteers to embrace Gen AI by cultivating a culture of learning. Provide accessible resources, such as online tutorials, interactive forums, or AI mentors. Recognize the contributions of those who champion AI initiatives, ensuring inclusivity for all skill levels and roles within the association.
- Monitor Progress and Adapt: Regularly evaluate the program’s impact through surveys, performance metrics, and qualitative feedback. Use insights to refine training materials, address gaps, and anticipate future needs. For example, if feedback reveals that volunteers in chapters need mobile-friendly tools, prioritize developing user-friendly solutions for these stakeholders.
- Scale Thoughtfully: When scaling the program to other departments or chapters, maintain flexibility. Customize training for new audiences and adapt delivery methods based on the feedback and success of earlier phases. This deliberate approach minimizes resistance and ensures long-term program viability.
Leadership’s Role in Guiding Gen AI Adoption
Strong leadership is essential to the successful integration of Gen AI in associations. Leaders must articulate a clear vision for how AI aligns with the association’s mission and allocate necessary resources for training and infrastructure. For example, they could emphasize how Gen AI can help chapters better serve their members by automating routine tasks, freeing time for more meaningful engagement.
Equally important is promoting the ethical use of AI. Leaders should establish policies that address potential biases, ensure data privacy, and align AI applications with the association’s values. By modeling ethical and responsible AI practices, associations not only build trust within their ranks but also set standards for the industries they serve.
Case Study: Enhancing Member Engagement Through Gen AI
An international association for financial professionals sought to improve its member engagement using Gen AI. With a network of regional chapters and a diverse membership base, the association needed a scalable solution that aligned with its mission of advancing education and collaboration in the field.
I was hired as a consultant to guide the association through a phased Gen AI learning program. We started with a three-month pilot focused on the communications team and a small group of chapter leaders. The pilot aimed to teach them how to use AI tools for personalized member outreach, such as drafting tailored email campaigns and analyzing feedback trends.
During the pilot, we gathered feedback through surveys and workshops. Participants highlighted the need for simplified training materials and practical exercises demonstrating real-world applications. By addressing these concerns, the program became more accessible, resulting in higher adoption rates.
The pilot produced measurable results: email engagement rates increased by 25%, and chapter leaders reported saving an average of four hours per week on administrative tasks. Based on these successes, the association expanded the program to include the education department, enabling them to create AI-enhanced learning resources for members.
After a year, the association saw significant outcomes, including a 15% increase in member satisfaction scores and a 20% boost in staff productivity. By aligning the Gen AI initiative with its strategic goals, the association demonstrated its commitment to innovation while setting an example for its field.
Conclusion
For associations, Gen AI offers unprecedented opportunities to enhance operations, support chapters and sections, and set standards for their industries. A phased learning approach ensures that this transformative technology is adopted effectively and equitably across the organization. By starting small, refining through feedback, and scaling thoughtfully, associations can empower staff and volunteers to harness the power of AI, driving meaningful progress for their members and the broader community they serve.
Key Take-Away
Using a phased rollout as a Gen AI tactic helps associations adopt AI effectively, starting small, learning fast, and scaling smart. Share on XImage credit: Musemind UX Agency/Unsplash
Dr. Gleb Tsipursky was named “Office Whisperer” by The New York Times for helping leaders overcome frustrations with hybrid work and 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 Thought Leaders and Content Creators: Unlocking the Potential of Generative AI for Innovative and Effective Content Creation. 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.