Associations Unleash Gen AI Success Through Team Collaboration

The emergence of generative AI (Gen AI) presents associations with transformative opportunities to optimize operations, enhance member engagement, and elevate the value they deliver to their professions. However, simply acquiring Gen AI tools is insufficient to achieve its full potential. True transformation requires cultivating a culture that empowers staff and volunteers to experiment, iterate, address challenges, manage risks, and uncover innovative applications of this technology to advance the association’s mission.

At the heart of successful Gen AI adoption is a balance between autonomy and support. Autonomy allows teams—comprising staff, volunteers, and even more engaged members—to explore solutions tailored to their unique needs and operational contexts. Support ensures alignment with strategic goals, providing necessary resources (e.g., access to relevant data, technical expertise, and computing power), and establishing accountability frameworks. Together, these factors enable associations to explore Gen AI’s potential while safeguarding against risks.

Striking the Balance for Gen AI Success

The initial step in fostering a Gen AI-friendly culture involves dismantling restrictive structures that stifle creativity and innovation. For associations, this may mean reevaluating traditional approval processes or hierarchical decision-making that can slow experimentation. While oversight is necessary—especially given ethical considerations and data privacy concerns—excessive micromanagement can discourage both staff and volunteers from exploring new ideas.

Association executives and board members must aim for a balance between providing clear strategic direction and granting teams the latitude to experiment. Trust is foundational here; association leaders must demonstrate confidence in their teams to explore solutions that align with the organization’s mission and objectives.

A practical way to achieve this balance involves structured frameworks that set clear objectives, milestones, and evaluation criteria without dictating the methods or tools to be used. For example, an association might establish a goal of improving member retention through more personalized engagement. Teams of staff and volunteers could then experiment with Gen AI tools, such as natural language processing for personalized communications or predictive analytics to identify at-risk members. This approach fosters ownership, motivation, and engagement among those working on these projects.

Gen AI Success Through Cross-Functional Collaboration

While individual autonomy is crucial, Gen AI success thrives on cross-functional collaboration. Associations are uniquely positioned to leverage the diverse expertise of their staff, volunteers, and members. Bringing together teams with varied skill sets—such as data analysts, IT professionals, program managers, chapter leaders, and subject matter experts—can unlock innovative solutions.

Cross-functional collaboration not only fosters innovation but also helps identify and mitigate risks. For example, membership teams might provide insights into recurring member pain points, while IT teams ensure that Gen AI solutions align with data security requirements. Program managers and chapter leaders can offer perspectives on how solutions will work in varied geographic or professional contexts. Together, these perspectives ensure that Gen AI initiatives are both innovative and practical.

To foster collaboration, associations should create mechanisms for regular communication and knowledge sharing. These can include:

• Open forums for brainstorming and sharing findings from Gen AI experiments.
• Feedback loops to capture lessons learned and adjust strategies as needed.
• Cross-departmental learning sessions to disseminate knowledge and foster alignment.

Such initiatives encourage transparency, open communication, and collective problem-solving, ensuring that successes and challenges inform future efforts.

Client Case Study: Enhancing Member Engagement

As a consultant specializing in association innovation, I recently worked with a national professional association of over 10,000 financial professionals seeking to enhance member engagement and streamline administrative processes using Gen AI. The association faced challenges such as declining event attendance, underutilized member benefits, and inefficiencies in staff-volunteer coordination.

We initiated the engagement by conducting a survey, followed by a series of focus groups and town halls with staff and volunteer leaders to identify pain points and opportunities for improvement. Based on these discussions, the association prioritized three goals:

1. Boosting event attendance by targeting communications to members most likely to attend.
2. Improving member benefit utilization through personalized recommendations.
3. Streamlining volunteer coordination by automating routine communications and administrative tasks.

To address these priorities, we established three cross-functional teams that included staff from marketing, event, member coordination, and IT teams, along with board members and chapter leaders. Each team was tasked with exploring specific Gen AI applications within a secure, sandbox environment.

• The event attendance team leveraged predictive analytics to analyze historical attendance data, identifying patterns such as preferred event types, timing, and regional preferences. Using these insights, the association developed tailored marketing campaigns, resulting in a 20% increase in event registrations within six months.
  
• The member benefits team used Gen AI to create a recommendation engine that personalized benefit suggestions based on members’ career stages and professional interests. Benefit utilization increased by 15%, and member satisfaction scores improved by 24%.
  
• The volunteer coordination team implemented a chatbot powered by Gen AI to handle routine inquiries and reminders for volunteer tasks. This solution reduced staff workload by over 25% and improved volunteer satisfaction with association support.
  

These successes were made possible by fostering a culture of trust, collaboration, and continuous learning. Regular feedback sessions ensured alignment with the association’s mission and allowed teams to learn from one another’s experiences.

Key Principles for Associations

Based on this experience and others, the following principles are essential for associations to harness the full potential of Gen AI:

1. Cultivate a culture of trust and psychological safety: Encourage calculated risk-taking and experimentation among staff and volunteers. Emphasize that failures are valuable learning opportunities.
2. Provide clear strategic direction: Align Gen AI initiatives with the association’s mission and goals. Establish measurable objectives and transparent evaluation criteria to guide experimentation.
3. Promote cross-functional collaboration: Bring together diverse expertise from staff, volunteers, and members to drive innovation and ensure practical solutions.
4. Encourage continuous learning: Establish feedback loops and knowledge-sharing mechanisms to accelerate organizational learning and improve future initiatives.
5. Invest in resources and training: Ensure teams have access to the necessary tools, data, and expertise. Provide training programs to build confidence and competence in using Gen AI.
   

Driving Sustainable Innovation

By adopting these principles, associations can unlock the transformative potential of Gen AI, enhancing their operations and delivering greater value to their members and professions. Success in this endeavor requires a deliberate and collaborative approach—one that empowers teams to explore, innovate, and learn while staying firmly aligned with the association’s mission.

Gen AI represents a profound opportunity for associations to advance their strategic goals, engage members more effectively, and reinforce their role as leaders within their professions. With the right cultural and organizational foundations, associations can harness this technology to drive meaningful and lasting impact.

Key Take-Away

Gen AI success in associations comes from balancing autonomy with support, enabling cross-functional experimentation, and building a culture of trust, learning, and alignment. Share on X

Image credit: fauxels/pexels

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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.