Or simply to inefficient usage: As Alonso noted, “The average employee isn’t inventing with AI; they’re using it to optimize — 22 percent have almost no experience and 63 percent call themselves beginners.”
Resetting the culture code ensures that the adoption of generative AI is aligned with the association’s mission and values. It helps build trust among staff, volunteers, and members, fosters inclusivity, and sets a standard for how AI can be used ethically and effectively.
The Pillars of a Gen AI-Ready Culture Code
Collaboration across boundaries. Associations thrive on collaboration between staff, chapters, and sections. Generative AI tools can bridge gaps, enabling more seamless communication and joint initiatives. However, cultural norms must support this collaboration by promoting transparency and shared ownership of outcomes.
Inclusion in innovation. AI can exacerbate biases if not implemented carefully. A culture of inclusion ensures that all voices — across demographics, chapters, and professional levels — are considered in AI-driven decision-making. This means creating training and feedback loops that empower traditionally underrepresented groups to participate fully, while managing risks.
Ethical leadership. Associations must model ethical AI adoption for their members and industries. A strong culture code emphasizes transparency, fairness, and accountability in how AI tools are deployed, ensuring they align with the association’s mission and values.
Lifelong learning. As generative AI continues to evolve, so too must the skills and understanding of those within the association. A culture of continuous learning encourages staff, volunteers, and members to stay ahead of trends and adopt new tools confidently. As Alonso noted, “The most successful tactic we’ve seen is communal learning — forums where employees share prompts, code, and wins.”
Case Study: Resetting the Association Culture Code for a National Association
As a consultant, I partnered with a national professional association that was introducing generative AI tools to streamline operations and enhance member engagement. Despite the potential benefits, the association faced cultural resistance from staff and volunteer leaders. Some feared job displacement, while others were skeptical of the technology’s fairness and inclusivity.
To address these concerns and reset the culture code, we implemented a strategic framework:
- Engaging leadership at all levels: We began by facilitating workshops with the association’s executive team, chapter leaders, and section representatives to define a shared vision for AI adoption. These sessions emphasized how generative AI could enhance — not replace — their contributions.
- Building trust through transparency: Staff and volunteers were given clear, accessible explanations of how AI tools would be used. This included addressing concerns about data privacy and ensuring that AI outputs would be regularly reviewed by humans for fairness and accuracy.
- Fostering inclusion and equity: Recognizing the association’s diverse membership, we created tailored training programs for different chapters and demographics. For example, early-career sections focused on using AI for networking and career development, while senior professionals explored thought leadership applications.
- Creating feedback mechanisms: We established channels for staff and volunteers to share their experiences with the AI tools. This feedback loop helped identify challenges early and demonstrated the association’s commitment to inclusivity and adaptability.
- Aligning AI adoption with core values: The association developed an AI ethics policy rooted in its mission of advancing equity and professionalism. This policy became a cornerstone of the culture code, reinforcing the organization’s commitment to serving its members ethically.
The results were transformative. Staff productivity improved by 28 percent as routine tasks were automated, freeing up time for strategic initiatives. Chapters reported stronger engagement as AI tools helped them tailor programming to local needs, with more than 20 percent higher attendance and 15 percent higher retention over six months. Most importantly, the association established itself as a thought leader in responsible AI adoption, earning the trust of its members and industry stakeholders.
Overcoming Resistance: A Cultural Challenge
Resistance to change is natural, especially when it involves technology as complex and transformative as generative AI. As Alonso noted, “Generative-AI change management is fragmented: one platform, but potentially 70,000 micro-use-cases across functions.” Resetting the culture code requires addressing resistance head-on through clear communication, education, and empathy.
