Failure: The Secret Sauce in Association Gen AI Strategy
Associations need to recognize that in the dynamic realm of Generative AI (Gen AI), “mistakes” are not setbacks but stepping stones. Facing unique challenges balancing member needs, volunteer engagement, and professional standards, embracing failure isn’t just a feel-good concept for association executives and board members. It’s a strategic imperative that propels innovation forward, enabling associations to overcome challenges and manage risks effectively. When it comes to leveraging Gen AI, associations must acknowledge that failure is not the opposite of success but an integral part of achieving it. Solutions in this transformative field demand iteration, testing, and refinement—with lessons often gleaned from what doesn’t work.
De-Stigmatizing Failure in Association Gen AI Strategy
Many associations operate within a culture of caution, stemming from a desire to protect their reputation and serve their members prudently. This cautious approach can lead to risk aversion, particularly when venturing into transformative technologies like Gen AI. Volunteers and staff may hesitate to advocate for experimental projects out of fear of failure, potential wasted resources, or loss of credibility.
However, research underscores the undeniable link between embracing failure and achieving tangible success. Research by McKinsey shows that organizations fostering a culture of innovation and embracing failure greatly outperform their peers in implementing technology, with 21% of weak innovators succeeding in digital transformations compared to 45% of strong innovators. This mindset shift is critical for associations that must innovate to remain relevant to members and the professions they serve.
For associations, this cultural shift must start at the top. Leaders need to actively promote an environment where calculated risk-taking is encouraged and celebrated. Volunteers and staff should feel assured that their contributions won’t be undervalued because an experiment didn’t yield immediate success. Instead, the focus should be on the insights gained, fostering an atmosphere where every misstep provides a roadmap for future success.
The Power of Post-Mortem Analysis in Association Gen AI Strategy
When projects don’t meet expectations, the instinct to assign blame is counterproductive, especially for associations where reputational risk is a significant concern. Instead, a constructive approach involves conducting post-mortem analyses focused on learning rather than fault-finding.
Key Questions to Explore in Post-Mortems:
- Were there gaps in the data used to train the Gen AI models?
- Did we align the Gen AI solution with specific organizational goals?
- Were internal processes or team dynamics contributing factors?
Associations can systematize these analyses to build institutional knowledge, ensuring that both staff and volunteers benefit from collective learning. By sharing findings—both successes and setbacks—across the organization, associations can foster a culture of transparency and continuous improvement.
Client Case Study: Embracing Failure to Drive Member Engagement
Consider a mid-sized national association of about 25 staff I consulted for that was seeking to enhance member engagement through more personalized communication. The leadership team hesitated to invest in Gen AI solutions, fearing wasted resources and a negative perception from their board if initial projects faltered. Recognizing the need for a paradigm shift, I helped them approach the project as a series of small-scale experiments with built-in mechanisms to analyze and learn from outcomes, including failures.
We launched a pilot program using Gen AI to tailor email communications to specific member segments. Initially, the results were underwhelming. Engagement metrics, including email open rates and click-through rates, remained stagnant at 10% and 2%, respectively, about the same as without the Gen AI tool. Rather than labeling this outcome as a failure, we conducted a thorough post-mortem analysis to understand what went wrong.
Here’s what we found:
- Segmentation Gaps: The initial member segmentation model relied on broad categories, such as career stage and geographic region, which led to generic messaging that didn’t resonate.
- Tone Mismatch: The AI-generated content appeared overly formal and impersonal.
By refining the segmentation model to incorporate more granular data, such as specific member interests and participation history, and fine-tuning the AI’s tone to be more engaging and personal, subsequent campaigns performed significantly better. Within three months, email open rates increased to 15%, and click-through rates rose to 4%. The pilot program ultimately demonstrated the potential of Gen AI to enhance member engagement, while also saving the association approximately $25,000 in outreach costs through more targeted communications. And that was the first project of many, which overall improved their bottom line by over $120,000 in a year.
Creating a Shared Learning Environment
Associations thrive on collaboration. Leveraging this strength is essential to embedding a culture of shared learning in Gen AI initiatives. By openly discussing failures and successes, associations can accelerate their collective learning curve, reducing the likelihood of repeated mistakes and fostering a sense of community. Consider these practical strategies:
- Regular Knowledge-Sharing Forums: Establish forums where teams can present their Gen AI experiments and findings, highlighting lessons learned from both successful and unsuccessful initiatives.
- Peer Support Networks: Facilitate cross-departmental peer groups to discuss challenges and share insights from Gen AI projects.
- Innovation Sandboxes: Create controlled environments where teams can test Gen AI solutions without fear of disrupting core operations or public-facing initiatives.
For example, one association’s learning forum revealed that a failed member recruitment campaign’s messaging strategy inadvertently alienated younger professionals. This insight not only informed future recruitment efforts but also prompted broader discussions about generational engagement strategies.
Psychological Safety as a Catalyst for Innovation
Psychological safety is a cornerstone of any innovative culture. In associations, where staff and volunteers often work closely to serve diverse member needs, fostering an environment where experimentation is supported is particularly important. A lack of psychological safety can lead to a “play-it-safe” mentality, stifling the creativity needed for transformative projects like Gen AI. To foster psychological safety, association executives and board members need to:
- Publicly recognize efforts to innovate, regardless of outcomes.
- Frame failures as opportunities for growth and learning.
- Provide consistent messaging that supports experimentation and risk-taking.
An article by Forbes highlights the importance of psychological safety in driving innovation. It emphasizes how leaders can create a culture where employees feel empowered to take risks. Additionally, a study by Google, discussed on their re:Work platform, found that psychological safety was the most important factor in team effectiveness. For associations, this translates into empowering both staff and volunteers to push boundaries without fear of retribution.
Turning Failure into Success
In the rapidly evolving world of Gen AI, associations have much to gain by embracing failure as part of their innovation strategy. Each setback offers a chance to learn, refine, and improve. By fostering a culture that values experimentation, associations can stay agile, enhance member experiences, and better fulfill their mission.
Ultimately, failure is not an ending but a beginning—a starting point for the innovations that will shape the future of associations and the professions they represent. For association leaders at all levels, the challenge is clear: embrace failure as the secret sauce that fuels Gen AI success and, in doing so, lead their organizations toward greater resilience and innovation.
Key Take-Away
In association Gen AI strategy, failure is not the opposite of success but a vital part of innovation. Embracing and analyzing setbacks fosters agility and learning, helping associations stay relevant while enhancing member engagement and… Share on XImage credit: Kindel Media/pexels
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.