As associations increasingly integrate generative AI, often referred to as Gen AI, to enhance member services, optimize operations, and provide value to stakeholders, they encounter a unique set of challenges, including resistance to change, concerns about job displacement, and data privacy issues. For association executives, understanding and overcoming these challenges is critical to harnessing the full potential of Gen AI while remaining aligned with their mission and values.

Common Frustrations and Challenges

One of the most significant hurdles in Gen AI adoption is resistance to change among staff and members. Association executives often face pushback due to fears that it could lead to job displacement, particularly among administrative staff or member-facing roles. This fear is not unfounded; headlines about major companies like IBM, Salesforce, and Google implementing hiring freezes and layoffs due to Gen AI adoption only heighten these anxieties. For example, a study by Intelligent.com found that 78 percent of hiring managers plan to lay off some recent graduates due to Gen AI, with over 10 percent expecting to reduce their recent grad workforce by 30-60 percent. Such statistics fuel apprehension, particularly in sectors that thrive on human connections, like associations.

It’s important for association leaders to recognize that while Gen AI can automate routine tasks, it also offers significant opportunities to augment human capabilities. It allows professionals to focus on more strategic and creative endeavors, enhancing member engagement and value creation. A study by Harvard Business School, in partnership with Boston Consulting Group, revealed that consultants with access to Gen AI completed 12.2% more tasks on average than consultants without access. And according to the study, the quality of their work was more than 40% higher quality than the group without AI access, as evaluated by external observers who had no knowledge of who did the work. This finding demonstrattes that AI can enhance both efficiency and the caliber of outputs. For associations, this could mean more personalized member services, improved advocacy efforts, or more effective educational programming.

A major challenge for associations lies in the lack of understanding and expertise. Many association staff members may feel unfamiliar with AI’s functionality and potential benefits, leading to skepticism and reluctance to adopt these tools. Unlike for-profit organizations that may have dedicated resources for tech adoption, associations often operate with leaner budgets and fewer tech-savvy personnel. Without targeted education and training, association staff and members might struggle to see how integrating Gen AI can support their mission, advocacy, or member engagement goals.

Associations also face significant hurdles in integrating Gen AI with existing systems. Many associations use legacy software platforms for membership management, event planning, and advocacy tracking. This can present compatibility issues, data migration challenges, and technical glitches that frustrate staff and delay adoption. For example, automating member communication using AI-powered tools may lead to errors if the AI is not fully integrated with existing CRM systems. Executives need to allocate adequate resources for integration and collaborate closely with IT teams and AI vendors to ensure a smooth transition.

Risk Around Gen AI in Associations

A pressing risk is data privacy and security, which is especially crucial for associations handling sensitive member data. Many associations have unique obligations to their members regarding data protection, and the adoption of Gen AI raises questions about how these systems handle personal information. Any data breaches or unauthorized access could result in significant reputational damage, loss of member trust, and potential legal consequences. To address these concerns, associations must implement robust security measures, such as encryption, access controls, and regular audits, ensuring compliance with both internal policies and external regulations.

As cyber threats evolve, the introduction of Gen AI systems may open new vulnerabilities. Sophisticated cyberattacks could target AI algorithms or exploit integration points between AI and legacy systems. Associations must stay ahead of these challenges by continuously updating security protocols and collaborating with cybersecurity experts to safeguard their organizations against emerging threats.

Beyond immediate challenges, association executives must also consider the long-term and existential risks associated with Gen AI adoption. One such risk involves the potential for AI systems to perpetuate biases. Since AI algorithms learn from historical data, they can inadvertently reinforce existing biases, which could lead to unfair outcomes in areas such as member engagement, recruitment, and event programming. Associations must actively monitor AI systems to identify and correct biases, ensuring that their use aligns with organizational values and goals.

Another risk is the potential overreliance on Gen AI systems, which could lead to a diminished role for human judgment and critical thinking in decision-making processes. Associations, driven by human relationships and community building, need to ensure that AI serves as a tool to support—rather than replace—human decision making. Encouraging a culture of critical thinking, where staff and leaders continuously question and validate AI-driven insights, will help mitigate this risk.

Ethical considerations are also crucial as Gen AI becomes more advanced. Associations, especially those that advocate for ethical standards within their industries, must engage in ongoing discussions about the broader societal implications of Gen AI. As AI systems grow more autonomous, questions about their alignment with human values, member expectations, and the association’s mission will become more pertinent. Executives must be proactive in shaping ethical frameworks and governance structures to ensure responsible and beneficial AI use.

One of the unique concerns for associations adopting Gen AI is the potential loss of the human touch in member interactions. Many associations pride themselves on building strong, personal relationships with their members. The automation of tasks such as member communications, event registrations, or support inquiries could risk creating impersonal experiences that erode member loyalty. Associations need to strike a careful balance between leveraging AI for efficiency and maintaining the personalized interactions that define their member relationships.

To address this concern, associations can design AI systems that enhance rather than replace human engagement. AI-driven tools can be programmed to recognize member preferences, emotional cues, and historical interactions, allowing for more personalized and empathetic responses. And AI can help segment members for targeted communications, provide tailored content based on member interests, and even support personalized member onboarding processes.

Conclusion

The adoption of Gen AI presents both significant opportunities and challenges for associations. By understanding the specific hurdles that their organizations face, executives can develop tailored strategies that align Gen AI adoption with their organizational missions and member expectations.