11/19/2024

Overcoming Gen AI Frustrations and Challenges

A common hurdle in its adoption is staff's resistance to change

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 Google, IBM and Salesforce 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 percent 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.

Please select this link to read the complete article from ASAE’s Center for Association Leadership.