July is already well on its way, but we’re still very much thinking about the conversations at last month’s AMSFest Chicago and the key concerns that emerged through our follow-up conversations with decision makers in the association space.
To call these topics concerns may seem a touch dramatic, but it’s important to note that the underpinning theme behind these conversations is a recognition of the need for change. Specifically, how do associations adapt to meet changing member needs within a rapidly evolving landscape?
Our community is beyond curious about leveraging AI to ease staff workloads, engage members, and better inform decision-making processes. And so it’s no surprise that data quality, specifically how to condition data to enable AI, emerged as a recurring topic of conversation. This was so top-of-mind for the group that it was not only present in every AI session we attended but also a major topic in almost every break-time or lunch conversation we joined.
Many of these data-specific concerns were mentioned in larger discussions surrounding the need for stronger audience engagement.
