Artificial Intelligence (AI) has quickly become one of the hottest talked about opportunities in the association space. Leaders are no longer questioning if you should explore AI, rather how to implement it strategically across your systems without overcomplicating operations or draining resources. The key in my eyes is not to chase the shiniest tool, but to make purposeful choices about integration, scalability and value. 

Asking the Right Questions 

One of the most common mistakes in implementing AI is starting with the tool, rather than the problem at hand. Organizations are often intrigued by the potential of AI in streamlining operations, member experiences and more, but the truth is, without clarity on the actual challenge we’re aiming to solve, such tools can create unnecessary complexities. We need to clearly define our pain points to evaluate whether AI is the correct solution. To get started, here are some questions to consider: 

• Where are staff spending time on tasks of low value? 

• Where are members not fully engaged? 
• Are there locations where critical data is silo-ed? 

Making Systems Collaborate 

Even after a use case is clear, integration can be a difficult challenge. Associations rarely rely on a single system. Most operate with a combination of AMS or CRM platforms, learning management systems, event technologies, marketing tools and more. Dropping AI into that hemisphere doesn’t automatically create value. To ensure the benefits outweigh the burden, we need to consider overall integration functionality, and ask questions like “how will it work across our systems?” Another key factor that can often be overlooked is what the current state of data looks like across your systems. Clean and reliable data will always find more success in leveraging AI tools. 

Finding Value in AI 

When strategically applied, leveraging AI can add real, measurable value for organizations. Associations often collect a plethora of information, typically scattered across multiple systems. AI that connects these data points can be used to discover engagement patterns, predict member churn or even highlight opportunities for targeted outreach. These insights can help drive strategic goals for the organization and help deliver more personalized experiences for members. 

Another area where there can be significant value is AI-powered content support. From drafting routine communications and event descriptions to creating FAQs or email reminders, staff spend a significant amount of time creating content from scratch. AI can help speed up this process, allowing staff more time to focus on refining messages. 

AI can also support associations beyond these applications, especially in areas such as event planning, member retention and more. 

What to Skip 

There are also many AI use cases that associations should approach cautiously. All-in-one AI platforms that claim to solve every problem are often tempting, but not always practical. While they may have a feature or two that stand out, you’re likely to run into product limitations, or the need for expensive customizations. 

Another scenario where you may want to reconsider AI is if you already have a similar process to support the result. For example, if your system provides analytics for you, laying on a second tool with the same function may be redundant. To avoid duplication and wasted resources, make sure your business use case is clear and adds value. If it doesn’t, saying no can also be the ideal strategic move. 

Conclusion 

Artificial intelligence is not magically going to make everything better but can be a tool to help organization thrive. Overall, the goal should be to deliberately use AI to help solve true challenges, integrating it thoughtfully across systems. In the end, correctly leveraging AI involves making purposeful choices and delivering positive and sustainable value.