As AI transforms industries, associations are identifying opportunities to enhance member value and provide additional benefits. Hayley Schofill, VP of Strategic Partnerships at Multiview, spoke with Jason Wampler, Managing Director of IT at the International Society of Automation (ISA), about AI’s role in associations, the challenges of adopting new technology, and their recommendations on implementing this innovation.
This interview has been edited for length and clarity.
Q: Jason, can you start by telling us about your background and how you got involved with associations?
Jason: I’ve been in the association space since 2009. Before that, I worked at a nonprofit for about 11 years. I’ve always been in mission-driven organizations, particularly in IT leadership roles. I also spent a short time on the vendor side, which gave me a unique perspective on how associations operate from both sides. Ultimately, what brought me back to nonprofits was the passion for working in organizations where the focus is on the mission rather than the bottom line. I’ve been at ISA for two and a half years now, leading a small but powerful IT team of five.
Q: When it comes to AI, what are some of the common gaps that you see amongst associations?
Jason: For us, we’re in the standards industry, which covers certain proficiencies and business criteria. What we've discovered through our AI exploration is that some of our standards may not have everything people are looking for. This led us to go back and ask if there is a derivative product, white paper, or case study we need to fill those gaps. It’s those kind of brainstorming ideas that AI LLMs can spur on—to get past that "creative writing block" we can sometimes have.
Q: I can definitely relate to using AI in different ways to spark other thoughts or creativity. It gives you those prompts to continue to push forward in that direction without hitting a wall.
Jason: In your traditional search, you’re only going to be able to do so many keywords before the algorithms determine your results. In most cases, the top results are influenced by who paid the most for ads. Ultimately, you’re trying to find another knowledge expert or a discussion on the topic you're looking for, but in a different way. AI is like having someone that you would normally banter with who knows everything you want to know, just presented in a new way.
Q: AI is such a broad topic with vast applications. In the context of associations, what are some of the biggest challenges for adopting and integrating AI, and what’s the greatest opportunity for impact?
Jason: Two major challenges come to mind: fear of technology and a lack of understanding of an organization’s own data. Fear is common because AI is new, and many don’t know what the limits are. On the other hand, organizations often don’t have a strong grasp on their data, especially when operating in silos.
I think you would be amiss if you didn't at least attempt using AI in some fashion, if nothing else to help clean up and organize data. Doing so can help spur up an adoption for the creative process within your organization. At the end of the day, associations are in the business of content, and AI can help make that process more streamlined and relevant.
Q: Fear of technology is a big one and it’s common throughout associations. Privacy is always a concern when it comes to AI. How can associations protect their members’ information while still leveraging AI’s benefits?
Jason: You definitely want to start small and look at where you can get the best return for your efforts—like my buddy says, "the juice versus the squeeze."
For privacy, don’t let AI loose on your membership database and start spitting that out to the public. That’s privacy 101: a big no-no. But where you can apply AI is in areas like training or educational content. For instance, if members reach out to customer service with questions, you could have an AI tool handle that by consuming relevant content and responding in a conversational way—more like a widget than a chatbot. AI models like large language models (LLMs) can infer things and have a more dynamic conversation. However, with privacy concerns, you need strong policies in place and make sure everyone knows this is just a tool—not the final word from the association.
Q: Associations often operate in silos. How can AI help resolve data issues across departments?
Jason: AI can be a big help with that. It can bridge gaps between departments, whether it's with membership data, training data, or any other silo. For instance, we work with standards in oil and gas, smart buildings, and automation, but cybersecurity applies everywhere. So, we asked our AI how one of our standards would apply to NASA’s space program. It came back with an answer, even though that’s not something we typically work with. AI can help associations uncover connections between their content and the broader mission, even across traditionally siloed areas.
Q: This is a big one. Do you believe cost is a prohibitive factor for associations with limited budgets?
Jason: It can be, but I think not adopting AI could cost associations more in the long run. There are efficiencies and advantages being realized even in this early stage, not just with AI LLMs, but also with marketing automation and personalization tools. Some tools can even predict member behavior, like whether someone might drop their membership based on past engagement. That allows associations to intervene early with tailored campaigns. Even if you start small, AI can help associations gain significant advantages.
Q: ISA is at the forefront of automation. What examples are you hearing from your members about how AI is impacting their fields?
One example comes from a CIO at a university in North Carolina. Their network team was overwhelmed with trouble tickets—something like 500 in a short period. They implemented an AI networking platform and brought that number down to under a dozen in just a few months. The AI helped free up their team so they could focus on more strategic work. It’s a great example of how AI can take over repetitive tasks and let teams focus on higher-level efforts.
Even if AI saves just an hour or two a day, over time, that adds up. Those small efficiencies can make a big difference. And who knows, maybe it even leads to discussions about four-day workweeks because people are getting more done in less time. It's about working smarter, not harder.
Q: Tell us more about MIMO, ISA’s new AI tool. What capabilities does it offer, and how is it benefiting your members?
Jason: MIMO is our newest addition. It’s essentially our mascot for trained content like standards, reports, articles, and news clippings. What’s really exciting about MIMO is that it can handle prompts in multiple languages, which is something I hadn’t fully realized at first. On launch, which was in early July, MIMO responded in eight different languages, including Taiwanese, Indian, Japanese, and Mandarin. It was fascinating because it almost mirrored our membership demographics, which gave us some really valuable insights.
As an international organization, a lot of our members don’t speak English as their first language. For those members, MIMO is a huge benefit because it allows them to interact with our mostly English-based content and find what they need, without having to struggle with translations. It was a real "wow" moment for us.
Q: It sounds like MIMO has some really special capabilities. What are some other interesting use cases you’ve seen so far and what’s next for MIMO?
Jason: One interesting use case came from members asking MIMO for help preparing for certification exams, like CAP. It started generating questions based on our content to help them study. It’s been really helpful in ways we hadn’t anticipated.
We’re actually looking into integrating MIMO with our online community. We’re thinking of leveraging MIMO to help answer technical questions between member discussions. If someone posts a question and no one responds, MIMO could jump in and provide an answer. Of course, we’ll need to gate this carefully. We don’t want MIMO consuming random content or developing biases from public input. The goal is to keep it factually accurate and unbiased, ensuring members get the best experience possible.
