In this episode of Associations NOW Presents, guest host Joanna Pineda of the Associations Thrive podcast chats with Rob Wenger, CEO of Higher Logic, and Amanda DeLuke, senior privacy analyst at Higher Logic. The conversation unpacks Higher Logic's own AI adoption journey, starting in October 2023, and the strategies they used to engage employees with AI tools. Rob and Amanda share practical insights on how associations can begin their AI journey, create policies, and leverage AI tools while prioritizing data privacy. Whether you're just getting started or looking to expand your AI capabilities, this episode offers actionable advice on using AI to enhance operations, improve member engagement, and drive innovation.

Check out the video podcast here:

https://www.youtube.com/watch?v=JLKUv2GFpUY

 

This episode is sponsored by Higher Logic.

Associations NOW Presents is produced by Association Briefings.

Transcript

Joanna Pineda: [00:00:00 ] Hey everyone, I'm Joanna Pineda, CEO and Chief Troublemaker at Matrix Group International and host of the Associations Thrive podcast. Each week I interview and association our non profit CEO about their personal journey and the things their organization is doing to thrive. But today, I am thrilled to be a guest host for the ASAE podcast for Associations Now.

And I am absolutely honored because I'm going to be interviewing Rob Wenger. CEO of HigherLogic and Amanda DeLuke, Senior Privacy Analyst. We'd like to thank our episode sponsor, HigherLogic, for their support of this podcast. Rob and Amanda, welcome to the show.

Rob Wenger: Thank you. It's great to be here.

Joanna Pineda: Hey Rob, there's probably two people out there in the universe that don't know HigherLogic, and for those two people, tell us about HigherLogic.

Rob Wenger: So our main product is online community. It's a place where associations members can talk to each other, share documents, ask questions, network, all the kinds of good stuff that they might do in person. They do it online 365 days a year. And we also make marketing automation products and a bunch of other different add-ons to it, like volunteer management.

Mentor management, a lot of different things that really are geared toward helping associations and their members connect.

Joanna Pineda: Amanda, you've got an interesting title. Your title is Senior Privacy Analyst. What is a Senior Privacy Analyst at HgherLogic?

Amanda DeLuke: Yeah, so I am definitely someone that works across the company.

You know, privacy is really everyone's problem, right? Everyone works together, creating privacy champions. So I actually report to the legal team. I deal with audit and making sure we are compliant for any applicable privacy laws, also working with our sales team and our data processing agreement and working with marketing.

So really just collaboration across the company, just to make sure we're staying safe. And we're adhering to any applicable [00:02:00 ] laws and staying compliant. Well, that's

Joanna Pineda: really interesting because today our topic is AI. And Robyn and Vanda, I'm really curious to learn almost two sides of the AI journey at HigherLogic because I bet you're integrating AI into HigherLogic products, but I'm also really curious to learn about your AI journey as a company.

Like how do you get people trained up and excited about AI so that now it becomes part of the culture? So what do you want to start with?

Rob Wenger: Yeah, so we sort of kicked off our internal AI journey in October 2023. I had this idea and I guess in August, Hey, let's get everyone in the company using AI like for a day, like sort of one of those hackathon type thing.

And then report back on what they did that was cool. And so I started kicking this thing off and then the folks in legal and Amanda's team said, Hey, hey, let us. Think about this privacy stuff first. Don't just jump into this. So we spent a little bit of [00:03:00 ] time putting it together. We ended up doing a whole month.

AI October we called it.

Joanna Pineda: And this was in 2023.

Rob Wenger: 2023, right, so October 2023. And so we spent a bunch of time, Amanda's team spent a bunch of time coming up with sort of the rules of the thing. Like don't just go use any tool and don't put customer data in it and all these kinds of great things. She developed processes and stuff like that.

I'll let her talk about that because she knows way more about it than I do, but then we ended up doing it as a full month, and the idea was everyone spend 16 hours in October. Do some stuff, get in the teams of one, two or three, play with these tools and come back and report back. And what we ended up doing is having on Halloween, it was a contest with costumes and with who had the best usage of AI.

And so it was a lot of fun, but it was a big journey to get there. And I'll let Amanda talk about that because she did most of the work. I just have the big idea and she made it happen.

Amanda DeLuke: Yeah, so it's really important to establish an internal policy and, you [00:04:00 ] know, it's really kind of putting the guardrails on certain areas.

And what I see in legislation is they really focus on balancing innovation and safety. And I think that's what we're kind of doing here too, right? We want to innovate, but we want to do it safely. So putting in place those policies is really important and again, like collaborating with teams on what type of data do we have and what are we holding and what are we okay with as it relates to AI and what type of data goes into AI.

And I think Rob, you bring up such a good point because we talk a lot about testing and really getting our hands dirty. And I think that's so important and it's really important because AI is ever evolving, that we're always evolving our policy and evolving how we work internally as well.

Joanna Pineda: Well, let's step back here because I'm curious about this and I'll give you a little bit of background.

So I was at a luncheon with a bunch of association CEOs and a number of them said, [00:05:00 ] gosh, we're struggling with AI. What does that mean? And they said, we've asked our staff to use the tools and they're either getting pushback or they're not seeing the fruits of some of this experimentation. And so what would you say to an exec who says, look, I think AI can help my team be more productive, but how do they kick it off?

Like, how do you get people comfortable with the tools so that they are seeing the fruits of this amazing technology?

Rob Wenger: Couple of thoughts on that. I get some really good advice. Yes. About a year ago from an AI luminary and the gist of it was If you're trying to turn people's daily routine around, that's difficult.

It takes time, and it's difficult to get them to start. Once they start, it takes time to get it to work, right? And the advice was start higher up. Start at system level stuff, like get AI. Doing things that don't involve humans yet. I mean, humans, you want them in the loop, but it's sort of like automating things [00:06:00 ] as opposed to like using ChatGPT every day on your desktop, right?

So we really started there looking at all right, we're going to build a data warehouse. It's going to have all this data from around the company in it. And Amanda's part of that as to how we handle the stuff that really is like privacy related or would be data for clients. We don't really put that in there.

We put data about clients more, but keeping the privacy stuff working well, but then doing it on top of that to give us sort of answers as opposed to letting a person go into ChatGPT and just. Ask a whole bunch of questions. So starting at that end of the spectrum, you can get a lot more of those kinds of things done.

And, and, and I know we're gonna talk about the product later, but that's how we're thinking about the product as well. It's more about automation than it is about what you're used to seeing in JATTPT, for example. We have that functionality. But where we think the real bang for the buck is going to come from is having AIs do a lot of automated type tasks.

So we started there. And [00:07:00 ] then, of course, we do encourage our staff to use these tools. The easiest place for us to start was with our engineers. Some of the reason is because it's way behind the scenes. Like, they don't really touch client data. And they also, products of an AI are Then test it, right?

Because that's the whole point of software development. You have to write the software and develop it and test it. And if you have any, I do that work, you know, it's going to be right because it's got to go through that process. And so that is an easy place to start. They're also very technical. It's easy to get them going where it starts to become, you know, more interesting.

I'm not gonna say challenging because the uptakes been really good. But when you get into finance or you get into, you know, accounting and some of these other aspects of the business where it's not obvious, How the data is going to be used. You got to be careful, but you can see a lot of gains. So it's been quite a journey.

Like I say, we started almost a year and a half ago and it's become something where it is throughout the company. One of the thing we did in that timeframe is we actually appointed, [00:08:00 ] I call him the AI Czar, his actual title is chief data officer, but Steve was the head of engineering and it seems like we have a bunch of engineers, so it was like, we really need to get AI done right in the compan