How Arizona State University Became a Leader in Practical AI for Higher Ed Marketing Teams
Arizona State University (ASU) has turned heads for how quickly and strategically it’s adopted artificial intelligence, especially in its marketing and communications departments. Executive Director Tina Miller, featured on the Higher Ed Demand Gen podcast, shared how ASU’s culture of innovation—backed by visionary leadership—has paved the way for campuses nationwide looking to do more than dabble in AI.
Real-World Use Cases for AI in Higher Ed Communications
ASU’s commitment to AI starts at the top, with President Michael Crow championing inclusion and technology. When OpenAI approached ASU to launch the AI Innovation Challenge, the university jumped in, inviting faculty, staff, and researchers to propose impactful projects. With over 500 proposals (and counting), the focus is on maximized impact, not a one-size-fits-all approach. Units from engineering to business are encouraged to develop their own AI-driven projects. This decentralized innovation has attracted partners like OpenAI and Google, reinforcing ASU’s national leadership role.
AI Tools That Move Beyond Content Writing: From Storytelling Bots to Brand Compliance
Miller’s team has gone way past basic AI prompts. They’ve created custom storytelling bots like Spin Cycle, which draws from years of published ASU stories. This bot allows communicators to retrieve relevant quotes, context, and even generate first-draft follow-ups using past content. Another example is the “Gonnick Guru” bot built from CIO Lev Gonnick’s presentations and interviews, capturing his voice for accurate, on-brand messaging.
ASU’s AI-powered brand bot checks stories for adherence to brand style and corrects names for over 17 schools and departments automatically—a huge time-saver for writers and editors dealing with long reviews and nitpicky brand requirements.
Empowering Marketing Teams Through AI Training and Community Support
Tina Miller emphasizes hands-on experimentation, encouraging her team to try tools like ChatGPT, Wordtune, Canva, and more. ASU also supports peer-to-peer learning through the AI Beacon Network—a community of higher ed marketing professionals sharing tools, solutions, and support. Training at ASU blends online courses, weekly sessions, and open culture, making sure staff feel confident in using new AI solutions and bringing fresh ideas.
ASU’s approach proves that practical AI can transform marketing teams—delivering measurable efficiencies while keeping the human touch front and center.
Read the transcription (coming soon)
Shiro [00:00:00]:
Welcome to the Higher Ed Demand Gen Podcast, helping higher education marketing leaders share knowledge about learning, strategies, and tactics that are relevant today. See what you can learn today by listening to one of our episodes.
Tina Miller [00:00:15]:
Hello, everyone. Welcome to the Higher Ed Demand Gen podcast hosted by Concept three d. If you like our content, please follow and subscribe to us. As always, I’m Shiro Hattori, your host. And today, I’m very excited to talk about practical AI applications for higher ed marketing teams. For the topic, I have none other than Tina Miller joining us today. She is the executive director of creative and communications for enterprise technology at Arizona State University. Welcome to the show, Tina.
Tina Miller [00:00:46]:
Thank you. I’m excited to talk to you today about AI.
Tina Miller [00:00:50]:
I’m very excited to have you. I know you’ve been on a lot of other podcasts. I’m really excited to finally talk to you today. So as an icebreaker, I love to ask all my guests this. Tell us what you love about higher ed.
Tina Miller [00:01:02]:
Love this question. So for me, I am a first generation college graduate. And so for me, I look at higher ed as it is just the greatest opportunity that anybody can take advantage of. And, so not only do I have a bachelor’s in journalism from the University of Missouri, I also have an MBA from the University of Phoenix. And I just love this sector because I love to give back to, a place in a in a field that has given so much to me and offered me so many career opportunities. And my my boys, who are now both attending Arizona State University, you know, offering them opportunities to grow and learn. So I just love this sector because it has trans literally transformed my life.
Tina Miller [00:01:48]:
Amazing. Generational impact.
Tina Miller [00:01:50]:
Yes. Absolutely.
Tina Miller [00:01:53]:
Well, let’s let’s jump in here. Can you tell us a little bit about your background and your role here today?
Tina Miller [00:01:59]:
Absolutely. So, I came to Arizona State University after working in nonprofits, in government, and other, for profit education companies. So I came to Arizona State University in the fall of twenty twenty two, right when ChattGPT, was born. And so, right away, some of my colleagues started using it, and they said, hey. There’s this new tool that would be really interesting for you to, you know, fix up your jazz up your emails. So I started using it. And in the in March of twenty twenty three, I went to South by Southwest in Austin, Texas, and there were only three workshops at that time, and they were all about the the three that were about AI. And I went to them, and they were standing room only.
Tina Miller [00:02:43]:
And, and I knew, okay. There’s something, you know, to this. And so from there, at that point, I was in a different division at ASU, and then this job opened up at enterprise technology, which is the IT division. And so I came here in the summer of twenty three. When I interviewed, AI wasn’t even uttered. I thought that the only thing I knew about AI is I would use Alexa to oil to order toilet paper or dog food. Didn’t really know much else about it, but I knew that this was an opportunity. So, I joined Enterprise Technology, and then, my first assignment was I had to do a presentation for president Crow for every single AI project that was going on at that time.
Tina Miller [00:03:24]:
So it was like a over a hundred slide deck. And so that’s kind of led me to this as I just started looking at more and more opportunities of how, we can position ASU as the leader in AI in higher ed. And so the rest is really history. Here I am.
Tina Miller [00:03:42]:
Yeah. That’s fascinating. And it’s in very incredible to hear all the the work you’ve done and your teams have done and your partners have done just in just two years. You know? It’s that’s very, very fast moving in a slow paced industry. So,
Tina Miller [00:03:57]:
that’s Well, and that’s Oh, sorry. Go ahead.
Tina Miller [00:03:59]:
Go ahead.
Tina Miller [00:03:59]:
I was gonna say Arizona State University for ten years in a row, we are the most, by, we are the most innovative university in the country, by US World News and World Reports. So ten years in a row. So we do know a little bit about how to be innovative and how to create and get ahead of the curve.
Tina Miller [00:04:18]:
Yeah. That’s incredible. And I know one thing you’ve done and ASU has been able to do is really drive AI innovation, through communities and being a driving force of adoption. So can you tell us a little bit more about that?
Tina Miller [00:04:33]:
Yeah. Well, so for us, it started how we started driving adoption at ASU, first of all, we couldn’t have done this without the vision and the support of our president, president Michael Crow. He is a visionary. You know, he’s the one that had the idea for the new American University, which is what we all follow. He also is the one that created our charter about how we measure ourselves by whom we include, not who we exclude. So we believe anybody who wants to have a a chance or an opportunity at higher ed to better their lives and their families and their communities that we find a a way for them to get here. So that’s kind of the framework that we work in. But for AI, we started by telling stories.
Tina Miller [00:05:15]:
So on my team, we started identifying faculty members that were doing really innovative things with AI, and then we just started telling stories about them. And then in January of last year, OpenAI came to us. And as you know, OpenAI is the parent company of ChatGPT. And so they came to us and said, we want to develop a a platform or a program for higher ed. And so we partnered with OpenAI, and, we offered to our community what was called the AI Innovation Challenge. So what we offered is if you if faculty, staff, and researchers wanted to submit ideas for proposals, for a project, then we would evaluate that and then determine if we wanted to give them a license for chat GPT for this semester. So, the three areas that we focus on in AI at ASU are teaching and learning success, research for societal impact, and the future of work. And so that’s what we focus on.
Tina Miller [00:06:16]:
We’ve had, we’re now in our fifth AI innovation challenge. More than 500 projects have been proposed, and I think there’s over 300 that are actively in in flight right now. And so that’s really what we you know, how we really started introducing it to the community is doing this challenge to say, okay. We focus on impact at ASU. We’re not just doing the peanut butter method where we spread it out everywhere and everybody gets it. If you have access to it, we wanna make sure that there was an impact that, these proposals we’re working towards so that we can continue on that innovation track that we have.
Tina Miller [00:06:54]:
Yeah. That’s that’s incredible. So it’s really not just it doesn’t work like it doesn’t seem like AI is being worked on in silos within ASU’s community. There’s there’s parts of AI that you’re trying to adopt in every department.
Tina Miller [00:07:10]:
Yeah. I would say, the the challenge has certainly brought together a lot of, people from different areas. I think, we have about 17 different schools and, and colleges, units within ASU, and I believe every single one of them has submitted something at one time or another. So it really has been a great way to get everybody on the same page. But they’re also you know, innovation doesn’t have a road map, and so we are all encouraged at ASU to to start our own projects to do what we can. So while we have the challenge and people are working on that, we also have everywhere from the Fulton Schools of Engineering to WP Carey School of Business. You know, they’re they’re also working on their own AI projects independent of the challenge. And so that’s really what our executive leadership wants is they want a bunch of innovation centers all across our ASU community so that we’re actively working those, and we’re not waiting for people to tell us, okay.
Tina Miller [00:08:10]:
This is what you need to do next.
Tina Miller [00:08:14]:
That’s fantastic. And speaking of community, I know you’re a part of the founding group of AI Beacon Network as well. And can you tell us a little bit more about that as well and how that’s been an impact for your understanding of AI and your your ability to build community around it.
Tina Miller [00:08:30]:
Absolutely. Well, so I, I go around the country a lot, and I speak about the importance of AI adoption, especially when it comes to leadership and the importance of leaders adopting it. And my lane really is more of of marketing and communications because I have a a background of three decades in that, most of it in higher ed. And as I was traveling around the country and listening to my colleagues, I realized that there wasn’t any unifying force to say, okay. Is there any type of group, like, a go to, a body or network that people could actually go and and and have a free exchange of ideas, understand what’s going on with other universities and colleges? And so for me, I felt because ASU was leading in this space, I felt like I had a responsibility to my colleagues in marketing and communications and higher ed to create something that we can all come together, once a month. And so that’s what we do. It’s called the AI Beacon Network, and we have about a 15 different colleges and universities in there right now. We meet once a month, and we usually have one member who will introduce a tool, that they’ve adopted onto their team so they can show everybody else how it’s used.
Tina Miller [00:09:43]:
And then we also usually have one presentation where somebody does something strategic as far as here’s an issue that I had, and this is how I solved it. And so it’s a really great way. And the other reason I really created this network is I didn’t want my colleagues to feel alone because there it is all over the board how AI is adopted at, at colleges and universities across the country. Some are on board right away. Some, it’s stuck in faculty. Some, there isn’t any leadership oversight or interest. Some of it is lack of training. And so I just didn’t want my colleagues to feel alone.
Tina Miller [00:10:20]:
I wanted them to feel like there is a group that is also dealing with this and also working through these challenges that you can go to once a month and learn you know, we can learn from each other, because there’s there’s nothing else out there like it. And so far, we’ve had we’ve, had six meetings. So tomorrow or we have a a meeting tomorrow. I think it’s our sixth meeting. And our membership keeps growing and growing. So it’s just a great way for us to support each other. And then also, as a group, look ahead to say what is on the horizon for AI and higher ed, and how do we need to be prepared for that?
Tina Miller [00:10:57]:
That’s amazing. I actually have a note here from our last call, which was a pre call about two months ago that you had a hundred five, members on there. So you’ve it looks like you’ve already grown since then. And your story of of founding this community seems very similar to, the Higher Ed Social Group, which is a Facebook group, for Higher Ed Social Media marketers that I would love to give a shout out to. The, the founder, Cassandra, has been on this podcast too, and she’s built an amazing community with very similar pain points where, like, higher in social media marketers didn’t have a place. They were working in silos and it was just forming. And so, that community is, like, 10 old now, but sounds very similar to that story. So I think this is fantastic and, I can only see it continue to grow.
Tina Miller [00:11:46]:
Alright, Tina. So I know that you’ve told me a lot about the AI Beacon network, which is amazing, and I love that you are sharing practical AI applications within the community with examples. Can you give us some examples of some of the things either you’ve and your team have developed or things that have been shared by the community?
Tina Miller [00:12:04]:
Absolutely. So a couple things. So at Arizona State University, not only do we offer chat GPT to to faculty, staff, researchers, to do projects, but we are also creating our own tools, because we we wanna make sure that we’re also being responsible and, and that we’re looking for alternatives to what is out there in the marketplace, not to replace it, but just to augment to what we’re you know, what tools are already out there. So we have an AI acceleration team, and so they have created our own platform. And if you go to ai.asu.edu, the second tab from the left says technical platform. Your listeners and viewers can find out more about that. But we have, so we have our own tools that we’ve used on the platform. And so, the platform allows us to build our own bots and to build our own AI projects.
Tina Miller [00:12:58]:
And so one of the things that I did is I created a storytelling bot called Spin Cycle. And so what I did was I took all of our stories from the past two years. We do have a very active newsroom. Your listeners and viewers can go to tech.asu.edu and see more about what we’re about. But so I took those stories. I loaded it into a bot. And then that way, what we can my team can do is we can retrieve stories we’ve done in the past with that bot to say, okay. We had this we had this, quote from from, you know, president Crowe.
Tina Miller [00:13:32]:
What exactly did he say? What context, you know, what context was it in? And then we can look and say, okay. What if we wanna do a follow-up story? What was the story before? Or help us determine what are three options that we can do on follow-up stories. So it’s a really good way just to utilize what we’ve done in the past. And then, also, my team can actually put information in there, and it will help write, like, a a first draft of it too. But, of course, we don’t you know, you know, we’re big here at Arizona State University. We don’t wanna take humans out of the middle of technology. So as you imagine, you know, we still have to look everything over, but the bot has really allowed us to, to to really take our storytelling to a new level because it’s it’s like we have something right there that we can access quickly. Another thing that I’ve done, on using chat g p t e d u, which is, which is the system that we use at Arizona State University.
Tina Miller [00:14:30]:
I created what was called the Gonnick guru, and that is named after our CIO, Lev Gonnick. So I took a lot of his information, papers he’s written, media interviews that he’s done, presentations that he he travels around the country, around the world, actually. And so I uploaded that into this Gonick Guru bot, and it has been great. He likes it. He asks himself questions all the time. But it’s a way for us to real when we’re writing, like, what does Lev Gonnick think about AI and, you know, and and communities? Or what does Lev you know, what does the Gonic guru think about AI and the future of higher ed? And so we can actually talk to that bot and then include that when we’re doing stories, when we’re doing presentations. We can it’s infused with Lev’s voice, and he’s approved it. You know? So I would encourage anybody that is in marketing and communications that are lit that’s listening to this right now or watching this, that that’s where you can start.
Tina Miller [00:15:28]:
If you don’t know where to start, pick a simple project like a bot and just start loading things into the bot, especially if you do a lot of promotion for a certain leader or, you know, or certain body of work. You can start with a bot. Just load it in there and then work with the bot on storytelling, and it’s it’s a very powerful use of the tool.
Tina Miller [00:15:53]:
I I’m I really like these examples because I think they move beyond just write me a blog about ASU’s athletic team in 600 words. You know, it’s it goes beyond just the content writing perspective, and these are great examples. And your spin cycle, example actually made me think I know that content libraries in higher ed are very, very siloed and hard to find, like, content, like, finding pictures from last year’s game day and then maybe another team from different department trying to find those images. It’d be amazing if you could use a similar technology to also find pieces of media content too very easily instead of having to, like, look through files. So Oh, yes. That was
Tina Miller [00:16:36]:
Another, another project that we did that you and I talked about is, my in the AI innovation challenge, my team took on a brand bot project. And so what we did is we worked with ASU’s enterprise brand team, the media relations and strategic communications team, and a bunch of other, stakeholders. And so my team created a bot that had loaded into it all of our branding guidelines, and then it also uploaded all of our AI branding guidelines. And so the team used that to say, okay. They would write a story. They would put it through this bot, and this bot would come back and say, well, you you called the WP Carey School of Business something different. This is actually the name of the school. And it you know, we have over 17, you know, departments and colleges and schools, so sometimes you might get the name wrong because there’s so many different things.
Tina Miller [00:17:29]:
So it really was, it was really effective because we could put it in there, and it would come back out and say, this isn’t correct. This is correct, so that we’re writing in ASU style. Because we as you could imagine, as a, you know, a very prominent university, we have specific brand guidelines on how things have to be written. And so that has that also proved to be a huge help to the people in our writing community because now they have this bot that they can then double check to make sure that their writing is within ASU’s brand standards.
Tina Miller [00:18:02]:
I I really like this example. I I shared it actually with a few other people on on this podcast, and, yeah, I think this is fantastic because there’s layers of, content that you have to review, and this could be an amazing step in between, like, a writer and an editor where you’re basically saving hours from editor having to, like, do things that are obviously stick out as a first draft, and then maybe you can pull them in for the second one. So this is this is great.
Tina Miller [00:18:32]:
Yeah. I would suggest anybody that oh, sorry. Go ahead.
Tina Miller [00:18:35]:
Oh, I was just gonna say finish your sentence. I have another question.
Tina Miller [00:18:38]:
Okay. I would just say anybody who, you know, doesn’t like I said, doesn’t know where to start, just start you can easily do it. If you have any guidelines, anything that you have to use, you can throw that into a bot and start training it. And so then that way, you can actually have it right there at your fingertips. Instead of flipping through something or scrolling in a screen, you can have it in a bot, and it’s very convenient.
Tina Miller [00:19:04]:
Amazing. And then I really like this I think this example you had from one of your members at the AI Beacon network, I think at Boston University, was it, about storytelling templates? Can you tell us more about that?
Tina Miller [00:19:19]:
Yeah. So this was a project by Austin Boyer who is a member of the AI Beacon network, and he works at Boston University. And it’s really a team of him. It’s he’s a team of one. He calls it one ish, and I believe he has two student workers. And they had to do a couple hundred profiles for, for alumni on their website. And so that would have, Austin broke it down where that, you know, getting the picture he had to take pictures and he had to write, he had to do write ups on each one of these alumni. At least I think it was alumni.
Tina Miller [00:19:52]:
It might have been students. But, anyway, regardless so, he actually used I believe it was Claude. He used it, and he was able to to work the platform so that it not only, approved the pictures and actually cropped the pictures that they took accordingly, but it also helped him write these profiles in a systematic formulate way so that they got them done a lot sooner. So when, by using AI, I believe he said he calculated it out. It would have it would have taken him o him alone, or his, his two teams of, student workers, I I think over a hundred and twenty hours to do all of these profiles. And then when he was able to use AI, he found that that was reduced by at least half. And so, you know, his team and them were they were able to complete this project in a in a timely manner by using AI to help write those profiles and to help, to help crop and, work on the the pictures that they had to upload as well. And so it saved him an a a lot of time, which was, you know, which is what is great about AI is it can help you save time too.
Tina Miller [00:21:07]:
Yeah. That’s that’s amazing. And can you tell us what Claude is real quick as well?
Tina Miller [00:21:12]:
Claude is one of the is one of the, large language models just like OpenAI has ChatGPT, and there’s also Microsoft Copilot. Claude is just another, LLM that people can access.
Tina Miller [00:21:25]:
Perfect. Thank you so much. Yeah. Oh, this these are all amazing examples. Again, love that they’re going beyond just the typical chat GBT prompt and taking things deeper and using data and trying to use AI to save time by either searching through that data or understanding and learning from it. So this is this is great. I’m wondering just from, like, a training perspective on the receiving end, like, how what is your strategy or strategies and approaches you’ve heard, in training your team or other teams to learn more about how to use AI?
Tina Miller [00:21:59]:
There’s a few different things we do because, you know, training is is always, I think, one of the things that is the most important that a lot of people, not just in higher ed, say that they need more of, like, what teams do. So one of the things we did early on is we created a course for faculties and staff that was kind of an overall, overview of AI, how to use it, what it’s used for, kind of the guidelines for using it. We don’t we don’t say at Arizona State University you have to use it, and we don’t say that you can’t use it. So it just depends on the situation. But so I think we’ve had more than 3,000 faculty and staff who have gone through that. So that was kind of a primer, you know, and so people are still utilizing that. And then I would also say that for the platform I just talked about, we do have weekly meetings where people that are being added to the to our internal platform all the time, they have training for that so that people that are accessing that and building bots will understand how to do it. And so we have training for that.
Tina Miller [00:23:01]:
And we also had training for how to use chat GPT so that our that our community knew how to to use that in a responsible way. And then as far as my team, what I started doing is I started just asking my team members, what where are your pain points? What are the things that you can automate? What are the things we can try? And so, you know, at at ASU, we’re all because we are innovative, it’s like we try something. And if we fail at it, that’s fine. Let’s learn the lesson and move on. And so, you know, with my team, we just started experimenting with different tools, ChatGPT. We use Wordtune, Grammarly, Canva. They’re, pro read Pro Reader. There’s, like, just a bunch of different things that I just said, let’s just start experimenting.
Tina Miller [00:23:47]:
And, and so the training kinda went hand in hand with that. Like, some of us knew how to use some of these tools, and so we would just, work with the rest of the members on our team to say, what do you understand? How can I help you? So I didn’t really have to do a lot of training on my team because we kinda use a lot of the same tools. I think it it was more of me as the leader in this team saying we need to do this. And I will give you the resources if you wanna try a new tool as long as it’s approved through our security process, let’s try it. And you can try it for six months and see if it works. And if it it does, great. And if not, that’s fine too. But I just wanted to make sure that my team was set up for success and the fact that we are all subject matter experts because we are the ones that are basically communicating a lot about AI.
Tina Miller [00:24:42]:
So I wanted to make sure that they were prepared for that, whether it was design, photography, storytelling, media relations, to make sure that we knew everything we could about AI so that we can help the rest of our community also get familiar with it and be comfortable with the technology.
Tina Miller [00:25:03]:
That’s great. I like your open approach to it and giving, agency to your team. Have any fun projects, ideas come from, like, this open endedness? And maybe that you’ve already talked about it with the the examples you gave.
Tina Miller [00:25:17]:
Yeah. I would just say, you know, we use it on a daily basis. So we use it for a variety of things. We’re in the process right now of finishing up our next AI journey publication, which gives an overview of all the AI projects we’ve been doing for the past six months. That will be distributed at the ASU GSB summit in April in San Diego, but we’re working on that. So we use ChatGPT to help us refine the copy. You know, we will get these big stories, and we have to reduce them to fit into this publication. So we might use it for that.
Tina Miller [00:25:49]:
We’ve even used it. Most recently, we had to do about ten two minute videos that we called tech, tech talks. And it was really just videos that were introducing our community to what AI is from everything from what is principled innovation, that’s our approach that we use at ASU, to what is rag and fine tuning and different things. So we had, we interview we had I don’t know. It was probably four hours of video footage from interviewing people on our AI acceleration team. So then, we took all of that, and it was probably 75 pages of transcripts. So, I uploaded that into ChatGPT, and I said, okay. I wanna know we had the 10 different videos.
Tina Miller [00:26:32]:
So I said, I wanna know all the people that talked about these different topics, what the time stamp was, and then I want you to create scripts out of all of those. And, you know, by the way, I did it in, like, twenty seconds. But, you know, so it created so the, ChatGPT created 10 different scripts based on what these people said, and I had to go back in and kinda smooth the edges, but it worked out really well. Now if we would have to have done that without ChatGPT, it would have taken us probably more than a week because we would have to identify all the different, you know, all the different quotes, who said it, what the time stamp, and then do a script. So I see it really helps a lot with script writing, and that was a a big plus for us because it it really created, a way for us to be creative with, script writing, but that way it didn’t take us weeks and weeks to to gather everything to write it.
Tina Miller [00:27:32]:
Yeah. That’s that’s fantastic. It’s so so good to take big pieces of data and and synthesize it into the portions that you like. I think a great example and I’ll give a shout out to a a LinkedIn friend here as well. But, I recently worked on a salary salary survey report for higher ed marketers, and we came up with, like, a 20 page PDF. And, he, like, ran it through NotebookLM, and he was able to create, like, a podcast recording with audio from it, which was crazy to hear my like, it was insane.
Tina Miller [00:28:06]:
Yeah. We, we are a test bed for, NotebookLM. So we’ve been working Google is, one of our partners, and so we have been, working with them. They’ve asked us to kind of do a test run with NotebookLM. So members me and some members of my team have started using NotebookLM just, like, as a trial basis to just see what we can do with it. Yeah. It’s a great tool.
Tina Miller [00:28:30]:
Yeah. It’s it’s shout out to Chris Arapozzo. But, yeah, he sent me he, like, basically sent me the auto audio file. Here’s your audio version of your salary survey, and I was blown away. It was it was a conversational podcast with two different people, and they talked about the salary survey more, like, conversationally like it would it would on a podcast, and that was all derived from a PDF.
Tina Miller [00:28:51]:
I know. And we we’ve done it with, power with, PowerPoints and Google Slides. We upload it, and some of it was, like, five slides. And the thing about yeah. I there they still need to do a little bit more work on the podcast because it is only two voices. At least, a couple weeks ago when I was in it, you can’t really say anything at the beginning or and, like, you know, you do your intros and your outros. I don’t think they have that yet. And so there isn’t a way to change voices, and and then it it’s at random.
Tina Miller [00:29:23]:
Like, you know, you can we had a five slide deck, and it was, like, ten minutes. And then we had a 20 slide deck, and it was, like, six minutes. So there’s no rhyme and reason as far as the length on a podcast, but I do think it’s a very promising technology. It’s just I I think there needs to be a few more iterations for it for us to be able to take it and actually use it in our community, but I do like what I’m seeing with that.
Tina Miller [00:29:52]:
Same. And I was gonna say the same thing. Was it cool, and was I wowed by it? Yes. Am I gonna post it as an episode on my podcast? No. Not yet.
Tina Miller [00:30:02]:
Not yet. Yeah. That’s the operative phrase. Not yet. But I think, you know, as as the technology improves yeah. You never know.
Tina Miller [00:30:10]:
Absolutely. Well, I think this is a great, lead into our next question, which is, where do you see the future of AI in higher ed? What are you excited for?
Tina Miller [00:30:20]:
What I’m really excited for is our students. As we continue to meet students where they are and and to do more VR and augmented reality, like, because that’s where this younger generation like, we need to meet them where they’re at, whether it’s gamifying or or VR. So for example, what we’re working on at Arizona State University is a digital twin of our our main campus here in Tempe, Arizona. So the reason we’re working on that is we, you know, we have a 81,000 students that come to us in any given year, but they all can’t come and take a tour in Tempe, and or one of the other three campuses we have in the Greater Phoenix Metro Area. And so this is a way that we can offer that if you’re a student in Montana and you don’t you can’t come and visit ASU, but you think you wanna you you might wanna attend school there, then we can just have you come to the to the digital twin. They can walk through campus. They can meet a professor that is in the course of study that they want to go after. They can go they can attend a, a virtual orientation.
Tina Miller [00:31:24]:
They can go in in tour a dorm. So I I think for me, what I’m we’re not there yet, but that is the future is being able our students are already used to using augmented, you know, or to using virtual reality. So let’s place them in that whether it’s a virtual class where they’re learning they’re sitting in class with people from all over the world, or if it’s touring the campus because they might want to attend ASU. So for me, that’s what’s exciting is how can technology rise up to to meet these students where they’re at and make it a more meaningful experience for them by utilizing these these tools.
Tina Miller [00:32:07]:
I I couldn’t agree more, and I I wish I had more examples off the top of my head of how we could demean students where they are using AI. But this is that that was a great example, so appreciate that. I know we’re just at about time. I’m wondering where our listeners can follow-up with you and learn more about what you’re doing, maybe also your AI beacon network as well.
Tina Miller [00:32:27]:
Sure. Well, I would say, so I’m on LinkedIn. I’m Tina Miller three, on LinkedIn. And so I’m always I’m happy to connect with people there because I’ve I’ve, you know, I’ve I’ve got a I’m creating quite a little following on LinkedIn, because I do post content about AI. Again, mostly in higher ed for marketing communications professionals, but not always. And, so Tina Miller three on LinkedIn. Or, if your if your listeners or your viewers are interested in the AI Beacon network, I personally vet every single person before they, come in to the network just to make sure they have to be in marketing communications at a university or college, and that has to, you know, basically be in their title. And so I just I vetted through looking through their LinkedIn page.
Tina Miller [00:33:13]:
So, you can, if people are interested in joining the AI Beacon Network, they can email me at tina_miller@asu.edu, and I’d be happy to send them the link that they can take the survey and and start that, member onboarding process.
Tina Miller [00:33:32]:
Well, it’s been fantastic speaking with you, and I’m so excited to see, like, where everything’s gonna go even, like, notebook, Ellen. Maybe in the future, I can post a podcast without ever saying a word.
Tina Miller [00:33:42]:
Yeah. Exactly. It’s it’s, yeah, I think it’s a really I think out of all the tools that I’ve experimented with recently, I I really do like NotebookLM. I just think it especially if you have reams and reams, if you have lots of podcasts, you can, you know, you can separate it out by notebook about different topics and, you know, and things. So I do think it has a lot of promise. I I just think that there it there’s just like any other AI tool, I think there just needs to be a couple more reiterations, but I do like where it’s going.
Tina Miller [00:34:12]:
Me too. Well, again, thank you so much for joining. It’s been a pleasure, and let’s connect again soon. I love talking about AI. So let’s see where the industry is in in a year from now.
Tina Miller [00:34:22]:
Okay. Have an AI amazing day.
Tina Miller [00:34:26]:
I like that. That’s a good one. Thank you, Tina.
Tina Miller [00:34:29]:
You’re welcome.
