Why AI in Higher Ed Isn’t Just About Tools Anymore
In this episode, host Shiro Torre, co-host Priya Vin, and returning guest Brian Piper dive deep into how higher ed institutions can actually integrate AI into their marketing strategies. As Piper stresses, this shift isn’t merely about adding cool new tools to your tech stack—it’s about meaningful, whole-system change. From his years as a web developer to spearheading the Marcom AI committee at the University of Rochester, Brian’s journey makes it clear: AI success starts with a culture shift.
Change Management: The Secret Ingredient to Successful AI Adoption
Most teams, Piper notes, start by squeezing AI into their current workflows. But real value emerges only when institutions treat AI implementation as a change management initiative. “You’re not replacing people—you’re augmenting your workforce,” he says. Educating teams, fostering collaboration, and setting up checks and balances (think: human review of AI outputs) are all critical to building trust and extracting real, responsible value from these tools.
Starting Small: Pilot Projects & Low-Risk Wins in Higher Ed Marketing
Piper suggests beginning with low-risk, high-impact projects—especially in content marketing. Here, AI can analyze search and performance data, pinpoint content gaps, and recommend strategies for repurposing and redistributing content. These early wins, he explains, build momentum, provide valuable data, and help gain buy-in from skeptical team members and leadership.
Centralized vs. Decentralized AI Committees: What Works Best?
While every institution is different, Piper’s experience suggests that centralized leadership—like AI councils—drive the most impact. Small, passionate committees can pilot new ideas and build proof points. As results emerge, collaborating across teams and gradually scaling to institution-wide initiatives works best.
The Future: Making Content Discoverable in an AI-First Search World
With the search landscape rapidly changing, institutions must make their content discoverable across all platforms, not just Google. AI can help by suggesting audience-first content and optimizing for new search behaviors, including social and Gen Z-preferred channels.
Read the transcription
Shiro [00:00:15]:
Hey, 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 Torre, your host. And today, I’m very excited to talk about how to actually implement AI in higher ed marketing. And for the topic, I’m very thrilled to have a returning guest, Brian Piper, join us today. I think in the previous episode, we actually talked about SEO, but he kind of been has been forefronting this AI movement in higher ed. So I’m very excited to talk about this.
Shiro [00:00:47]:
Brian is a higher ed influencer slash creator, author, and he recently made some big moves in his life that I’m sure he’ll talk more about, right after this. So welcome to the show, Brian.
Brian Piper [00:00:58]:
Thanks so much for having me on, Shiro. It’s always, always great to be on the show.
Shiro [00:01:02]:
It’s great to have you again. And I always ask my guest this, which is, can you tell us what you love about higher ed?
Brian Piper [00:01:08]:
I just love the fact that we are helping empower and inspire the next generation of leaders that’s coming on. So I love the the sharing of knowledge and information and just the conversations that get, you know, that start happening in that environment. So it’s a it’s a great place to work if you really wanna, like, keep pushing yourself, pushing your mind, and and helping the next the next group of people coming through.
Shiro [00:01:31]:
Yeah. Love to hear that. Couldn’t agree more. Real quick before we jump in, can you tell us a little bit about, your background and what’s been going on in your life right now?
Brian Piper [00:01:41]:
Yeah. So, you know, I started off as a web developer years ago. And then in about 2015, 2014, I migrated over into really focusing on content marketing, digital marketing, SEO. Really been doing SEO since ’96 and then, was working in a lot of different organizations doing online courses and, that you know, I worked for a defense contracting company for a while, and that led me into to the opportunity at University of Rochester. I worked there for eight years as the director of content strategy and assessment, really looking at, you know, how our data was informing our content decisions and what we should be doing more of or less of. And then, you know, back in 2022 when Chad GPT came out, I I saw the opportunities there, and I realized the impact that this was gonna have on, you know, all of our lives, but especially on the marketing, the administrative side, and just recognize the potential it had to help. So really started diving into that. Started the Marcom AI committee at the university, ended up migrating that into our institution wide AI council.
Brian Piper [00:02:54]:
We came up with guidelines and pilot projects and, you know, really figured out how to integrate that into the, you know, the administrative landscape, at the institution. And then about a month ago, I decided that, I wanted to go out and help other schools do the same thing. So I I left the university, and I’m out on my own now doing AI integration consulting and, primarily focused on marketing admit, admissions and advancement, but also, you know, that crosses over into teaching and learning and research and all the different areas because because everybody’s using AI. So yeah.
Shiro [00:03:35]:
That’s amazing. Oh, I’d I’d love your passion to move forward and try new things. How are you feeling in that moment when you made the decision to, to start helping other schools as well?
Brian Piper [00:03:47]:
You know, terrified and excited all wrapped up, at the same time. So you never know when you start, you know, a big new chapter like that, how it’s gonna turn out. But, I had so many, you know, kind of signals along the way. People every time I go present at conferences, people asking me if I, you know, do consulting, if I could help them out. And there’s been great interest and demand since, you know, since I went out on my own. I spent the last three weeks in Thailand teaching a course on content marketing and AI. So, you know, it’s nice to be to be back in The States and really focusing on the consulting business and and growing it and spreading the word. So, yeah, it’s it’s exciting and fun, and, every institution that I’ve talked to so far is recognizing the potential and the capability.
Brian Piper [00:04:38]:
They just wanna make sure that when they integrate it, it’s done responsibly, ethically, and, you know, set up for long term success.
Shiro [00:04:46]:
That’s great. And I’m very excited for you and excited for what’s next to come. So thanks so much for sharing that with us. Well, I think you kind of led us on there perfectly. So, today’s topic is really about talking about how to integrate AI into higher ed marketing. It’s not just a tool adoption. Right? It’s not just one thing that you’re adding to your workflow. It needs a a big level of change.
Shiro [00:05:09]:
So can you tell us a little bit more about, this concept?
Brian Piper [00:05:13]:
Yeah. I mean, so many schools or departments or teams are really looking at, you know, how can we start using these tools? How where can we start, you know, squeezing AI into our current workflows? And that’s great to start experimenting with the tools. But if you’re looking at, you know, really implementing at an institutional level or really trying to make the most out of AI integration even within a department or within a school, it’s really a change management project. Because to get the most out of these tools, you have to think of it as a collaboration. You have to realize that you’re really adding, you know, more, I don’t know, entities to your workforce. And that has to be something that is not only communicated and understood at the top at the leadership level, but it has to be understood at the team level because everyone has to know that, you know, we’re not trying to replace your jobs. We need your expertise. We need your experience.
Brian Piper [00:06:15]:
We need you to be able to put in the right prompts and add the right data in there ethically, responsibly, safely so that we get the best outputs. And then we need you to be able to validate those outputs and make sure they are strategic. They are audience first. You know, they do check off all the boxes that we expect all of our, you know, human led campaigns to check off. So really looking at AI adoption as a change management initiative, and really figuring out how to get the buy in, how to increase the awareness, how to educate people so that they understand the capabilities and the risks of these tools, and how to get the most out of them. And a lot of times, it’s you know, I I I oftentimes will just start off with a presentation, then I’ll come in and we’ll do some workshops. We’ll identify some, you know, potential pilot projects, where the biggest opportunities are. You always wanna start off looking for, you know, those low risk but high impact integrations, and then get people used to using the tools, like simple ways, straightforward ways, and then you’ll gradually build up on those.
Brian Piper [00:07:24]:
And once you get, you know, a good pilot project implemented and, you know, you run through that for, you know, two or three months, then you’ve got all sorts of data about how much time you saved, how much more efficient you are, how much more effective the outcomes are, you know, how the team is adopting AI, what their, you know, what their thoughts and feelings are about, you know, pulling this new kind of, you know, intellectual consciousness into your workflows and and figuring out how to work with that. So that’s really where, you know, when I look at AI integration, I I try to look at it from that scale instead of just, you know, let’s take the work you have and automate it to make it faster. Because it’s not always about speed. You know? Sometimes you have to be thoughtful about what you replace. You know? What tasks are you replacing? Are you replacing things that people like to do? Maybe you shouldn’t be automating those. You know? So, yeah, it’s it’s a interesting and every institution is different. People are at different places. Even within an institution, different people on the team.
Brian Piper [00:08:27]:
Sometimes we’ll get some, you know, AI enthusiasts or even AI experts on the teams who’ve been using the tools for for a couple years. And then you’ll have, like, AI skeptics who are like, we shouldn’t be doing this. This is, you know, this isn’t the right way to to do this. So it’s figuring out that dynamic and and figuring out how to make it work for everybody.
Shiro [00:08:47]:
Okay. Well, you you talked about skeptical moments. Like, what are what are some common things or common things you hear, and how do you address that?
Brian Piper [00:08:54]:
Yeah. And and there are a lot of things to be skeptical about. I mean, if you just use AI and go in and just ask the tool questions and copy and paste the answers, that is absolutely gonna have an impact on our creativity and our critical thinking. You really have to get into the mindset of using these tools in a way that makes you a better critical thinker and makes you more creative. And, you know, so that’s just one thing. People are concerned about the environmental impact. People are concerned about what’s gonna happen when we reach AGI and, you know, maybe all of our jobs are replaced. What are we gonna do? And we you know, we’ve seen all of these sorts of threats from previous technology shifts that we’ve experienced and gone through.
Brian Piper [00:09:43]:
When the Internet was coming out, everybody was like, we’re all gonna lose our jobs, and there’s not gonna be anything else to do. So new jobs were created. And I think that’s the same thing that’s gonna happen with AI. You’re gonna need more people with expertise, more people with deep understanding of their industry, of the people, of their audiences, of the strategies and the goals that they’re trying to attain. So you’ve really gotta be able to look at all of that and figure out what should we be doing with AI, what parts and pieces should it be doing. And then, you know, are we putting in the best information to get the best outcome? And then are we making sure that we validate all of that? Because, you know, we’ve seen so many instances of, you know, even newspapers publishing stories that haven’t been fact checked, and all of a sudden you see all sorts of, you know, AI inaccuracies throughout the stories or, so really being thoughtful about, you know, what the risks are and how we can, you know, work around those and understand those in order to make sure that what we’re putting out is the most valuable content for our audiences, and, you know, as accurate and unbiased and, you know, all the other things that you’ve gotta think about when when you start using these tools.
Shiro [00:11:01]:
Yeah. And I I finally, like, understood a a direct connection to what management and, you know, individual contributors do. There’s a level of checks and balances between the two. Right? And so when you think of AI and content created using AI, you need those systems of checks and balances, and that’s that’s part of this, management level change that you’re saying needs to happen. Right?
Brian Piper [00:11:23]:
Yeah. Absolutely. And it’s even like, it even goes into the hiring process. So when you’re, you know, putting out, you know, job descriptions for new jobs, you need to look through those, and there are all sorts of tools out there that can help you look at a job description and figure out, you know, what areas of that job are most likely to be automated by AI. So do you really need that set of skills that you’re hiring for, or do you need, you know, someone with some AI skills that can come in and maybe do two different jobs that you’re thinking of hiring for? But you still have to hire at that, like, entry level positions because eventually, in a few years, you’re gonna need people with expertise to be able to validate and judge and critique and approve the outputs from AI. So you can’t get rid of all entry level workers because you need them to be the experts in a few years. So it’s really trying to be thoughtful about, you know, how you’re implementing, integrating, and setting your business, your organization up for success in the future.
Shiro [00:12:29]:
Okay. No. That’s super helpful. You you said at the very start of this, you when you start working with the school and start looking at how AI is set up, you really look for high impact, low risk at the start. Are there some common themes across multiple schools that you’ve looked at that you would recommend or that you see often?
Brian Piper [00:12:48]:
Well, I mean, content marketing is always a great place to start because most of the time, the data you’re looking at is, like, you know, search data, content performance data, all low risk. No you know, there’s no personal information in any of that data.
Shiro [00:13:04]:
Mhmm.
Brian Piper [00:13:05]:
And then you’re you’re just looking at either, you know, finding, identifying content you already have that has potential to perform well or looking, you know, to repurpose that content, redistribute it on different channels, retarget it for different audiences, or to do predictive analysis to figure out what sort of content you should be creating, where do you have gaps in your content. And these are all things that AI is great at at looking at your data, looking at your content, figuring out what your peers are doing, figuring out what’s trending in the market, and then figuring out, you know, what is your audience interested in and how can you test your, you know, potential content against your, you know, simulated audience members to get an idea of what’s probably gonna work and what’s not. So, you know, marketing is a, you know, a a gold mine of opportunities for these low risk, high impact projects because we spend so much of our time in marketing doing things that are repetitive, doing things that, you know, are very process driven that can be automated very easily. So and once you start, like, finding pockets of things that you can automate within your workflows and you start using some different AI tools to handle those, then you really start thinking about alright. Now instead of just making our current workflows more effective
Shiro [00:14:27]:
Mhmm.
Brian Piper [00:14:27]:
How can we really do our jobs better? I mean, how can we really work with these tools in a way that’s transformational to what we do and really think about leveraging the the full capabilities of these tools. And until you get to that mindset, which is another part of the change management project, until you get to the mindset of thinking about how can we shift, how can we, you know, let go of all of our current workflows and processes and just figure out how to do this better, how to provide more value to our audiences, how to be more effective and more efficient, and how to do more with, you know, fewer resources, which is what we’re always asked to do in higher ed.
Shiro [00:15:08]:
Yeah. I think it’s marketing across the board too. For sure. For sure. Yeah. I I I like your comment about, using AI to find gaps in your marketing. I feel like the typical use case is always, like, you already know what you want, and so you prompt that. Right? Or you request that image or audio file, video, whatever to be created.
Shiro [00:15:26]:
Right? I thought that was pretty interesting. Like, can you tell me a scenario? Is it, like, downloading and exporting your Google Analytics data, on, let’s say, program pages, and then you figure out, you know, which pages are doing better. Like, can you tell me give me an example of, like, how you would identify gaps using AI?
Brian Piper [00:15:45]:
Yeah. And there’s, I mean, there’s so many opportunities, just for this one use case. Because as humans, we are great at seeing what’s in front of us. Mhmm. But we’re not so great at seeing what’s missing, what’s not there. So even looking at, like, you know, doing, you know, conversion funnel optimization. So if you’re trying to figure out where people are falling down in your process, you can upload your Google Analytics data, your newsletter data, your social data, whatever platform you’re operating on, and figure out what’s what’s creating conversions, what’s driving traffic, where are these different pieces of content in our engagement cycle, and how can we, you know, make sure that we are pushing people to that next step of engagement at at every point. So once you’ve kind of identified all the different content that you have that’s filling the different areas of the engagement cycle, AI can look at that and say, well, you’re not getting you’re not passing people from, you know, awareness to consideration or wherever the the phase is where it’s breaking down.
Brian Piper [00:16:49]:
And then it can recommend, you know, here are some content ideas with either content types or topics, and it can really look at what’s performing well in the content that you have and say you may want to adapt this piece of, you know, awareness content and turn that into a white paper that dives deeper into that and provide that as a free download, and that may help people convert. Or if it’s, you know, trying to get students on campus, trying to get the, you know, the the campus tours scheduled, what pieces of content have worked well for that in the past? How can we create more of those, how can we make sure we’re targeting the right audience in the right location at the right time. And AI is really great at looking at all of your data, like, even your discovery data, even your search data to figure out what keywords, what phrases, what questions people are asking, how you can make sure that, you know, this is great content about your, you know, your your programs that you have on campus for your students. Let’s figure out how to turn those into TikToks, which are gonna be, you know, consumed by those students and are gonna get them to come and take a tour of your campus. So really great at looking at, you know, that the the where your funnel is breaking down, where your cycle is is stopping and not pushing people into the next phase and giving you content ideas for for how to fill that and how to fix that.
Shiro [00:18:17]:
And, like, are there are there specific tools in AI that are better for, like, these data driven tasks? Like, I I’ve just I’ve personally tried to export, like, Google Analytics data, into ChatGPT, four, and it it it felt like it almost on certain projects, it almost felt like it took longer because I wasn’t great at the prompting, in figuring out data analysis. So I’m wondering, like, if there’s if there’s a code to it.
Brian Piper [00:18:46]:
Yeah. And a lot of it is just trying to figure out what data you really need to give it, so that it can, you know, take that and and take the next leap. So a lot of times, I’ll take my I mean, because Google Analytics can be difficult to export just the data that you want, in the right format that you want. So I’ll usually take my Google Analytics data and put it into Looker Studio, make a dashboard out of it with just the pieces that I want, and then you can export that. It’ll export all of the data. Analytics sometimes will give you a truncated set of data. So, usually, I’ll start there. And then I I typically you know, because these tools change so quickly and, you know, there are always new models and new versions coming out.
Brian Piper [00:19:29]:
I’ll typically run three or four models at the same time, ask the same questions, and even kind of pit them against each other. I’ll take the output from one model. I’ll paste it in the other model. I’ll see if it agrees with that. I’ll I’ll start off with the same dataset, the same prompt. I always ask in the prompt. You know, be sure to ask me any other questions that will help you provide better output. And then when it starts giving me the output, I’ll I’ll take the information that one model gives me, and I’ll put that into a the question in the other model.
Brian Piper [00:20:01]:
And so once you kind of run those together, then you can start aggregating all of that information, take all the best parts and pieces, the things that look most relevant to your, challenge to the problem that you’re trying to solve, and then I’ll start a clean prompt with whichever tool seems to be giving me the best outputs. And then I’ll ask the question, like, where are the gaps? What are we what are we trying to accomplish with this? And some of the tools are better than others because, like, JWT has a great memory. So once you start working with that tool, it will remember what you’re trying to accomplish and what your goal is. It’s a little trickier when you’re working with, you know, other schools and and different clients, because you wanna make sure that it just remembers the parts that are most relevant to that particular client. But, yeah, I I say keep a open mind about the specific tools. And, you know, when I’m working with institutions, I tell them that, you know, even if your institution like, if you’re a Microsoft shop and Copilot is what you have access to, that’s great. But you can do a lot of things in the free versions of the other tools even if, you know, your IT hasn’t approved it as long as you’re using low risk data, as long as you’re not putting in any proprietary information about your institution. All of that stuff, I mean, that that’s a lot of times the marketing data that we use, the content data that we use is stuff that anybody could really pull for any institution.
Brian Piper [00:21:35]:
So, you know, for for those use cases, pretty much any tool is a great place to start and figure out which one’s working the best for what you’re trying to accomplish.
Shiro [00:21:43]:
Oh, that’s just great advice. I’m trying to take mental notes and probably just replay back the last ten minutes because, these are issues I’m currently facing. So, this is fantastic. Kinda taking a step back, you know, more at the management level change that is needed with adoption of AI. I forgot to ask this. Do you see, like, what kind of model from a decentralized or centralized management area of AI? Like, how how does it work? And I know it changes based on size of admin and staff as well in school size, but, like, have you seen specific models work, or is it is it different case by case?
Brian Piper [00:22:23]:
Yeah. It’s it’s very, very dependent on a lot of different factors. A lot of it is, you know, how open the leadership, like, high level leadership already is for AI integration. Like with anything, the more siloed you are and the more separated you are, the more difficult it is to get the most out of any of these tools. We’re and we’re gonna keep seeing more and more of these issues where, you know, these tools are only as good as the data and the content that they’re trained on. So if your data and content is very siloed and very separated, it’s gonna be difficult for these tools to be able to understand your entire scope, your entire landscape for an institution. So for institutional adoption, really having kind of a centralized, you know, marketing leadership, administrative, leadership group that can work across all the different teams, all the different schools and departments. It’s really the best way to go to be able to get the most out of this.
Brian Piper [00:23:24]:
Schools that I’ve worked with that have set up, like, team accounts where they can share information and share, like, you know, custom GPTs or other tools among their team and really create those conversations where everyone’s talking about how they’re integrating and how they’re using the the different capabilities. That’s where you see the biggest impact, the most improvement. Now you can still do it. I’ve I’ve worked with a lot of, like, smaller departments or, you know, individual teams, and you can still have a huge impact on your business and your workflows and find your efficiencies there.
Shiro [00:24:00]:
Mhmm.
Brian Piper [00:24:01]:
But that’s a pocket. And a lot of times, that’s a great place to start your pilot project. It’s within one team, you set up a pilot project, then you go to leadership and say, we saved 40% of the time that it takes us to create our our newsletter every week. So then you start, you know, having those proof points that you can share to leadership. And a lot of times, they know that we’re, you know, at a time right now where institutions are looking for ways to save money and increase capabilities and and preserving resources. So they’ll say, maybe this is something we should look at across our entire institution. And then you’ve gotta make sure at that point that you, you you know, you bring in IT, you bring in legal, you bring in all the potential roadblock barriers that you’re gonna face along the way. People saying, you know, we don’t have budget, we don’t have the infrastructure, and and making sure that you’re getting ahead of those so that everyone’s not, you know, seeing the capabilities and the benefits, and then they they’re, you know, road blocked by, you know, we can’t get access to the tools we need or so really making sure that you have those conversations upfront and that everyone understands the the urgency, the the capabilities, the opportunities that we face with this.
Brian Piper [00:25:12]:
Mhmm. I think that’s critical.
Shiro [00:25:15]:
Oh, this is great. And one other question that I I just thought of is, when you’re oh my goodness. I just it just I just lost it. Let me let me think about it again. But, yeah, like, moving on a little bit, I know we wanted to talk also about we talked a little bit about content marketing. We wanna also talk I wanted to also talk about AI for searchability. Right? I think there’s a statistic out there that I think I grabbed close to around 30% of traffic to websites are being are seeing a decrease of around 30%. And a lot of it is attributed to people just using AI to now search for answers and also, Google coming out with their native AI within this the search, right, and other search web browsers and such.
Shiro [00:26:01]:
How do you think institutions are thinking about, AI driven search versus, like, traditional SEO?
Brian Piper [00:26:09]:
Yeah. So, I mean, I I started working in SEO in ’96, so I’ve seen the search landscape change, but never as dramatically as it has in the last two years, probably.
Shiro [00:26:21]:
Mhmm.
Brian Piper [00:26:22]:
I was at the University of Rochester for eight years. Every year, we saw, like, a a doubling or at least a significant increase in our organic traffic. We were very focused on SEO and really optimizing all of our content. Last year was the first year that we saw a decline in organic traffic. And it’s not just due to AI search because we know that especially, like, Gen z, Gen alpha, they’re searching on social. They’re searching on, you know, short video tools. They’re searching in communities like Reddit. So the search landscape is changing, but people are still searching.
Brian Piper [00:26:59]:
People are still looking for answers, whether they find those zero click results, you know, that are that give them the entire answer they’re looking for or whether they dive deeper into content. I think the most important thing right now for discoverability for, you know, any institution is figuring out how to get your content into all of the channels where people are looking for it and to make sure that you’re targeting the right audience on the right channel, delivering the right message, you have the right messenger. And so, you know, when when I started talking with, our marketing team about the fact that we need to be everywhere now, they’re like, we don’t have the resources. We don’t have the time. We don’t have the, you know, the overhead, the budgets. And I was like, AI can help with all of that. AI is so good at repurposing and retargeting content, figuring out how to get the right message to the right audience on the right platform. So you can look back at all the content you have that’s working and figure out how to repurpose those messages for different audiences on different channels, make it as discoverable as possible.
Brian Piper [00:28:11]:
Mhmm. And then really make sure that the language you’re using is the language that your audience is using when they’re searching. So if they’re asking a question, you wanna make sure that question is in your hashtags or in your video title or in your blog post or, you know, that you’re that you’re including those and you’re looking at all of those signals as to how people search and that you’re putting out the best answer in the right language on the right channel.
Shiro [00:28:40]:
That’s great. And is is the way to figure out those questions still the old school way of basically looking up your organic search terms?
Brian Piper [00:28:47]:
Is that one just a
Shiro [00:28:48]:
great place to start?
Brian Piper [00:28:49]:
Yep. Yep. People are still searching, and and regardless of the channel, they’re all asking the same questions. So you can go look at your search console data, figure out what questions people are asking to find your website. Those are the same kind of questions they’re gonna ask on social or through AI. So trying to figure out how to make sure that your answer to those questions is the one that gets indexed and appears on those search, you know, engines is is the right way to do it.
Shiro [00:29:19]:
I know you talked about this already a little bit, but is there a difference in how you’re structuring content so that it is, more visible from AI searches?
Brian Piper [00:29:29]:
Yeah. Absolutely. We you know, I always recommend anywhere you can to use schema markup so that, you know, not only do the search engines know, like, how to read and catalog the content, but it also it makes it easier for them to feed that up because they know that it fits within the news category or within the course category or you know? So that’s one way. And then also just really looking at those featured snippets, those people also ask. Anytimes you can anytime you can put in a question, the best answer to that question, and then a bunch of supporting information or link to other places on your website or within your content that you have, you know, the the knowledge, the expertise around that particular area. It helps all the search engines see you as a, you know, as a solid resource, as a a great place to send people to get the right information. And in higher ed, you know, with with our dot EDUs and, you know, the amount of social posts that we do, our integration into a lot of these different communities, we have a natural advantage. So we should be taking taking advantage of that whenever we can.
Shiro [00:30:46]:
Yeah. This is this is great advice and tips as well. Thank you. I I did remember my question from before. So, we I do I talk to a lot of web accessibility folks from higher ed as well. And, you know, one thing that I think I see across the board with institutions that are doing a good job with digital accessibility have set up committees within the school. Is there a similar do you recommend a similar thing with AI? And if you don’t have the top down resources immediately, just creating a group within school or you can openly talk about AI could be a good starting point. What do you think about that?
Brian Piper [00:31:18]:
Yeah. Absolutely. That’s one of the first things I recommend any institution do is is if you don’t already have an AI council, you know, at the institutional level, start, you know, a group within your team or within marketing in general. I mean, that’s what we did. We started a Marcom AI committee where we found people across, you know, different marketing teams across the institution who had an interest in AI already. And we just brought them together, and we started talking about how we could use the technologies, what sort of guidelines we think we should, you know, set up. I’ve got a presentation that we gave to our leadership, you know, about why we should start this, committee. I’m glad to share that with anyone that’s interested.
Brian Piper [00:32:03]:
You know, I think that’s really the best first step is to start those conversations happening, get these people connected. And once you start sharing ideas and information, it’s gonna easily, you know, exponentially start to grow. We started off with, I think, 15 people on our Markham AI committee. And within three months, we had guidelines. We had pilot projects. We had use cases. We had a prompt library already built. So you can get a lot done quickly with a small group of people.
Brian Piper [00:32:37]:
And then when we joined the larger AI council, which was, I think we had around a 100 representatives between all the different committees that were joined together in the council, it was much easier to say, here’s all the work that we’ve already done. We’ve kind of started this. Everybody can follow our lead, and and just integrate these different opportunities within your own different teams. And then once we started sharing ideas with research and the academics teams and the clinical teams, then we started seeing new ways that we could use the tool. So really just, you know, we started doing monthly AI hangouts where we would just bring anybody together that wanted to and just talk about, you know, here’s how we’re using AI. Here’s what it here’s where it’s working well. Here’s where it’s not working well. So and I think, you know, even the engineers that create these tools don’t really know, all the capabilities of them or what we can do with them.
Brian Piper [00:33:30]:
So the only way to figure that out is to talk and share and and help each other out.
Shiro [00:33:36]:
Yeah. This is great. I mean, it’s an amazing circle back to your first opening question about what you love about higher ed, and it’s that sharing of information, the openness to help each other and how that can actually save you time and, you know, bring ideas together. So this is great. I’m I’m wondering if there’s something I could do from more of the vendor side of bringing higher ed marketers together too just because I feel like, yeah, it’s it’s definitely a bit siloed because we’re you know, we we feel like maybe because it’s competitive, we can’t talk about it, but I think there should be some more knowledge here. I agree.
Brian Piper [00:34:07]:
Yeah.
Shiro [00:34:07]:
Well, this has been oh, go ahead.
Brian Piper [00:34:09]:
I was just gonna say, you know, when I I came from a a defense contracting company where no one could talk about anything they were working on. You know?
Shiro [00:34:16]:
Right.
Brian Piper [00:34:17]:
And I went to my first higher ed conference and sat down at a table, and within five minutes, there were eight strangers telling me about all the tools they were using, all the tactics they were trying, and what was working, and what what wasn’t. And I was like, this is this is where I need to be. These people are just trying to figure out how to do things better, and I think AI is the perfect, you know, technology to try to figure out and work together to come up with the best solutions. So
Shiro [00:34:45]:
No. This is great. Well, I’d love to ask also, like, you know, what’s next for Brian? What’s next for you? I know you’re in this transition phase right now.
Brian Piper [00:34:53]:
Yeah. You know, just trying to to help as many schools as I can figure out how to start leveraging this technology. I think higher ed has been kinda doing things the same way for a long time, and I think we’re gonna see a lot of that shifting. I think we’re gonna see, you know, a real impact of AI on higher ed. You’re not gonna be able to just, you know, have an institution that focuses on, you know, knowledge transfer anymore. It’s gotta be it’s gotta be more than that. You’ve really gotta start figuring out how to teach the next generation of workers how to work with these tools, how to integrate these technologies into, you know, their lives, their careers, because it is so transformative. I mean, I can’t imagine doing my work without AI anymore because it has allowed me to, scale and, you know, expand my offering so much.
Brian Piper [00:35:54]:
I I wouldn’t wanna go back. But at the same time, you have to be cautious about letting it, you know, replace your creativity or, you know, have it do all your writing for you. It’s there are downsides to all of that. So, I think finding that balance, and continuing to pay attention to what’s going on in the AI landscape at the same time, trying to figure out how to get as many institutions as I can, you know, up to the next level.
Shiro [00:36:23]:
Oh, that’s fantastic. And, yeah, I I don’t know what I would do without it anymore as well. I’m wondering where listeners can learn more about, you know, your, your services, your content, newsletter. Yeah. Feel free.
Brian Piper [00:36:37]:
Yep. You can find me at brian w piper dot com or brian w piper on pretty much every social channel. So
Shiro [00:36:44]:
Well, awesome, Brian. It’s great to have you on the show again, and I’m very excited to continue to follow everything you’re up to on LinkedIn and probably have you on again in in, like, six months or a year.
Brian Piper [00:36:55]:
Thanks so much for the opportunity, Shiro, and thanks for all the great content you’re always putting out. Super helpful.
