How Community Colleges Are Pioneering AI Education
Artificial intelligence is reshaping work, leaving many people wondering how to gain the skills they need to keep up with a rapidly changing world. Now, a group of American community colleges is working to democratize AI education and prepare students for the future.
On this episode, host Sara Frueh is joined by Antonio Delgado, vice president of innovation and technology partnerships at Miami-Dade College and founder and leader of the National Applied AI Consortium. Delgado discusses “applied AI,” a pioneering program at Miami-Dade that provides students pathways to these jobs, and the broader effort by community colleges to help meet the need for AI-fluent workers in the labor force.
Resources
- Check out Antonio Delgado’s Issues article, “Community Colleges are Training the Applied AI Workforce” (Summer 2026) to learn more about how he developed Miami Dade College’s applied AI degree program and founded the National Applied AI Consortium.
- Visit the National Applied AI Consortium’s website to learn more about their work.
Transcript
Sara Frueh: Welcome to The Ongoing Transformation, a podcast from Issues in Science and Technology. Issues is a quarterly journal published by the National Academy of Sciences and Arizona State University. I’m Sarah Frueh, an editor at Issues.
Artificial intelligence is already reshaping work, leaving many students and workers wondering how to gain the skills they need so they won’t be left behind in a rapidly changing labor market. In response, a group of American community colleges is working to democratize AI education with the goal of helping students and current workers learn to apply AI in a wide range of jobs.
I’m joined today by Antonio Delgado, vice president of innovation and technology partnerships at Miami-Dade College and founder and leader of the National Applied AI Consortium. He joins us today to talk about jobs in applied AI, a pioneering program he developed at Miami Dade to provide students with pathways to these jobs, and the broader effort by community colleges to help meet this need in the labor force.
Antonio, welcome. Thanks for joining us.
Antonio Delgado: Thanks for having me, Sara.
Frueh: So I think it was back around 2019 or 2020—before ChatGPT started a lot of us thinking about how AI will impact work—you started to notice the need among employers for what you called applied AI. Can you talk a little bit about that? What you were seeing employers looking for, and what do you mean by applied AI?
Delgado: You’re right. Like around 2019, we were thinking about what are the future jobs, like what do we need to start doing now for the new jobs that are gonna be created and our students getting an opportunity into those jobs. We realized AI has been there for years. AI has been in academia for many decades, but always from a graduate level, master’s, PhD, never at the undergraduate level, thinking about technicians and thinking about specialists that could understand AI, not from an AI engineer, but actually more on the basic foundation on how to apply AI, and the application coming from basic understanding, not on how AI is developed, but how AI is applied to any business so businesses can actually evolve and implement AI.
And at the same time, we were thinking on, yes, we see these comments that AI is gonna come, it’s gonna create new jobs, but it’s also gonna displace people from their jobs. And we were thinking, if that happens, like who’s gonna retrain all those people that, that need to get these AI skills? And if AI education is only at the graduate level, then not everyone will be able to afford it or to actually have a chance.
So we started thinking, what is artificial intelligence for everyone? And how can we actually get anyone, doesn’t matter their background, with AI skills, and to start building from there and stack credentials so they can actually get meaningful experience to implement AI. And if they want, they can get a full degree, associate, bachelor’s, and then they can continue into graduate level programs.
So this is our thinking. We started validating with employers, and they were having challenges finding talent that understood the foundation, not from a theory perspective, but foundation on data and applications for machine learning projects. and the technician level of understanding that we see in other fields, but didn’t exist on AI. And we started working with them.
We developed the concepts of a brand-new program, no prerequisite, to start learning about AI, then start building the prerequisites as the students could advance into machine learning and computer vision and NLP, and then we complete with an associate degree. And then why don’t continue into the two-plus-two modality that community colleges can implement and then have a more advanced content that completes a full graduate in applied AI. So, we developed that for a year.
We started working with companies like IBM, Microsoft, AWS, Google, and we started doing training for our faculty, and then we connected with Intel, that they had curriculum specifically developed to help faculty understand AI from an applied perspective. And then boom, we created this first associate degree in the state of Florida. and barely we got 30 students in that class. It was hard to get 30 students in that first class. But then ChatGPT happened, boom, many people started worrying about, “Am I gonna lose my job because of AI?” and “How can I learn AI? Where do I start?” And we had a program that was developed for this moment. So, we launched from barely having 30 students to join an AI class to 750 people registering the moment that the associate degree was launched, and it was because of ChatGPT.
Frueh: But what a big challenge. Were you equipped to deal with that high of an enrollment right off the bat, or did you have to scale up your program immediately?
Delgado: The good thing about community colleges, we’re open door institutions. So we don’t have an enrollment cap per program, and it’s basically based on demand. And this was a very unpredictable demand that came up running from 30 students in a class to suddenly 750 students that want to start taking classes. And so, it was a good problem to have and we were working during that time on upskilling our faculty. There were no books on how to teach this applied AI concept by the time that we were doing it. And great, we have a body of faculty ready, but even that group was not enough, so we had to quickly start hiring and training adjuncts to teach for the program and that was only the first year.
The second year, we doubled the demand. 1,500 people coming, wow, through our doors. So, we just closed the third year of the program last academic year, and we closed with almost 2,000 people. And we’re excited to see, yes, community college can definitely meet this demand that exists for applied AI skills, and we can see automatically how the students and the population that we’re serving on these programs are coming back to the workforce and putting those skills to practice.
Frueh: I’m hoping you can say a little bit more about the nature of these jobs that people are training for in your program. How many sectors are these applied AI skills relevant to? What are examples of some of the kinds of jobs where your graduates will be using these skills?
Delgado: So, the first part of the question is not about one sector or another. This applies to every single sector. How are you able to understand any business or any process and then bring an AI solution to it?
And that applies to pretty much everything that goes through a computer. At the beginning, we were thinking about the future. Now that future is here. That future is happening faster than we thought, and we didn’t know the exact names of titles and positions and even industries that will be completely disrupted.
Now we see that, again, it’s touching at every level, every sector. And then regarding the roles in particular that we have seen a transition of, roles that didn’t exist and now, an easy one is AI data annotator. That’s growing exponentially, as the learning models are growing, you need this position. And then automatically we’re seeing our students getting those jobs easily. Without knowing about that role when we created the program, this has become, automatically a channel or a pathway for those particular roles. And then recently, many different roles that, of course, AI creator, AI strategist, AI specialist, or machine learning technician, all those roles, like we see the pipelines and how our students, they land into those particular roles.
It could be any company, marketing, healthcare, even government, doesn’t matter. I never imagined how quickly this will ramp in a direction that every position that requires this AI level of expertise is open to even consider an associate degree graduate. I’m not even talking about bachelor’s, and I have students going in that direction, but this is not even about a bachelor.
This is about a foundational level of skills and understanding of implementation of those skills that my students or graduates are already, demonstrating that it’s possible. and with meaningful salaries, again, maybe not the six-figure salaries, but still getting an opportunity to the entry-level roles for these new job descriptions that are being created.
Frueh: So everything in AI, when you talk about training for these jobs, preparing for these jobs, everything in the technology, how do you stay on top of that and make sure that what you’re teaching students matches employers’ needs as the technology evolves?
Delgado: Great question, and that’s really a core concept of everything that we have done since day one. Again, we created a program that didn’t exist at a community college level, and we didn’t have the expertise to do it, so definitely we didn’t do it by ourselves. We went to the industry experts, AI experts that were in the field in big corporations doing AI, and they couldn’t find the talent that they needed. So we created what we call business industry leadership team to recruit these people to help us. What are the knowledge, skills, and abilities that you need to hire for but you’re not finding specific to AI? How can we build the learning outcomes? It’s around 20 people, these high-level companies, and that feedback is what our, my faculty were able to transform into learning outcomes.
But the moment that I mentioned, when we launched the program is exactly when ChatGPT released the concept of generative AI and LLMs. That was not part of our program. That was not included because that was completely new to the public at that moment. And then, okay, great. Let’s go back. And that’s why we have built this business industry leadership team. Meeting three times a year and doing the KSA analysis once a year, discussing trends, and then connecting with faculty on the retroactive feedback on how that’s transforming the curriculum. Education is always gonna be behind the evolution of technology, of course, but how behind we are, that’s what we want to shorten that timeline.
So this iterative process to connect with them really helped us continue evolving to the point like, great, we brought LLMs, we brought generative AI, but guess what? Now we’re talking about agentic AI. No problem. Let’s do it again.
That’s a reality for even faculty and their professional development to be able to teach this that they know. It’s not only the curriculum, it’s themselves, that they have to upskill constantly, and that’s why we are paying a lot of attention and support on the constant upskilling of faculty so they understand, what is the evolution in the field, and how can they teach this content to our students?
We’re not afraid of the evolution of the technology. We continue bringing this to our students, and we have a meaningful process that the feedback comes from industry, and then we connect that back to our faculty and students.
Frueh: Who are the students who are enrolling in this program? Are they mostly people who are already in the workforce? Are they younger and just pursuing a degree for the first time?
Delgado: And that’s exactly what we were not able to predict when we created this program. Of course, we’re a community college. We are serving traditional college students. Many are… the main source is high school students come to college, and they continue. We know that we are serving adult learners.
When we created the program, what we never expected, the minority of participants will be above 26 years old. Even more unpredictable, when you divide by decades the age of these groups, the largest decade was 41 to 50 years old. So one third of the participants were above 41 years old, and that has never happened, period.
This is a workforce that was out of education for actually decades, and they are coming back now because they see the need of learning AI. And also, this is a population that cannot necessarily can go to YouTube, TikTok, or Coursera to learn by themself. They need an instructor. They need to be in a classroom environment. They need classmates. They need to learn in the right setting, and that’s what community colleges could provide to them. But why community colleges? I don’t think that they were thinking, “I want to go to a community college.” But they saw that what we were producing and what we were offering was exactly what the market needed.
It’s applied AI. You don’t need an advanced degree. You come learn skills, and you can go back to apply those skills automatically. Two, it’s affordable. Way more affordable than other options. And three, it’s accessible. It’s not oh, if you come with a master’s degree, I can accept you in my program, or if you come with a computer science degree, no. It’s accessible to everyone. It doesn’t come with limitations or previous experience because we wanted to do it that way. So that’s a huge factor that I’m glad we did it that way because they became, minority of participants in the program.
Frueh: I remember also, I think in your article, you wrote about the significant percentage of women. Was it 40% or something like that? That struck me as interesting just because compared to other computer science programs, that’s pretty high.
Delgado: And that’s something that I’m… I was super excited, to see in the data, of participants how this is not perceived as, the typical man-led type of STEM programs. Typically, female representation in those programs is around 20%. Give or take. And I would love to see a 50/50% distribution, but again, 40% female shows, this is great because this is AI for everyone. Everyone should be able to have the skills to apply those skills into the workforce.
Even when you’re not thinking about getting a full degree, you can come take three classes, and you get a certificate on your foundational AI. But many of the participants when they came in, they automatically saw, “Oh, but I like this. I can learn more. This is not as hard as I thought.” And they continue taking more classes, so it’s really easy for anyone that comes to the program to come in and out at any point. There are no barriers for me of entry, and anyone can actually learn, and I’m happy to see the outcomes.
Frueh: Speaking of outcomes, what do you know so far? I know it’s still pretty early in the arc of this program, and you may not have a lot of hard data, but what do you know about the outcomes so far, either in terms of data or just more anecdotally what you’re seeing happen for students?
Delgado: So what I’m seeing based on data will be three years of full implementation. I see students that come for just the foundational skills, and they go back to apply those. Because most of them are working already, they’re applying those skills into what they do. So they are making themself available for the future in, within the same company, or many are switching into new roles. The graduates especially when they are getting into these new positions that didn’t exist before. Others surprise for me because, again, when we created the program, we were not thinking this way.
Everything is work-based learning, and they’re working on projects that they have to present. They’re not here for a grade. They’re here to really learn, and they’re working on a meaningful project. Suddenly, that project becomes a startup, and that project becomes like, great, like a potential revenue generation and it’s incredible what the students are doing as projects for every single class. And at the end of the program, the final class on the associate at least is this capstone where they put together everything that they have learned, and they work with real projects from companies, and that’s where we see the evolution.
Some of them are creating products, potential startups. Others are just convincing those companies, “Great, can you stay with me, as a full-time employee working on AI transformation?” And where I see the evolution going is that this is only gonna increase because, of course, AI continues evolving, but every company is being forced to really find ways to do AI transformation.
Frueh: So Antonio, after you established your program at Miami-Dade, you decided to try and expand this idea and help other community colleges develop their own applied AI degrees. Can you talk a little about how that evolved?
Delgado: Yeah. The moment that we launched the program and it became so popular, not only in Miami, like nationally, I started receiving pretty much emails, phone calls, LinkedIn messages all around, like of especially community colleges that wanted to learn, like how you did it.
Can you share your curriculum? How are you training your faculty? All kind of questions like to visit us and to see what we are doing and to learn from it. And of course, we always thought about, yeah, we’re doing something that hasn’t been done from a community college perspective, but always thinking like, how can we share this? We were still updating curriculum, and we’re getting this huge demand that we wanted to help, but we didn’t know what is the best way to do it efficiently. At the same time, a couple of other community colleges were doing the same we didn’t know about until later. Houston Community College, of course, in Texas, and Maricopa Community Colleges in Arizona, we quickly connected.
Yes, we’re doing the same concepts just with different flavors. Maricopa was the first one doing it at the associate level back in Arizona, connected with Intel with their offices and headquarters based in Arizona. And then Houston was more in the robotics side, playing with the bachelor in robotics with AI. But the three of us had different flavors of the same idea with artificial intelligence and the easy adoption and introduction to AI, at the undergraduate level. So we decided to join forces. How can we help all community colleges in the nation together? And we went to NSF. We sent this proposal as let’s create this national group of colleges supporting in artificial intelligence.
We landed this grant, multimillion-dollar grant, to do a national applied AI consortium, that the focus is 100% helping community colleges and how they can do it. If we were able to do it, this is possible anywhere in the nation through community colleges. So usually, colleges don’t have the funding or don’t have the training or don’t have the connections with industry to help create these programs that quickly at the national level.
They have the connections locally, but, artificial intelligence is new. It’s happening. This is 2024. There is a lot of excitement, but not necessarily knowing, like, how to transform excitement into an actual program and how to teach for that program. We launched this initiative, and it skyrocketed.
Huge demand for community colleges, educators, and from the industry perspective as well. Big companies care about, like, how can we support AI education? These companies are creating the technology. They’re also creating resources to support academic institutions. Like Intel developed a curriculum.
Microsoft had certifications and Microsoft Learn for Educators. AWS had AWS Academy and Google had Grow with Google, and others are creating their own programs. IBM with IBM SkillsBuild. All these opportunities are there, but these companies don’t have the bandwidth to work individually with every single community college or university, and it becomes a bottleneck.
So suddenly you have this consortium that is actually serving as really the bridge to connect with all these resources at no cost. With the funding from NSF, we were able to create this platform that is providing professional development to faculty at no cost. And the professional development is actually in collaboration with these companies.
Again, we’re not the experts on what’s happening with AI. We know how to connect with the companies that are evolving the technology and the resources to support faculty, so we partner with them and we have faculty professional development for free. In two years, we have trained over 3,000 faculty from all over the nation.
Then we have resources, a curriculum that is already developed that you don’t have to reinvent. You can just download it. We created a resource hub just to add all this content from companies, from community colleges, and it’s available for free. Anyone can download it. We have 1,500 people registered on that resource hub and downloading content.
And when I say people, it’s really from academia. It’s specific to faculty and administrators with an EDU account. They can go and they grab the content, and they use it as they see fit. We also have a mentorship program. Sometimes the training and the content are not enough. Colleges need the support, a full mentorship.
How can I make it work? And that’s what we provide for a full academic year. We select a cohort of colleges every year, and we work with them for a full academic year. We have done already almost 20 colleges, and all of them are implementing their own AI programs. and following the experiences from these three leading colleges, now they are doing the same at their own location.
So again, super exciting initiative because it’s really helping community colleges all around the nation. We’re touching every single state. We have supported over 900 institutions, by the way, not only community colleges, also universities and even high schools, and it continues growing
Frueh: As you work with all these colleges and faculty to help them respond to this new need in the workforce, to help them train their students, what challenges do you see them having to navigate?
Delgado: So yeah, the challenges that we have discussed already. The technology is constantly changing. So yes, it, the reality of the students that come through your program, they will have to adapt because the technology is changing. Of course, you, the faculty, institution, you have to adapt to be able to serve that student well.
So that’s number one. It’s like that mentality of growth and adaptability is not just for the students in the program, it’s for everyone involved, faculty, administrators, institutions at large. And then, a challenge that we discussed is when you start offering this and, who can teach this for this program? And great, you, that’s the upskilling that we’re doing. We recognize that the number one is the faculty. You need the faculty ready to teach. But then comes the scalability. suddenly, like you got 750 people, right? You say, what do you do about it? So it’s also like the challenge is to find enough candidates, with the skills, the academic skills, but definitely the technical skills to be able to teach this content.
That’s always an ongoing challenge. and definitely for institutions that are new, it takes longer, but it is something like to work actively on, again, the professional development and finding full-time or part-time educators that can be trained quickly to be able to deliver.
Other than that, it’s really, AI is expensive. That’s a reality. So the more advanced courses and content that you start teaching or the more advanced projects the students are working, it comes at a cost. So it’s definitely building on the sustainability component on how to make it effective and how to, public institutions, community colleges bring in the local support ecosystem from local government or the state to be able to help educate the students with the right tools and the right access to opportunities.
That is still expensive. and I think that more and more, there, there are more resources that are becoming available and that are supporting higher education. But definitely we need more of those to be able to support AI education at scale.
Frueh: So it sounds like funding is a big piece of what these schools need. Are there other, policy supports that you wish state or federal governments or local governments would put in place to make this work easier?
Delgado: I see this coming more and more now as infrastructure. It’s not that every institution needs to build their own AI infrastructure, but at least access to infrastructure that is available to everyone. And there are initiative from NSF. They created NAIRr, shared resources for faculty that when you have to teach with certain infrastructure or, capacity, you can just go through them, and you get it for free. And then we see more and more on how this is happening at the state level, like funding coming to create infrastructure hubs that academic institutions can join.
From a proximity perspective, it’s definitely easier, and creating those relationships that not every institution will have a full AI infrastructure, but they can connect to resources for their students, either research or projects that they’re working with. They can have meaning- use meaningful tools and processing capacity, compute power.
And so more and more we’re seeing that and of course, the companies, the big companies, AI frontier companies also working on finding solutions to make it either more affordable or a- or at least accessible for institutions, we’re not there yet, but I see more intentionality going on that direction.
So I think that, yes, in the future, this is gonna be cheaper and definitely more accessible for those that cannot pay for it.
Frueh: What has surprised you as you’ve done all of this work around AI? You foresaw a lot. What didn’t you foresee?
Delgado: I definitely didn’t foresee how quickly this AI revolution will happen, and I’m happy that we were prepared, but definitely not 100% prepared.
I think that no one was prepared for that. But now where we are three years later is really, like, how quickly this is going. And the surprise is to think, can a community college be part of the solution? I don’t think that anyone would have bet, three years ago, yes, of course, a community college can help you get a job in AI.
Like, no, not necessarily. But now we see that’s what’s happening, that the nation needs a huge workforce at scale in AI. And again, on every single sector, and there is not enough. So at a time that many people are questioning, entry-level jobs disappearing, some roles disappearing, other jobs being created, this is a chance to get into those new jobs. And it doesn’t come only at the graduate level opportunity. It comes at the undergraduate, even only with an associate degree. So that was a surprise, but a very positive surprise to really validate our original vision. And now is very gratifying to see that happen.
Frueh: I bet. I’m looking forward to seeing how this all unfolds in the future. Thank you very much for joining us today, Antonio.
Delgado: Thank you again for inviting me.
Frueh: To learn more about the National Applied AI Consortium, read Antonio Delgado’s piece in our Summer 2026 issue called “Community Colleges Are Training the Applied AI Workforce,” or visit their website at www.naaic.ai. Find links to these and more by visiting our show notes.
Please subscribe to the Ongoing Transformation wherever you get your podcasts and write to us at podcast@issues.org. Thanks to our podcast producer, Kimberly Quach, and our podcast technical director, Roddy Nikpour. I’m Sarah Freuh, a consulting editor at Issues. Thanks for listening.