Dr. Joe: [00:00:00] Welcome to Safe and Innovative Schools. I'm Dr. Joe Phillips, and today we're going to be talking about Plant AI, a framework that I created to help schools and educational organizations build robust AI ecosystems.

Dr. Joe: As an educational leader with lots of experience in innovation and technology work, I have seen the power that AI can have on educational institutions. I've also seen what can happen when these organizations jump in too far too fast when doing an AI adoption, and not making sure that they have everything in place prior to trying to bring in an AI tool.

I've also seen the opposite happen where educational organizations, schools, districts, universities have been hesitant to even dip their toe in the water of AI because they don't know where to start and they don't know how to proceed. And that's really what has inspired me to come up with this PLANT-AI framework for how we can bring [00:01:00] AI into educational organizations in a very structured and methodical way so that we can build a very robust and solid AI ecosystem.

To help understand the framework, I've built an analogy to go along with it, and it's one that I think that most people could relate to, and that is building a garden. So that is, how do we plant and grow AI ecosystems inside of our educational organizations? And just like a garden is not a single plant, AI is not a single tool.

It is an ecosystem that we have to grow and develop within our educational organizations.

And just like planting and growing a garden, successful AI implementation requires careful planning, preparation, and consistent, constant tending.

Each letter in the plant AI framework represents a key phase in the AI implementation journey.

Plan and align vision, learn, assemble data and infrastructure, new automations, team up, autonomous agentic capabilities [00:02:00] with oversight, and innovate boldly.

So here's the thing. Gardening is more than just planting some seeds in the dirt. It's about creating an environment where growth is possible. It takes planning, nurturing, and tending to every detail. The same philosophy applies to AI. Moving forward without a plan, without a strong foundation, and without tending along the way will lead to disappointing results . Educational leaders must think like gardeners. Establish clear principles and policies. Establish safeguards and ensure alignment with your goals. Just like gardeners pull weeds, enrich the soil and fend off pests, school leaders must constantly tend their AI ecosystem to keep it healthy and responsive to change.

Okay, so let's actually dig into the model here. So the first letter is P for plan and align your vision. Every great garden starts with careful planning, with learning, and with preparation. The PLANT-AI model guides you through these [00:03:00] essential steps, ensuring that your AI ecosystem grows intentionally and sustainably.

Start by mapping out your AI use cases into three categories. Explore now. Use cases that align with your current goals and your readiness. Explore later. So they're promising ideas, but you're not quite ready to dig into those yet. And explore never. Maybe we're never going to be interested in having a Tesla self driving school bus in our school district.

So what is an AI use case? Well, an AI use case is a specific application of artificial intelligence designed to solve a problem or to achieve a goal.

For example, you might automate progress reports for parents and teachers, use AI tools to assist with adaptive lesson planning, implement AI systems to optimize campus energy usage, or develop immersive virtual field trips powered by AI and virtual reality.

By identifying and categorizing these use cases into the Explore Now, Explore Later, Explore Never [00:04:00] categories, you can focus in on those impactful initiatives and ensure that every one of the actions that you take aligns with your organizational goals.

Or to put it another way, choosing your use cases for AI is like choosing your plants for your garden. You might be comfortable starting with growing some simple herbs and some tomatoes, but maybe you're not ready for some more challenging or robust plants. Maybe you're not ready to do a hybrid orchid , as an example.

Choose those use cases or those plants. plants for your garden that are going to be simple and get you those quick wins right away that you can build confidence and build from there.

The learn phase is this class is about building AI awareness and AI literacy throughout your educational system across your organization. So that is everybody, your educators, your staff, your students, your leaders, everybody needs to understand those basics.

So kind of like how you might know what plants you want to put in your garden, if you've never gardened before, you need to learn a little bit more of the basics and the truth is the same [00:05:00] for AI. No gardener starts out knowing everything and nobody that is implementing AI into their educational system is going to know everything about AI. So before you can plant, you really need to understand those basics, what tools to use, how to handle challenges that might come up .

And there's some questions that we really want to answer inside of this learn phase of PLANT-AI.

And that is, what is AI for and what is it not for? Who can plant and who can harvest? What are the rules for how AI should be used? Which specific AI solutions can be used and which ones cannot be used. When everybody inside of your school system has a shared understanding of AI's roles and most importantly the boundaries of AI.

You can create the confidence and trust that is needed for your AI ecosystem growth.

The next letter is A Assembly and Assembly is about preparing the soil of your garden. And when that comes to [00:06:00] AI, that is talking about your data and your infrastructure. Just like your gardener can't just throw seeds in the dirt and expect it to grow.

We can't just start bringing in AI use cases if we have bad data, bad data ecosystems and infrastructure that is not ready for AI and expect that we're going to have a lot of success. We need to make sure that we are getting our data into a unified ecosystem. So whether that's a data lake. a data warehouse or some other solution that you have to get all of your data into the same location or the same ecosystem because data is what AI feeds off of in order to get the benefit out of it.

You also want to make sure that you have a good, robust infrastructure, whether that's your network infrastructure, your servers, your cloud computing, and that you have those enhanced security measures and safeguards that have been put in place around your infrastructure. You have to make sure that you're protecting the sensitive data that AI is leveraging and using. That you're using proper [00:07:00] encryption, role based permissions, and access controls, and that we're having compliance with federal laws like FERPA, COPA, HIPAA, CIPA, GDPR, if you're in the EU, and any state laws that garner the protection of that data that you have with your students. There's some AI tools that are out there that will tell you that your data is safe and you're FERPA compliant, for example, if you don't put the privately identifiable information, or PII, of your students into that tool. And that's not accurate. And so we have to make sure we have those safeguards in place and we want to build a resilience. equip our ecosystem to handle any challenges that might come along, by training staff in cybersecurity best practices and implementing our tools that identify and mitigate the risk that could come up.

The truth is AI is a technology tool and we have already seen inside of K-12 and post secondary institutions that we are a big target for [00:08:00] cybersecurity attacks and AI is no different.

So we've gotten our gardener's mindset, we've planned out our garden, we've learned about the garden itself and what use cases or tools that we want to put in the garden, and we have started to assemble the dirt to make sure that our data is clean and ready, our infrastructure is good to go, and now it is time to start planting inside of our garden.

And that starts with the letter N for New Automations. These use cases are really your starter plants or those herbs or tomatoes that I talked about earlier. They are the easy wins that can simplify repetitive tasks that our teachers and staff do throughout the district. These are things that are going to free up time and allow your staff to focus on more impactful work.

Best of all, many organizations have already actually gained some valuable experience when it comes to growing and developing some successful automations. So a lot of districts might already have attendance calls that go out. Well, that's an automation that if you [00:09:00] go and you take attendance and then your student information system goes up to your call out system and sends those calls, that's automation.

And so you might already have experience automating some tasks and some scripting. AI just brings in a different and higher level of that. As an example, you might have a chatbot for your website that scrapes all the data off of your website and puts that into a chatbot. And now if a parent or a community member or student goes to the website, they can ask that chat bot some questions and it gets automated responses.

The next type of use case or plant for your garden is what I call team up. Team up are these plants that thrive when humans and AI collaborate together so they can enhance efficiency and outcomes by really pairing the human creativity and AI capability. Some examples that we have seen of some Team Up use cases could this generative AI that's really, that has come out.

So whether it's chatGPT or Gemini or Sora or some of these other tools that [00:10:00] allow teachers and staff members to use their minds, use their creativity, but use the generative AI features that come along with some of these tools in order to help make them more productive themselves. Some instructional examples would be using AI to co create personalized lesson plans that tailor to students strengths and needs, or incorporating AI based

augmented reality tools to overlay some 3D visuals onto science experiments or history lessons, and making concepts more tangible and engaging. On the operational side, some examples could be AI assisting HR departments in identifying professional development needs and opportunities for teachers by analyzing staff performance data, or collaborating with AI systems to identify energy usage trends and recommend cost saving measures for those school facilities.

The A in Plant AI is for autonomous agentic capabilities. And I know that that's a mouthful, but [00:11:00] really what that is about is plants that can thrive on their own. So maybe a cactus, it doesn't take a lot of effort to grow a cactus. It can pretty much take care of itself with very little intervention.

But you still might need to provide some oversight for that. Autonomous AI systems that can handle some complex tasks on their own is really what we're talking about with agentic capabilities. So very little human involvement and very little human effort that are required for these agentic AI applications and tools to do their job.

So this can free up educators and staff to focus on really high value work. Some examples of that might be an AI based tutoring system that's available to students 24/7.

It is autonomous. We still want to make sure that it has some human oversight, but it can respond to those students 24/7. And as long as it's built properly and effectively, it's going to actually tutor the students autonomously. While letting us, see that information, making sure that it's going [00:12:00] to a safe and secure environment and that, the students are actually still learning and not just getting the answers like they would potentially from chat GPT or something like that.

Another example could be AI driven teaching assistants, and actually with agentic capabilities we could have an AI teaching assistant that is specialized for each student. That's really a way to help the teacher out with understanding what's going on with each student, preparing and differentiating instruction for those students, maybe potentially giving instruction in different modalities, or teaching Tearing instruction for students all at the same time, allowing teachers to really focus in and ensure that mastery of that content is happening.

We can also see some behavioral trend monitoring with agentic capabilities, some lab equipment optimization. Cybersecurity threat response is an agent, a capability that we're already seeing come in with some Microsoft copilot for security, some energy management systems that can see what trends are happening and potentially take some [00:13:00] actions on their own based upon different triggers or events that have been set up and some AI powered scheduling.

Okay, so when it comes to your bold statement plants, those exotic transformative projects that we're going to be bringing in with AI. This is where the I in plant AI comes in, and that is innovate boldly. These are, again, your transformative projects that can really redefine how the garden or your school system works.

So once your foundation is strong, once you have worked on some new automations and you have some agentic AI going, you can start to really look at innovating boldly. That is looking at some things like immersive AI driven experiential learning where students can step into hyper realistic virtual environments powered by AI and virtual reality to experience moments in history, participate in scientific breakthroughs, or tackle societal [00:14:00] challenges.

Imagine a student working alongside of Albert Einstein in a virtual lab to understand relativity. Or collaborating in a simulated United Nations to solve global crises . Where AI generates realtime feedback based on their decisions, their communication skills, and their cultural awareness.

Another example could be AI facilitated peer collaboration, where AI powered platforms that match students for collaborative projects based on their complementary strengths and interests. For example, a platform might pair a student with strong analytical skills with a peer that has excellent creativity to design a sustainable city in a virtual simulation.

Some other examples on the operational side might include advanced resource management with robotics. So combining AI with robotics to automate and optimize resource management, perhaps, some logistics at the warehouse . There's even some robotic AI based janitors, that are cleaning buildings out there.

So, [00:15:00] definitely some depth that we can get into as we start to look at these

innovate boldly use cases. We can also see some AI driven crisis intervention or response systems where they can centralize emergency management and provide real time insights during crises such as natural disasters, cybersecurity breaches, or campus safety incidents.

During a severe weather event, AI could identify safe evacuation routes, track students and staff locations, and send real time updates to parents and emergency services, all while coordinating campus response teams.

These examples are not just enhancements, they are game changers, and we want to make sure that Because they can absolutely reimagine education and operations that we're not taking these things lightly.

We're not just jumping in to these innovate boldly plants or these innovate boldly use cases. And I'm going to talk about that next.

So we've talked about having that gardener's mindset. We've talked about the planning that is involved and needs to happen with bringing [00:16:00] AI into your educational system. The learning that needs to happen, the assembly of the dirt or your data in that infrastructure and the types of plants or use cases that you can bring into your garden.

But there's a couple of considerations that we want to make sure. That we keep in mind as we go down this journey of bringing AI into our school systems. And the first thing that I want to bring up is going slow to go fast. New AI tools are sprouting up constantly, but just like planting too many plants at once will overwhelm your garden and hurt what's already growing, going after and trying to keep up with the pace of AI innovation is just not possible.

And if you try to keep grabbing those new AI innovations and bring them into your school system before you have that foundation ready, before you've done your planning, your learning, assembled your dirt and gotten that experience with those earlier and easy to grow use cases. You're not going to be ready to even try to keep up with the amount of [00:17:00] innovation that is coming. The truth is AI is advancing so fast that research cannot even keep up with it. We're having to get new articles and research papers before they are getting peer reviewed to just try to keep up with the pace of disruption that is happening in the AI space.

But just because that pace of disruption and innovation is happening in the AI space does not mean that that is what we need to bring into our school systems. We can follow a methodology that is structured and leverage those AI use cases that can really bring true benefit into our educational systems.

And so we don't have to try to keep up with the Joneses when it comes to AI.

The next thing I'd like to talk about is harvesting with care or ensuring that sustained growth. So one of the biggest mistakes I see in AI adoption is districts or schools or educational organizations trying to jump straight to that harvest, trying to grab some AI solution off the shelf or have it built for them because they're going to do something [00:18:00] absolutely amazing and game changing.

But they haven't set up their garden yet. We want to make sure that we're not just trying to plant seeds in the morning and harvest in the afternoon. We want to go through the phases and make sure that we are ready. You can't just grow vegetables without preparing the soil, planting the seeds, and nurturing those plants.

The same principle applies to AI initiatives. jumping ahead to ambitious projects like predictive analytics or immersive VR experiences without building strong foundational clean data without having basic automations in place and learning and growing with that it'll lead to shallow roots and disappointing outcomes.

For example, a district that skips those foundational steps, like unifying data systems, may struggle with inaccuracies with AI driven reports.

Garbage in, garbage out, is the saying with data, and so you might have bought or built a really cool, amazing AI reporting tool, but the data itself isn't clean, and so you're getting inactionable [00:19:00] insights. And this can lead to some challenges, so let's say that we're trying to do some predictive analytics to see which students might need some just in time interventions for example. If your data is not accurate or it's fragmented in the wrong places, two things could happen. One, the students who need those interventions might not be getting identified. Because, two, students who don't need them are getting identified. And so what we're doing is we're ineffectively allocating resources because of the bad data.

We might have this amazing platform, but because we're not in the place where our dirt of our garden was actually set up properly, we're not getting what we need out of these tools. And we've seen some of these examples happen in districts across the country.

Additionally, Teachers and educators who go out and sign up for some of these AI tools on their own and bring those into the educational system are also bringing some challenges along with those tools. Without proper coordination and without those proper safeguards, we [00:20:00] can unintentionally expose sensitive student data.

Or implement tools that conflict with established systems. So we might have multiple AI ecosystems going on inside of our school system at the same time, and that can cause conflict. So these might be well meaning, but unaligned efforts that can really disrupt the workflows and complicate our operations and compromise the organization's entire ecosystem.

We need to make sure that we have gone through the steps to really structure the garden, that we have really analyzed the use cases that we want to explore now, explore later, and explore never, and that we're bringing these tools in, in a good and safe way, where we have fully vetted them, that we are doing proper training, communication, and support around these tools as we bring them in.

And we really don't need to be in a hurry to bring in these AI tools. These initiatives really require careful cultivation. We want to start small, gain that experience and [00:21:00] build layer by layer.

Success comes from patience, tending to your ecosystem and ensuring that each phase builds upon the prior phase and supports the next.

Thank you for joining Safe and Innovative Schools. If today's episode gave you new ideas or inspiration, I would love for you to subscribe, share this podcast, and leave a review.

If you'd like to learn more about the PLANT-AI framework or share how you're implementing AI in your school or district, reach out. Let's keep the conversation going as we work together to build safer, more innovative schools.

Until next time, keep planning, learning, and innovating boldly. I'm Dr. Joe Phillips and I'll see you in the next episode.