5 Lessons From College CTE Programs Already Implementing AI
By Lauren Mason, PhD, Co-Principal Investigator of the Perkins READI AI Fellowship
Participants listen attentively during a recent Perkins READI AI Fellowship gathering.
Ask any career and technical education (CTE) instructor about artificial intelligence (AI), and you will likely hear a mix of perspectives. Whether excited about AI’s potential or exhausted from the hype, CTE instructors are seeing firsthand that AI is rapidly transforming their industries.
The urgency is real. Students are entering a workforce where AI is already being embedded into daily workflows, as educators are catching up on what that means for their programs. Instructors need to understand AI tools, see how industry is implementing them, and translate that into their classrooms. If students are expected to work alongside AI, preparing them now can't wait. But it’s not as simple as ensuring access to AI tools. Once instructors have access, they face a steep learning curve, a lack of time, and students who are sometimes resistant to using the technology.
How can CTE instructors cut through the noise and ensure their students are prepared for an AI-driven economy? Drawing from feedback within the Perkins READI AI Fellowship, we break down five lessons we’ve learned on what it takes to implement AI in college CTE programs—and how programs can successfully navigate the transition.
Lesson 1: Instructors want more than access to AI tools – they need professional development and curriculum support
The Perkins READI AI Fellowship helps CTE programs purchase and implement AI tools in classrooms. This financial support helps get AI tools into the hands of faculty and students, ultimately lessening the gap between classroom practice and industry demand. While this financial support is valuable, it is not the only type of support needed to help faculty succeed.
Feedback from instructors within our fellowship reveals that many do not yet feel confident in their ability to understand, let alone teach students about, AI. Many have only ever dipped their toe into AI tools like ChatGPT. Even those who do understand how AI is changing their industries lack the necessary time to develop strong lesson plans that incorporate these new tools. Ultimately, funding for AI tools is an important step, but it is only the first one.
To integrate these technologies in effective and sustainable ways, instructors need fundamental AI literacy and ethics training, alongside substantial support for the heavy lift of curriculum development.
Lesson 2: Not all students are on board with AI in the classroom – and framing matters
An unexpected challenge from this fellowship has been resistance among some CTE students to integrate AI into their workflows. Their concerns are multifold and valid: AI has the potential to displace jobs, and using it might expose them to accusations of cheating. To overcome this skepticism, how we frame these technologies in the classroom matters deeply.
Instructors can explicitly position AI as a tool that is actively transforming the industries students are preparing to enter, and when possible, provide tangible examples of how it is currently being used. Providing clear guardrails that distinguish appropriate, human-led AI use from academic dishonesty can give students further confidence to explore these tools safely.
Ultimately, instructors must emphasize to students that human judgment and subject matter expertise remain irreplaceable; AI is not a replacement for their skills, but a tool to maximize their potential.
Lesson 3: Industry partners are essential – and they are actively learning, too
AI is actively transforming every industry, a shift we explore in detail within our recent report, Applied Co-Intelligence: Preparing Career and Technical Education Learners for an AI-Driven Workforce. To ensure CTE classrooms keep pace with these innovations and properly prepare students for the workforce, deep partnerships with industry leaders are essential.
Aligning classroom instruction with real-world practice is already a foundational challenge for CTE; now, the rapid acceleration of AI makes keeping instruction rigorous and relevant even more difficult. Fortunately, industry leaders are actively learning too, and firsthand insights from our fellowship suggest that they do not have all the answers either.
This shared learning curve creates a unique opportunity: if we equip CTE students with fundamental AI literacy and a clear understanding of how to optimize workflows, they can enter the workforce not just as entry-level employees, but as innovative leaders ready to help drive AI implementation on the job.
Lesson 4: Flexible funding and timelines are necessary – AI adoption isn’t a one size fits all
The logistical reality of adopting AI in the classroom involves unpredictable technical and timeline demands; some tools turn out to be more error-prone than expected or require additional software integration to function properly. These technical hurdles, in turn, can cause unexpected delays in project timelines.
Additionally, instructors must first take the time to teach themselves how to navigate these tools prior to developing comprehensive lesson plans that incorporate them. To accommodate this learning curve, we recommend that programs incorporate a dedicated trial period into their implementation plans.
Financial needs also vary significantly by discipline. Some technical colleges benefit greatly from advanced, industry-specific AI tools like AI-assisted welding technology, which often come with a hefty price tag. Other programs can successfully utilize accessible platforms like Microsoft Copilot to teach students how to thoughtfully engage with AI while keeping the human at the center as the subject-matter expert. Flexibility is a requirement for success.
Lesson 5: Integrating AI tools into CTE classrooms requires trial and error – we must fail forward
Striving for a perfect, fixed protocol for AI implementation in CTE classrooms simply isn’t feasible. AI tools must be thoughtfully selected with industry alignment at the forefront, which means that as workforce expectations evolve, our tools must change too.
It is easy to feel discouraged when the initial rollout of these tools brings unexpected challenges. Technical errors, steep learning curves, and the need for additional resources can quickly become overwhelming. Designing lesson plans that truly engage students and deepen their understanding further adds a heavy burden on an instructor's limited time. However, embracing these roadblocks and allowing students to witness the troubleshooting process may actually be the best path forward. Trial and error is inherent to mastering any new technology, and building AI competency is exactly that—a complex skill with distinct layers and nuance.
When it comes to adopting AI in CTE, the initial instinct is simple: secure the funding, buy the software, and hand it to instructors. But as fellows in our program are actively discovering, true AI integration is a complex journey, not a one-time software deployment.
The experiences of our fellows prove that overcoming student skepticism and building instructor confidence requires patience, iteration, and a willingness to "fail forward." There is no fixed playbook for this transition. The programs that thrive will be the ones that adapt as the workforce evolves.
Want a deeper look at how AI is reshaping the workforce and how you can prepare your students? Download our full report, Applied Co-Intelligence: Preparing Career and Technical Education Learners for an AI-Driven Workforce.