About the Episode
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About The Episode:
Carrie Phillips sits down with Jeff Ebbing for a practical, no-nonsense conversation about AI from a community college perspective. Jeff shares what it really looks like to think about AI when “doing more with less” is the daily reality, including what’s worth trying, what’s not, and how to bring skeptical colleagues along without overselling the technology. They talk about where community colleges are getting AI right and how to take smart, low-risk steps forward.
Key Takeaways
- AI adoption in community colleges is rooted in practicality, not trend-chasing. These institutions focus on tools that deliver tangible results, fast.
- Limited resources drive intentional AI usage. With small teams, there’s no room for experimentation that doesn’t serve a clear purpose.
- Trust and security concerns dominate early AI conversations—especially when power users aren’t yet part of decision-making spaces.
- Use cases like enrollment planning and strategic communication highlight AI's potential to drastically improve workflows and turnaround time.
- Start small by identifying internal champions. Empowering a few early adopters to test and refine use cases is a low-risk way to build internal buy-in.
- The Eisenhower Matrix is a valuable framework for deciding when—and when not—to use AI in your workflows.
- Cultural buy-in requires showing impact, not selling hype. Let the problem be the teacher by demonstrating how AI can help solve real challenges.
Episode Summary: FAQs Answered in This Episode
What makes AI adoption different in community colleges compared to four-year institutions?
Community colleges often operate with fewer resources and smaller teams, which means there’s little room for trial and error. Unlike many four-year institutions that may use AI for exploratory or experimental purposes, community colleges focus on purpose-driven adoption. AI use is centered on achieving measurable, practical outcomes—whether it’s reducing time spent on strategic planning or supporting overburdened staff with content generation.
How do community college marketers evaluate whether AI is worth implementing?
According to Jeff, it all comes down to impact and effort—a principle informed by the Eisenhower Matrix. AI tools must either increase the quality of output or reduce the time it takes to produce it. If a tool doesn’t clearly achieve one of those two goals, it’s not worth the limited bandwidth. Teams look for AI tools that solve immediate problems and seamlessly integrate into existing workflows.
What are the biggest concerns about AI on community college campuses?
Without widespread AI champions in leadership roles, early conversations tend to focus on security risks, compliance, and academic integrity—not innovation. In many cases, practitioners in marketing, admissions, or financial aid use AI differently than faculty, but their voices aren’t always centered. Jeff notes that real cultural change happens when power users in these functional areas start showing how AI drives efficiency and impact.
Can AI really save time in a meaningful way?
Absolutely. Jeff shares a compelling example of using AI to co-author an Aspen Prize application, reducing what could have been a multi-week writing and revision process into just a few days. By letting AI act as a thought partner—structuring content, synthesizing input from various contributors, and maintaining a cohesive tone—the team was able to significantly speed up the process without sacrificing quality.
How should community colleges approach AI without overwhelming their teams?
Jeff recommends a champion-first approach. Identify individuals who are curious, tech-savvy, and open to experimenting. Give them space to test AI in their daily work and document the outcomes. If they can show that their output is either better or more efficient, that creates a ripple effect—others take notice, leadership gains confidence, and AI adoption grows from within, organically and strategically.
How do you manage internal resistance or skepticism about AI?
Rather than pushing hesitant colleagues, Jeff suggests "letting the problem be the teacher." When real-world challenges emerge—like writing high-stakes applications or responding to short-term strategic needs—those are opportunities to demonstrate AI’s value. Once skeptical colleagues see the productivity and quality gains firsthand, resistance tends to diminish naturally.
Enrollify is produced by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com.
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