This week on EdTech Connect, host Jeff Dillon sits down with Erin Callihan, AVP of Strategic Marketing at NYU and a powerhouse who blends law, design, and deep tech strategy. They dive into the ever-expanding AI toolbox that's reshaping how higher ed professionals work.

Erin shares her latest favorite tools—from Google Gemini's surprising slide design capabilities and Napkin AI for instant data viz to Notebook LM's powerful research features. She gets practical about how AI is saving her team significant time on everything from analyzing survey data to identifying fonts from a screenshot. The conversation tackles the big questions: How do we maintain an authentic, human voice while scaling content with AI? What's the right pace for developing university-wide AI policy? And how can professionals in "high-risk" areas like advancement and fundraising get started safely? Tune in for a masterclass in practical AI adoption from one of higher ed's most creative and strategic minds.

Key Takeaways

1. AI is Built into the Tools You Already Use: The most powerful and accessible AI is often integrated into existing platforms. Leverage the AI functions in Google Sheets, Gemini, and Notebook LM for data analysis, research, and content creation before seeking out standalone apps.
2. Start with Low-Risk, High-Impact Tasks: To build comfort and demonstrate value, begin with AI on "low-risk" tasks. Examples include analyzing anonymized survey data, brainstorming campaign ideas, troubleshooting tech issues, or automating mundane formatting tasks in spreadsheets.
3. The "Human 20%" is Non-Negotiable: For authentic communication—especially in areas like donor relations—AI should handle the middle 80% of a task. Humans must provide the crucial front-end context (brand voice, mission, audience personas) and the final 20% review to ensure quality, accuracy, and heart.
4. AI Policy is About Guidance, Not Just Prohibition: Effective university AI strategy involves moving beyond simple "don't share data" policies. It requires providing practical guidance, showcasing good and bad use cases, and, where possible, standardizing on a few trusted, vetted tools to simplify training and security.
5. Clean Your Data to Mitigate Risk: For teams in sensitive areas (e.g., advancement), a critical first step is ensuring data is clean and exportable. This allows you to replace private information (like donor names) with unique identifiers before using LLMs for analysis, protecting privacy while unlocking insights.
6. Curiosity is the Ultimate Superpower: Erin’s unique background in law (distilling authoritative sources) and design (asking exhaustive questions) makes her a natural at prompt engineering. The key to using AI effectively is innate curiosity and the ability to ask comprehensive, context-rich questions.
7. AI is Not a Fad—Ignoring It is the Risk: The biggest misconception is that AI is a passing trend. It is already integrated into everyday technology and is reshaping the economy and workforce. The real risk for higher ed professionals is not engaging with it to understand its capabilities and limitations.
8. The Real Need is a "Pause Button": With the breakneck pace of new tool releases, the greatest challenge—and desired superpower—is time. Professionals need dedicated space to explore, experiment, and thoughtfully integrate new technologies into their workflows without being overwhelmed.

Find Erin Callihan:

LinkedIn

https://www.linkedin.com/in/erincallihan/

NYU

https://www.nyu.edu/

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