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/

And find EdTech Co...

• (00:00:00) - EdTech Connect: The Future of AI in Higher Ed
• (00:01:37) - The Most Fun Tool of All Time
• (00:08:37) - How AI Is Saving Time
• (00:09:48) - Alex Jones on His AI Wins
• (00:12:01) - Advancement & Campaigns: The Future of AI
• (00:16:00) - How AI is Affecting the Storytelling of Higher Ed
• (00:18:04) - In an AI World, Authentic Voice
• (00:21:04) - How Law and Design intersect in higher ed
• (00:27:21) - Teachers: We Have to Empower Them
• (00:27:41) - So AI is Having Its Moment
• (00:29:33) - What's an AI Superpower for Higher Ed?

Jeff Dillon sits down with Dr. Christy Heid, a Nursing Simulation Specialist at UbiSim. They tackle a critical issue revealed by UbiSim’s recent report: 65% of hospital leaders feel new nursing graduates aren't fully prepared for day-one patient care.

Christy explains how this "readiness gap" is being closed through immersive VR simulation and AI-powered tools. She delves into how UbiSim’s nurse-built platform fosters essential clinical judgment, provides a safe space for deliberate practice, and helps solve systemic challenges like clinical site shortages and faculty burnout. From stunning stats on AI-assisted charting adoption to real-world success stories of improved nurse retention, this conversation is a deep dive into how technology is not just enhancing, but fundamentally reshaping, nursing education to create a more confident, competent, and future-ready healthcare workforce.

Key Takeaways

1. There is a Significant "Readiness Gap": 65% of hospital leaders believe new nursing graduates are not fully prepared for day-one patient care, highlighting a critical disconnect between academic training and the realities of modern healthcare.
2. Clinical Judgment is the #1 Priority: The most pressing skill gap identified by employers is clinical judgment—the ability to make sound decisions in complex, changing situations. This is a foundational skill that takes time and repeated practice to develop.
3. VR Simulation is a Safe, Scalable Solution: Immersive VR provides a risk-free environment for students to make mistakes, learn from them, and engage in "deliberate practice." It is scalable, standardizes experiences for all learners, and can help address limitations like scarce clinical sites and faculty shortages.
4. AI is Already Transforming Healthcare Workflows: The adoption of AI-assisted charting in hospitals has increased by 165% in the last three years. Nurses now need to be trained to work alongside AI tools, which can free up to half of their time from administrative tasks for direct patient care.
5. The Future is a Blended, Personalized Approach: The goal isn't to replace all live clinical experience with simulation, but to use it as a strategic, blended component. The future of nursing education lies in personalized, goal-directed learning that leverages both VR immersion and AI-driven feedback.
6. Technology Strengthens Academic-Practice Partnerships: A major trend is hospitals and nursing schools creating co-branded micro-credential programs. Immersive VR acts as a bridge between these two worlds, ensuring graduates are equipped with the specific competencies employers need.
7. The Human Element Remains Irreplaceable: While AI and VR are powerful tools, they are designed to enhance, not replace, human skills. The focus is on using technology to recapture time for the human connection, critical thinking, and reflective dialogue that are at the heart of nursing.

Find Christy Heid:

LinkedIn

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

UbiSim

https://www.ubisimvr.com/

And find EdTech Connect here:

Web: https://edtechconnect.com/

• (00:00:00) - How Technology is Disrupting Nursing Education
• (00:02:16) - UB SIM: The Nursing Education Platform
• (00:04:28) - Practice Ready: The Need for New Graduates
• (00:07:26) - How is AI impacting the nursing profession?
• (00:11:58) - Immersive VR Simulation
• (00:15:04) - UBSIM: Case Studies
• (00:16:44) - The Right Blend Between Simulation and Live Clinical Experience
• (00:17:53) - Immersive VR Training
• (00:19:47) - How is simulation influencing healthcare system training programs?
• (00:22:23) - The future of nursing education: VR and AI
• (00:25:30) - How VR Simulation and EdTech Connect are shaping nursing education

In this episode of EdTech Connect, host Jeff Dillon sits down with digital marketing pioneer Jim Sterne, a professional explainer who has been at the forefront of every major tech shift since the 1980s. Jim reframes Generative AI not as just another tool, but as a fundamental metamorphosis—a shift from computational power to intellectual prowess.

They explore how this changes the very nature of our work and identity, why "taste" and "context" are the irreplaceable human advantages, and how organizations can build trust with this new technology. Jim offers pragmatic advice on where to start, the critical importance of sharing failures, and why the goal isn't to replace people, but to empower them to become trusted advisors. Tune in for a masterclass in navigating the AI revolution with clarity, curiosity, and a healthy dose of critical thinking.

Key Takeaways

1. AI is a Metamorphosis, Not Just a Tool: Generative AI represents a sea change from automating tasks to generating ideas. It's a different kind of computing that requires a fundamental shift in how we think about work, creativity, and problem-solving.
2. Humans Provide the Critical "Taste" and "Context": The two most valuable things humans bring to the table in the age of AI are context (understanding the bigger picture) and taste (the opinion and judgment to evaluate AI's output). Our role is evolving from task-doers to trusted advisors.
3. Trust, But Verify: You can trust AI to be creative and generate ideas, but you should never trust it for facts. Always validate and verify its outputs before publication or action, treating it like a witness that may tell you what you want to hear rather than the absolute truth.
4. Start with an "AI Council" and Active Play: To adopt AI effectively, organizations should form a cross-functional council to establish policy and risk tolerance. Simultaneously, individuals should dedicate time to "active learning"—playing with the tools daily and sharing insights with colleagues.
5. Celebrate and Share Failures: The path to AI mastery is paved with mistakes. Creating a culture that celebrates and shares "stupid mistakes" is one of the fastest ways for an entire organization to learn and avoid common pitfalls.
6. AI Enhances Jobs, It Doesn't Just Replace Them: The misconception is that AI will allow you to fire half your team. The reality is that it allows your current team to do the work of 10, freeing them from toil to focus on higher-level strategy, creativity, and human connection.
7. Ask for Opinions, Not Just Facts: When using AI for analytics, move beyond simple queries for data. Ask it for its opinion—"Where do we seem to be making the same problem over and over again?"—to uncover insights that prompt critical thinking and new ideas.
8. The Promise of Hyper-Personalization is Finally Here: AI is the key to delivering on the long-held "one-to-one" marketing promise. It can parse complex customer data to not only send the right message at the right time but also to use the right tone, creating truly personalized customer relationships at scale.

Find Jim Sterne:

LinkedIn

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

Target Marketing of Santa Barbara

https://targeting.com

And find EdTech Connect here:

Web: https://edtechconnect.com/

• (00:00:00) - The challenge of digital transformation
• (00:00:46) - Jim Stern on Artificial Intelligence & Customer Relationships
• (00:01:47) - What's Surprising About AI in Marketing?
• (00:05:03) - The Role of the Fractional Evangelist
• (00:06:37) - How to Train Your Team for Generative AI
• (00:10:47) - The Future of Websites: Analytics
• (00:14:03) - How Much Do We Trust AI?
• (00:18:56) - What's the Biggest Concerns About Generative AI?
• (00:22:29) - What Excites and Worrys About AI Marketing
• (00:24:03) - The Future of Analytics in Content and Campaigns
• (00:25:04) - What's One Mind Shift for AI Teams?
• (00:26:08) - Jeff Greene: The New Science of Customer Relationships
• (00:28:24) - EdTech Connect