Carlyn Chatfield is an IT Technical Communicator at Cornell with four decades of experience writing for internal and external higher education audiences. 

Storytelling is one of my gifts. I love breaking down complex ideas into stories that appeal to broad audiences. So when my team was encouraged to “try AI,” my first reaction wasn’t excitement. It was skepticism. 

I was already working at full speed. What exactly was AI supposed to fix? 

Rethink Your Approach 

The problem wasn’t writing. It was scale. I wanted to write more stories, but didn’t have the time. 

• How could I do more of what I really loved at work?  
• Was I willing to change my mind about AI so I had time to write more stories?

I was going to have to rethink my approach. 

A typical story—from outreach to publication—took 4–8 hours. The process was deeply manual: researching subjects, crafting custom interview questions, drafting from scratch, and working through multiple edits to highlight key ideas without losing flow.  

The process didn’t scale. Setting aside time for writing meant sacrificing other responsibilities. 

To learn more about AI tools for everyday work activities, I began attending workshops, meetings, and events hosted by Cornell’s AI Initiative. I signed up for two classes that required hands-on experimentation with conversational AI tools. 

Change One Thing at a Time 

I didn’t overhaul my workflow. I tested one task at a time, looking for places to reduce friction. 

Because much of my work involved unannounced projects, I stayed within Cornell’s secure AI environment to protect sensitive material. 

The first breakthrough came with research. My AI tools quickly generated solid background information and links I could use to verify those details, speeding up the interview prep. Other steps were less consistent. When something didn’t work, I moved on and tested another part of the process.  

That trial-and-error process led to a shift in how I think about AI. Having managed student workers, I started treating it like an intern: 

• Give clear, contextual prompts 
• Refine outputs iteratively 
• Always fact-check 

Like my best student workers, my AI “intern” helps with the heavy lifting even if I still shape the final result. It can take on repeatable tasks or shift into collaborative mode to brainstorm angles or troubleshoot a paragraph that isn’t working. 

It doesn’t replace my thinking—it both expands and accelerates it.  

A Word about the Em Dash 
As a creative and professional writer, I’ve been using the em dash for four decades. This habit can probably be traced to my favorite high school English teacher, my favorite college English teacher, and my early high school typing classes on first a manual and then an electric typewriter. It also suits my conversational storytelling style. If there is an em dash in my story, I put it there on purpose, manually. After all, what do you think trained AI models?

Content from writers like me. 

Create Strong Content in Half the Time 

On one particularly busy Thursday in May, I completed four stories while still managing my other responsibilities. That’s not typical, but it reflects a broader shift over the past 18 months. 

My AI tools now handle time-consuming tasks like summarizing transcripts, freeing me to focus on storytelling. When a piece stalls, I load my current work, clarify the goal, and ask for next steps. If deadlines are tight, I use it to generate title suggestions and teaser options. 

With the time to create a story cut roughly in half, I can meet my responsibilities and still find space to tell more stories.  

The result isn’t just more output, it’s more flexibility to focus on the work I love most: telling stories. 

Time Saving Prompts for Writers 

Here are a few ways I use AI to reduce friction in my process: 

Speeding Up Interview Preparation 

Task: Generate targeted interview questions  

Prompt: Here are questions from a previous interview. Suggest questions for the next student in this series about their summer projects [paste questions + notes] 

Outcome: A strong starting point I could quickly refine. 

Turning Transcripts into First Drafts 

Task: Transform a webinar transcript into a structured narrative 
Prompt sequence: 

• Summarize each section 
• Identify key themes 
• Suggest an introduction and structure 
• Refine using my notes 

Outcome: A solid first draft that organizes complex material quickly. The final polish is both manual (because it’s the aspect I enjoy most) and human-driven. 

No Fear of Cloning 

The most valuable parts of my work are still human: 

• Institutional knowledge 
• Cross-team relationships 
• Context across multiple initiatives 
• Connections across universities 
• The ability to link ideas across conversations 

Those insights come from being present—in meetings, at events, and in everyday interactions. Talking with someone in line for coffee at The Coal Yard can spark a story idea. That kind of connection isn’t something AI generates on its own. 

Return on Investment 

Learning how to incorporate AI in my storytelling has expanded my capacity. In fact, I built an AI “calendar cruncher” to analyze how I spend my time and where I’ve gained efficiency. It became a key data point in my next performance dialogue. 

Looking back, AI didn’t replace me or my process. AI changed where and how I spend my time: less building from scratch, more shaping the stories that matter. 

For me, that’s where the real work—and real value—has always been. 

Bonus: Ready to Try AI?  

If you’re new to AI assistant tools, start somewhere low-risk and build confidence.  

Start outside of work 

• Plan a trip based on a favorite story or theme 
• Explore a potential career change 
• Turn complex information into a checklist 

Then apply it to your workflow 

1. Summarize or structure content 
2. Turn notes or transcripts into drafts 
3. Simplify communication into key messages 
4. Generate interview questions or improve a process 
5. Build reusable templates for recurring work

Focus on tasks you repeat, or ones you tend to put off.