What We're Actually Using AI For This Week (Vol. 1)

Learn what the VAILL team actually used AI for this week (and how to make it work for you too).

“How do you use it?” That’s now the #1 question I get from colleagues, friends, family, and other professionals. We’re past the stage of “what is it?”

The people asking aren’t looking for AI to completely overhaul their lives or replace their expertise. They want to know how these tools can make Tuesday afternoons less frustrating, how to handle the small annoyances that pile up throughout the week, and how to get practical value without becoming an “AI person.”

The disconnect is real: while the AI conversation is dominated by predictions about wholesale industry transformation, most people just want to know how to make their Wednesday morning less annoying. There’s a gap between the revolutionary promises and the practical reality of what these tools actually do well. Worse, this mismatch can be paralyzing: when every example feels impossibly ambitious, people either don’t try at all or get so frustrated by the gap between expectation and reality that they write off AI entirely.

Inspired by these conversations, I thought I’d share what the VAILL team is actually using AI for this week. We’re hoping to turn this into a regular content feature, with ideas from smart folks (you!) who are also doing cool work and making their day-to-day easier. We’ve got a Google form set up for you to share, and we’d love to hear from you.

Keep in mind, these aren’t flashy use cases or carefully curated demos. This is the real stuff: the mundane problems, the “I need help with this right now” moments, and the small wins that actually make our work (and life) better.

Strategic Planning That Doesn’t Make You Want to Scream – Emily Pavuluri

My library colleagues and I have been working on our department’s strategic plan. Don’t get me wrong, this is an important task, but does anyone actually enjoy doing it? (No.)

This year, some of us have been using Copilot to tackle the organizational nightmare that strategic planning usually becomes. We’re using it to identify what goals are actually in our plan, figure out how existing work fits into different sections, and develop measurable objectives to track our progress. Vanderbilt offers Copilot, and it integrates with our Sharepoint, so we can easily call up shared files, rather than trying to find it, download it, and reupload it to a tool.

In previous years, this process would consume hours of our individual time and at least two meetings where we’d discuss whether Initiative X belonged under Goal 2 or Goal 3, and whether “improve user satisfaction” was specific enough to actually measure. This year? An hour max, and that’s being generous. I spent (maybe) 15 minutes working with Copilot to create metrics for our goals and identify realistic ways to achieve them.

Copilot didn’t write our strategic plan for us, but it helped us see the structure we already had and organize our thinking in ways that actually made sense.

How do you make this work for you? AI excels at the organizational and analytical tasks that bog down important work. It’s not doing the strategic thinking for you, but it can help you align what you already know and do with the output and expectations stakeholders expect of you.

Travel Planning That Adds Value – Cat Moon

I planned a summer trip through Switzerland, the Netherlands, and France for a series of AI workshops I hosted over the summer, and I bounce between Claude, ChatGPT, and Gemini to figure out the best combination of scenic and efficient travel options.

Here’s my approach: I start broad, giving the bots my travel dates and any must-haves, but resist the urge to over-specify. Almost universally, they point me toward delightful options I wouldn’t have found through my usual travel search methods. The suggestions aren’t perfect (ChatGPT kept recommending month-long apartment rentals in Paris when I was only there for three days), but they’re excellent starting points.

I always do my own research first: checking CN Traveler for hotels, consulting a few trusted travel blogs, and asking friends for recommendations. But the AI suggestions consistently push me in directions I wouldn’t have explored otherwise. After 2+ years of using AI for travel planning, I’m continually amazed at how much better the recommendations have gotten.

How do you make this work for you? Use AI to expand your initial thinking, not replace your research. The magic happens when AI surfaces options you didn’t know to look for.

Rapid Prototyping Without the Design Bottleneck – Mark Williams

I’m currently leading an effort to build out our AI Legislation Tracker. In the past, getting a project like this off the ground involved a slow, painstaking process of creating mockups and writing lengthy descriptions to translate my vision for our team of data scientists and student developers. It’s a process filled with meetings where you spend more time saying “imagine if...” than actually building.

This week, I took a different approach. Using a generative AI assistant, I built a functional, interactive prototype of the tracker’s key pages. I fed it my project notes, examples of other trackers I liked, and raw content outlines. In response, it generated the complete HTML, CSS, and even the JavaScript needed for an interactive webpage.

Instead of just telling my team what I wanted, I could show them. The conversation immediately shifted from “what are we building?” to “how do we build this?”

It’s important to note that the code the AI generated isn’t what we’ll use for the final, deployed version. There’s still a wide gulf between a prototype and a secure, scalable application. However, the ability to leapfrog the initial design and communication hurdles has already saved us weeks of effort and aligned the entire team around a concrete vision.

How do you make this work for you? AI is a powerful force for rapid prototyping. It empowers anyone, regardless of their coding ability, to turn an abstract idea into a tangible, interactive example that bridges the crucial communication gap between vision and execution.

Small Wins: AI for Admin Tasks – Kyle Turner

As I gear up for class, there are a lot of small administrative tasks that eat away at my day. While we often talk about the “newest” or “coolest” use cases, I took time to reflect on how I was actually using AI on a daily basis. It’s the small things that add up to real “help” for me. Recently, I was given a large Excel file, and I needed to transfer the data into a different format. I knew it could be done, but I had a hard time creating a Google search to answer my inarticulate question. I turned to ChatGPT, which understood my ask, and then gave me the steps to transform the file. Instead of having the system do something for me, I used the tech as a learning tool to walk me through and it answered each question along the way.

I find myself doing this often for many admin tasks. “How do I accomplish XYZ in Outlook,” or even sending a screenshot of various “error messages” has helped me learn a new skill that would have taken a lot longer via traditional review of instructions or FAQs. Never underestimate the ability of the AI to explain hard and even mundane processes at a granular level, and as a bonus, it never gets mad if I need something explained more than once.

How do you make this work for you? Think of AI as your patient teacher for all those small technical tasks that eat up your day. Instead of struggling through unclear help documentation or generic Google results, describe your specific situation, even if you can’t articulate it perfectly. AI excels at understanding context and walking you through step-by-step solutions, and you can ask follow-up questions without feeling like you’re bothering anyone.

BONUS: Note-Taking That Actually Gets Used – Emily Pavuluri

My husband, who is also a lawyer, started a new job recently and has been attending tons of information sessions and informal conversations about different aspects of his company’s work. Sometimes he’s hearing about areas of law he knows well; other times, he’s learning completely new concepts and scribbling down acronyms and key points. He’s in webinars and meetings with constant updates about new laws, big policy changes, and the current presidential administration’s actions. It is a lot to take in, and he’s been filling up notebooks with things he wants to remember.

His notes were becoming a mess of unstructured fragments that just weren’t helping him. There wasn’t an easy way for him to remember where he wrote Enter Copilot! Copilot is provided in his legal department, and he and many of his coworkers already use it to revise emails. He took photos of all his notes, with any client information scrubbed completely, and had Copilot organize them into a coherent outline structure.¹

Now, he has something he can actually refer back to instead of pages of random bullet points that made sense in the moment but are useless a week later. He’s also able to add to this outline structure with any new developments and make connections to previous developments much more efficiently.

How do you make this work for you? AI can turn your information chaos into usable knowledge systems. The key is feeding it enough context about what you’re trying to accomplish. Guiding the AI with some ‘hints’ about where content should go as you build out your materials will make the output better.

The Gap Between Hype and Help

Again, these examples don’t involve groundbreaking AI capabilities or fancy enterprise solutions. They’re all about using readily available tools to handle the small frictions that accumulate throughout our days and work. Yet if you follow the mainstream conversation about AI in law (or everywhere, really), you’d think the only applications worth discussing are the ones that promise to revolutionize entire practice areas overnight. These practical applications rarely make headlines or drive conference keynotes.

This matters more than you might think. A recent Bloomberg Law survey revealed a striking gap between what lawyers expected AI to accomplish in 2024 versus what actually happened in 2025. While 75% of lawyers predicted AI would significantly increase automated processes, only 37% observed meaningful changes. The biggest expectation gaps? Dramatic workflow transformations.

Here’s the thing, though: the lawyers focusing on massive systemic change might be missing the point.

The pattern in our examples isn’t “AI does everything for us.” Instead, how AI works in each of these examples is very simple. It takes the burden off our shoulders and makes something we have to do easier, without asking us to do more work to get an answer.

The Bloomberg survey showed that most lawyers reported ‘no change’ across categories—not because AI doesn’t work, but because they’re looking for revolutionary impact, not evolutionary improvement. Meanwhile, those of us using AI for strategic planning, travel research, prototyping, and note organization are getting real value every single day. We’re not winning awards for radical change, but we are less frustrated by the things that bog us down. And more often than not, we’re producing work that aligns more with what we want to do, without feeling frustrated or restrained by lack of technical know how.

This is exactly what the people asking “how do you use it?” want to hear. They don’t need AI to transform their entire profession overnight. They want to know how it can make their work less frustrating, their planning more efficient, and their daily tasks more manageable.

The real AI revolution isn’t necessarily happening in the headlines or the billable hour metrics—it’s happening in the tiny moments when these tools help us move from “this is annoying” to “this is manageable.”

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What are you actually using AI for this week? Not the theoretical applications or the tools you think you should be using. But the real ones. The boring ones. The ones that just work. If you’d like to share, we’ve got a Google form open and would love to hear your ideas.

1. Most of these notes don’t even include any client information anyway, but it is important to be overly cautious. Regardless, you should be aware of how Model Rule 1.6 (and others) may apply in the GenAI world. Learn more, ABA issues first ethics guidance on a lawyer’s use of AI tools.