AI Workflows Our Data Team Built—And Yours Can, Too

You already know AI matters. You’ve heard it from analysts, seen it in headlines, and maybe even tested a model or two. But turning that curiosity into real business impact? That’s where things get tricky. 

This post is here to make it simple. 

At Domo, we’ve put AI to work across our own business. And in doing so, we’ve uncovered several practical use cases to help any data team—not just ours—save time, reduce noise, and make smarter decisions faster. 

You don’t need a team of PhDs or a greenfield tech stack to get started. These are everyday wins that your current team could be running in a matter of weeks—with real business outcomes to show for it. 

Let’s jump in. (If you’d like to dig into the workflow diagrams for each use case, check out our Domopalooza session, 5 Generative AI Use Cases That Aren’t Chatbots.) 

1. Cut support response time without losing the human touch 

Goal: Automate replies using your internal knowledge base 
Category: Customer support

The problem: 
Support tickets roll in with questions your team has answered before. The answers exist—buried in the Community Forums, internal docs, or Knowledge Base articles—but someone still has to go hunt them down, copy the right snippet, and send it back. 

That takes time. And when volume spikes, customers wait. Slower support means slower adoption and lower satisfaction. 

The fix: 
We built a support assistant using Domo.AI that monitors incoming tickets in Salesforce, pulls relevant answers from indexed documents, and generates a suggested reply. It shows the source material alongside the draft response, so our team members can review, tweak, and send it—fast. 

The result: 
Less time spent searching. More consistency in responses. And the right balance of automation and human review, with future potential to scale even further. 

2. Get clearer insight from unstructured feedback 

Goal: Classify, summarize, and act on sentiment in real time 
Category: Voice of customer / Feedback analysis

The problem: 
Unstructured data—reviews, survey comments, emails—can tell you everything your dashboards can’t. But analyzing it manually takes too long. Traditional NLP methods were rigid and expensive, so most teams do this too late or not at all. Also, because the data isn’t standardized, it’s hard to take tactical action. 

The fix: 
We brought review data into Domo (in this case, from Google My Business) and used AI to classify sentiment, identify key themes (like price, service, or wait times), and summarize the takeaway. Each step was guided by clear prompts and tested against a human-coded sample set. 

The result: 
Now we can track negative feedback trends as they emerge—not months after the fact. Teams can zero in on what’s not working and fix any issues before they grow. 

3. Prospect faster without cutting corners 

Goal: Personalize outreach with AI-curated research and use cases  
Category: Sales prospecting

The problem: 
Outbound sales starts with a scramble: pulling public and internal data, scanning earnings reports, researching the org chart, and digging up relevant use cases. Done well, it’s personalized. Done at scale, it’s exhausting. 

The fix: 
We built a prospecting assistant that takes a company name and a prompt—like “What could I talk about with this persona?”—and pulls in data from investor reports, press coverage, internal use case catalogs, and call transcripts. It even suggests metrics, dashboards, and talk tracks aligned to the persona’s role. 

The result: 
Outreach that’s smarter, faster, and deeply relevant. What used to take 90 minutes now takes one. And reps can finally focus on selling—not on stitching together research from ten tabs. 

These aren’t moonshots. They’re everyday wins. 

Each of these use cases is live inside Domo. But they’re not just Domo stories—they’re your next quick win, your next experiment, your next way to make AI work harder for your team. 

Whether you’re building pipelines, modeling insights, or managing infrastructure, there’s a smarter, faster way forward—and you don’t need to rebuild your world to get there.  

Want to try these use cases for yourself? 

Join us for AI Academy, a free webinar series led by Domo’s Advanced Customer Enablement team. Whether you’re a data analyst, engineer, scientist, or architect, this series will show you how to build real, working AI agents inside your own Domo instance. 

No dev background required. Just bring your data—and we’ll walk you through everything else. 

Each session focuses on a different solution, with step-by-step guidance to help you get it up and running in your environment. 

Explore the AI Academy series (these are labeled AI Academy; toggled to “Past Recordings”) and start turning ideas into working solutions.