Full AI autonomy promises speed, but it often costs trust. In this Domo livestream, Abby Stowell, Solution Engineer, and Mark Boothe, CMO, explore how Human-in-the-Loop AI blends AI efficiency with human oversight to catch errors, reduce bias, and build responsible AI systems people can rely on. Through real-world examples spanning multiple industries, they show why keeping humans at the center leads to smarter, more accurate outcomes. This is agentic AI, governed by people, not just processes.

If your team is tracking referrals on sticky notes and managing member relationships in spreadsheets, you do not need to buy another SaaS tool. Domo CMO Mark Boothe and Solutions Engineer Shana Brennan demo a live AI-native CRM built entirely in Domo that logs calls, drafts personalized emails, moves pipeline stages, and runs a weekly AI sweep to identify new revenue opportunities across your entire member portfolio, all without writing a single line of code. This is what your data foundation looks like when it goes to work.

Reading hundreds of contracts to find the ones that need a decision today is not a job for a human. Domo CMO Mark Boothe and Forward Deployed Engineer Paul McCusker demo a live agentic contract management solution that extracts key terms from PDF agreements, benchmarks portfolio performance against external sentiment data, surfaces at-risk and expiring contracts, and routes renewal approvals through a governed workflow, all with row-level security that ensures every user only sees what they are supposed to see.

Working the oldest invoice first sounds logical until you realize it is a $50 invoice and a $10,000 one has been sitting unpaid for 20 days. Domo CMO Mark Boothe and Solution Engineer Gordon Pont demo a live AI Cash Agent that prioritizes receivables by risk score and payment history, auto-drafts collection emails, and keeps a human in the loop for every discount approval, all built on a governed Snowflake data foundation. Garbage in, garbage out. Domo does not have a garbage can.

Chris and Joe unpack “tokenmaxxing” and share a better framework for thinking about AI usage, token spend, and workflow building. They break down strategies from model selection to context management that are helping actual Domo customers build efficient AI systems that prioritize outcomes over token spend.

AI is only as useful as the data behind it, and your data foundation is already in Domo. Watch Domo CMO Mark Boothe and Senior Solutions Engineer Mike Tong demo the simplest place to start with AI: a custom decision support card that uses DomoGPT, RAG, and your existing governed datasets to auto-summarize dashboards, recommend actions, and let your decision makers ask smarter questions. The dashboard is not dead. It just got a whole lot smarter.

Account executives spend hours digging through CRMs, emails, and call transcripts just to plan a single customer visit. Domo CMO Mark Boothe and Associate Solution Engineer James Miller demo a live AI territory planning app built in 20 hours using Cursor and Domo's MCP that maps accounts by territory, scores customer health, recommends who to visit and why, and auto-generates dinner invites and manager approval requests, all from a single governed data foundation.

Growing an internal data community is hard until you give people a reason to log in every day. Sony PlayStation's Oleksii built a World Cup prediction challenge app in Domo in two hours, complete with real-time match scores from Google Sheets, timezone-aware scheduling for global teams, a live leaderboard, and an AI agent that writes sports-style commentary on standings after every match. This is what a governed custom app platform looks like when it is actually fun to use.

You cannot prompt your way out of a bad data foundation, and this session proves it live. Domo CMO Mark Boothe and Senior Solutions Engineer Megha Kumar show exactly what happens when Claude, ChatGPT, and Domo's governed AI answer the same revenue question using the same data, and why only one of them can be trusted to drive a business decision. This is what grounded, governed, actionable AI looks like in practice.

A multi-billion dollar company spent four years unable to solve their tail problem. Mason Crane solved it in four days. Domo CMO Mark Boothe and Senior Solution Engineer Mason Crane demo a live agentic warehouse optimization app that surfaces AI-suggested pallet moves with human-in-the-loop rationale, auto-evacuates offline lanes in real time, and tracks every decision so institutional knowledge never walks out the door again. This is what agentic ops looks like on the warehouse floor.