Manufacturing has the lowest AI adoption rate of any major sector. McKinsey's State of AI report puts the picture into sharp focus: 88% of organizations now use AI in at least one business function, but manufacturing sits towards the bottom of the table when it comes to scaling agentic AI inside the enterprise. The reasons are well known to anyone who has spent time on a factory floor. Operational technology lives behind a wall from the IT estate. Sensor data sits in historians, technical specifications sit in PDFs, and none of it is joined up. A wrong recommendation on a production line has physical consequences, not just a bad email. At Domo, we are building agentic solutions that help manufacturers find value with AI. For example, our Maintenance Agent reads Snowflake for sensor telemetry, predictive maintenance model outputs, asset history, and writes back where it matters. Every predicted failure gets analyzed for severity, asset criticality, and intervention window. Every work order is grounded in the data, with the rationale attached. Every recommendation pulls in the right technical documentation, the right parts list, the right safety procedures, and is then ready for one-click approval, with human oversight built in at every critical step. Featured Session: Inside the Maintenance Agent Join Domo CMO, Mark Boothe, and Jamie Morrison, Field CTO for EMEA, showcasing a solution purpose-built for the unique realities of predictive maintenance at enterprise scale. Jamie will walk through how the agent: surfaces predicted failures from a model running natively in Snowflake; retrieves the relevant technical manuals and equipment specifications from unstructured documentation in Domo; drafts the work order rationale and parts list your engineers would otherwise build by hand; and dispatches a structured work order to the maintenance technician's mobile device the moment a plant manager signs off. Engineered end to end on the Domo App Platform with data at rest in Snowflake. What You Will See: · It's Agentic: The agent doesn't just visualize, it analyses predicted failures, generates work order recommendations, retrieves the right technical documentation, and explains its reasoning. All routed through a workflow to a human in the loop. · It's Connected: One application, every layer. A modern front end, Domo Workflows orchestrating Code Engine functions, AppDB for persistence, Domo AI calling foundation models, unstructured documentation grounded through Domo. And Snowflake as the governed source of truth for sensor data and model outputs, natively integrated, reading where it should and writing where it matters. · It's Governed: Human-in-the-loop on every maintenance decision. No autonomous work orders, no autonomous spend, no new vendor, no surprises. Jamie is going to show you how to build a modern maintenance engine. Join us and see what happens when every sensor signal, every failure prediction, and every work order runs on agentic AI. Learn more about Domo: https://bit.ly/4ehbwDE

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