AI Use Cases for Predictive Maintenance

Turn Predictive Insights Into Coordinated Action With AI Agents

Predictive maintenance failures today are rarely caused by poor models. They happen when predictions remain disconnected from maintenance planning, work order execution, and parts availability. Without coordination across these systems, even accurate predictions fail to prevent downtime. 

This guide shows how manufacturing teams operationalize predictive maintenance using AI agents, connecting model outputs to prioritization, scheduling, and execution, while keeping humans in control. 

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Download the AI Manufacturing Guide

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Turn Predictive Maintenance Into
Competitive Advantage

Why Predictive Maintenance Is More Costly Than You Realize

See how unplanned downtime, safety incidents, and aging assets are driving double-digit cost increases — and why time-based maintenance can't keep up.

Explore AI Agents for Maintenance

Explore agent use cases like the Maintenance Scheduling Assistant and Machine-as-a-Service Uptime Agent that coordinate plans, parts, and uptime targets in real time.

A Practical Guide for Modern Predictive Maintenance

Follow a proven path from anomaly detection to failure prediction and remaining useful life modeling, designed for real-world operations.

Building a Trusted Maintenance Data Foundation

Learn how IoT sensor data, maintenance history, MES inputs, and external context must be connected and governed to produce reliable model outputs.

Turning Predictions Into Maintenance Work

Understand why even accurate predictions fail without work order integration, parts availability, and technician trust. 

Operationalize Predictive Maintenance With The Universal AI Platform™

Dataiku provides the enterprise foundation required to operationalize predictive maintenance at scale. By unifying governed data, machine learning, GenAI, and AI agents in one platform, Dataiku enables maintenance and operations teams to move from isolated predictions to coordinated execution with the traceability, governance, and operational control required in asset-intensive environments.

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