
Industrial AI Pilot: Why 68% of Manufacturers Can’t Scale Past the POC
Why 68% of industrial AI pilots fail to scale: non-replicable data pipelines, missing ROI baselines, and unclear ownership kill production deployment despite technical success.
Every industrial AI use case requires a custom data pipeline. Learn why legacy OT integration creates a hidden tax that compounds at scale and how to break the cycle.

Why 68% of industrial AI pilots fail to scale: non-replicable data pipelines, missing ROI baselines, and unclear ownership kill production deployment despite technical success.

Explore how human biases shape AI system architecture and why objectivity, intent design, and cultural transformation are essential for safe, effective agentic AI in manufacturing.

How to transform into an agentic AI company: encoding expertise, balancing innovation with reliability, and empowering teams through AI skills in the OT/IT convergence.

AI doesn’t replace experts; it codifies their knowledge into tools that empower everyone. Learn how AI enables a recursive self-improvement loop, turning domain expertise into an expertise flywheel.

In this guide, you'll see why industrial Agentic AI manufacturing strategies stall and what you can do to avoid those problems.

Learn how MQTT and HiveMQ Cloud powered a real-time interactive fursuit—proving MQTT's value for wearable robotics and creative IoT projects.

Learn how Agentic AI transforms manufacturing with autonomous systems, smarter supply chains, and scalable innovation.

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Learn how to unlock AI value in manufacturing OT with AI-ready data, Unified Namespace architecture, secure governance, and metrics to scale from pilots to autonomy.

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Final part of Agentic AI blueprint: establish multi-agent coordination through shared objectives, unified context, and event-driven protocols for industrial operations.

Part 4 of Agentic AI blueprint: systematic governance across design, engineering, and operations ensures safe autonomous intelligence in industrial environments.

Part 3 of Agentic AI blueprint: systematic framework for identifying use cases across production, quality, and efficiency with three maturity stages.

Part 2 of Agentic AI blueprint: build semantic graphs with domain ontologies to transform streaming data into contextual intelligence for industrial operations.

Part 1 of Agentic AI blueprint: establish real-time data flow through digitization, MQTT event-driven architecture, and Unified Namespace for industrial intelligence.

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Enterprise AI fails without data context. Edge-level metadata enrichment, unified namespaces, and MQTT turn guessing into deciding. Context is infrastructure.

Coordinate physical systems in distributed edge environments with HiveMQ and MQTT microservices. Leverage Pub/Sub, Request-Response, and UNS for scale & control.

Agentic AI needs trusted data pipelines, not just better models. Governed data contracts enable industrial agents to sense, reason, and act safely.

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Centrally manage HiveMQ Edge with the Barbara platform. Securely deploy, update, and configure your industrial MQTT gateway for seamless IIoT data flow.

Orange & HiveMQ streamlined automated edge rollouts, cutting deployment costs by 70%. See how a Unified Namespace and GitOps accelerate industrial digital transformation.

Leverage Distributed Data Intelligence to scale Industrial AI. Fix data inconsistencies with a Unified Namespace and robust governance.

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