AT&T, in collaboration with MicroAI, NVIDIA, and Microsoft, is accelerating smart manufacturing with the introduction of Connected AI for Manufacturing. By connecting diverse industrial assets and analyzing near real-time data, this platform delivers AI powered insights to boost productivity, cut downtime, and is designed to strengthen security from the shop floor to the back office.
Underscored by GlobalData’s 2026 Global Industrial IoT Services Competitive Landscape Assessment recognizing AT&T as the industry leader in IoT, this platform provides highly secure, low latency communications, and edge processing — not only between machines, sensors, and systems, but also between humans and machines. NVIDIA AI, Metropolis Blueprint for video search and summarization (VSS), and accelerated computing are key enablers of the Connected AI experience, helping deliver the real-time AI performance required for industrial monitoring from edge to cloud. By powering fast video analytics and conversational AI, NVIDIA helps transform traditional streaming analytics telemetry into timely, actionable insights.
By integrating generative AI at the edge—built on Microsoft Azure Open AI—operators can communicate using natural language to query, instruct, and collaborate with different machinery. This allows data to move reliably and decisions to happen faster.
What this delivers for manufacturers
- Advanced, GenAI powered modeling and analytics that identify bottlenecks, pinpoint root causes, and provide recommended corrective actions.
- Predictive maintenance that transitions teams from scheduled service to dynamic, machine-centric intelligence — helping prevent failures and reduce unplanned downtime.
- Overall Equipment Effectiveness (OEE) optimization with edge AI that monitors effectiveness across machines and lines and provides actionable insights to break through common OEE barriers, such as fault detection and optimized maintenance planning.
- AI enabled cybersecurity at the edge to learn “baseline” asset behavior and quickly flag anomalies — accelerating detection and mitigation of potential intrusions.
- GenAI enabled knowledge management to retain, retrieve, and apply institutional knowhow where it matters most: in front of the machine.
Early results show measurable impact. In controlled pilot deployments under test operating conditions, customers have seen up to a 70% reduction in waste on injection molding lines, 2.5–4 hours of lead time for pre-failure fault detection, and a 35% improvement in fulfillment center efficiency, with results varying based on deployment environment, integration scope, and operational practices.
“Bringing Connected AI to manufacturing puts AT&T’s network and AI expertise to work for the factory floor,” said Cameron Coursey, VP of Connected Solutions at AT&T. “By connecting machines with communications designed for security and low latency performance and layering in generative AI at the edge, we are helping to turn raw telemetry into timely insights so that machine operators can act sooner and produce better.”
Connected AI for Manufacturing is available today, with flexible engagement models — from fast POCs to multi-plant deployments. To get started, visit www.business.att.com/industries/manufacturing.
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