GE Appliances rolls out 800 AI agents across operations

GE Appliances has deployed more than 800 AI agents across its manufacturing, logistics and supply chain operations using Google Cloud's Gemini Enterprise, marking a broad rollout of AI across the appliance maker's operating network.

The system is now embedded in factory and operational workflows, where the tools analyse production performance, review logistics issues and manage supplier communications. The aim is to shift teams from manual, reactive processes to faster decisions based on live operating data.

At the centre of the effort is the company's Brilliant Factory manufacturing data platform, which tracks production performance, part genealogy and workforce activity across production lines, shifts and plants. By integrating Gemini Enterprise into the platform, GE Appliances allows staff to query production data directly and review operational issues without relying on specialist data science support.

AI agents can now produce shift summaries in minutes rather than hours, helping teams identify root causes more quickly. Live views of line yields and equipment health have also reduced downtime across operations.

Mandar Deo, Vice President of Digital Technology & Chief Digital Officer, GE Appliances, described AI as a core part of daily work across the business.

"AI is now integral to the way work gets done at GE Appliances. With hundreds of AI agents already in use across manufacturing and operations, our Digital Technology team is accelerating this AI transformation with Gemini Enterprise to build the secure, connected data foundations necessary to lead the industry in the AI era," said Deo.

Factory systems

The deployment uses both the Gemini Enterprise Agent Platform and the Gemini Enterprise app. The platform is used to build, govern and manage custom agents, while the app allows employees to create low-code or no-code agents for specific business tasks.

That structure points to a wider shift in how industrial groups are using AI tools. Rather than limiting development to central technology teams, manufacturers are increasingly putting software tools in the hands of line managers, operations staff and logistics teams closest to day-to-day problems.

This model has already extended beyond the factory floor. In logistics and product quality work, GE Appliances built a Quality Insights AI tool to analyse customer feedback and identify visual patterns linked to product issues.

The shift from manual review to AI-assisted analysis has identified millions of dollars in improvement opportunities across customer logistics and internal operations, although the company did not provide a precise figure.

Marcia Brey, Vice President of Logistics, GE Appliances, said the system was helping teams review customer feedback more quickly.

"We used Gemini Enterprise to create and deploy Quality Insights Assistant to help our teams identify visual patterns faster from customer feedback," said Brey. "At our scale, that means we can catch defects sooner and improve product quality, ultimately delivering a better consumer experience."

Supply chain

The company's service parts business provides another example of the operational scale involved. Its parts team works with more than 700 service parts suppliers and oversees the shipment of about 27 million parts and accessories a year, while keeping parts available for at least seven years after a model stops production.

Within that network, GE Appliances introduced a Supplier Collaboration Agent to handle communication with more than 600 suppliers. The tool automated order status enquiries and led to a 25% reduction in backorders, allowing staff to focus on other work.

The figures offer one of the clearer operational outcomes disclosed in the rollout. Many industrial companies have announced AI projects in manufacturing over the past two years, but fewer have attached performance measures tied to inventory, downtime or production support processes.

Google Cloud framed the deployment as an example of AI use at industrial scale, particularly in settings where large volumes of production, maintenance and supplier data sit across separate systems. Manufacturing groups have long sought to combine those data sources to improve yields, manage downtime and identify quality issues earlier, but the practical challenge has often been making the information usable for employees outside specialist analytics teams.

Matt Renner, President and Chief Revenue Officer, Google Cloud, said GE Appliances had shown how the software could be applied to industrial operations.

"GE Appliances serves as a model for the agentic enterprise, demonstrating how Gemini Enterprise can be deployed at scale to solve complex, real-world industrial challenges," said Renner. "By building AI agents into their manufacturing processes, they are combining their deep industry experience with modern AI to make faster, better decisions."

GE Appliances, based in Louisville, Kentucky, employs 15,500 people across the United States. It says it has invested more than USD $2 billion since 2016 and supports nearly 90,000 additional American jobs through its operations.