GE ‘Reinvents’ Manufacturing with Google AI

GE is leveraging Google’s agentic AI systems to supercharge its manufacturing, logistics and supply chain operations, including this top-freezer refrigeration plant in Decatur, Ala.

Gemini Enterprise embedded across multiple operations

YSN Staff

GE Appliances said it is building “the future of manufacturing” through an AI partnership with Google.

Using Gemini Enterprise, Google Cloud’s unified agentic portfolio, the appliance giant said it is reinventing its manufacturing operations at scale and “democratizing AI” by putting it in the hands of the people closest to the work.

Agentic AI is defined by the Massachusetts Institute of Technology (MIT) as an advanced class of AI systems that go beyond chatbots by planning, acting and learning on their own. Under the partnership with Google, GE has deployed more than 800 “AI agents” across its manufacturing, logistics and supply chain operations, driving faster decision-making, improved product quality and increased operational efficiency, the company said.

“AI is now integral to the way work gets done at GE Appliances,” said Mandar Deo, the company’s vice president of digital technology & chief digital officer. “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.” 

GE is using both the Gemini Enterprise Agent Platform and Gemini Enterprise app to fuel its agentic strategy. While the Agent Platform provides the foundation to build, scale, govern and optimize custom AI agents, the Gemini Enterprise app allows employees on the production line to create and orchestrate low-code/no-code agents to solve business challenges.

GE embedded Gemini Enterprise into its Brilliant Factory manufacturing data platform, which tracks production performance, part genealogy and workforce activity across production lines, shifts and plants. By applying AI within this environment, GE said it has shifted from reactive problem solving to real-time, data-driven decision making on the factory floor.

GE said the advantages of AI integration include:

Rapid shift summaries: AI agents analyze shift data in minutes rather than hours, allowing teams to identify root causes faster.

Intuitive data interaction: Employees can “talk” to production data to diagnose issues without needing specialized data science support.

Real-time optimization: Live view of line yields and equipment health have significantly reduced downtime, driving continuous improvement across operations.

GE also used Gemini Enterprise to build its Quality Insights AI tool, which enhances product design and accelerates improvement across customer logistics and quality processes. The transition from manual reviews to AI-assisted analysis has yielded measurable results, the company said, uncovering millions of dollars in improvement opportunities across customer logistics and internal operations.

“We used Gemini Enterprise to create and deploy Quality Insights Assistant to help our teams identify visual patterns faster from customer feedback,” said Marcia Brey, GE’s vice president of logistics. “At our scale, that means we can catch defects sooner and improve product quality, ultimately delivering a better consumer experience.”

In the supply chain, GE’s appliance parts team manages a massive logistical network, coordinating with more than 700 service parts suppliers and overseeing the shipment of approximately 27 million parts and accessories annually, while maintaining parts availability for at least seven years after a model’s production ends. Last year GE introduced a supplier collaboration agent to manage communication with more than 600 suppliers. The agent automated order status inquiries, leading to a 25% reduction in backorders and allowing the team to focus on high-value strategic growth, the company said.

“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 Matt Renner, president and chief revenue officer of Google Cloud. “By building AI agents into their manufacturing processes, they are combining their deep industry experience with modern AI to make faster, better decisions.”

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