Google Cloud Next 2025 revealed a significant expansion in generative AI applications, presenting 601 use cases, up from the 101 shared the previous year. The expansion signifies the growing role of GenAI in enterprise operations.
Matt Renner, President of Global Revenue at Google, emphasised, “This is just scratching the surface of what’s becoming possible with AI across the enterprise.” The newly released examples span a wide array of industries—from automotive and finance to healthcare and hospitality—illustrating GenAI’s deepening integration across both customer-facing and internal operations.
Structural Framework Enhances GenAI Integration Across Sectors
Google is formalising its generative AI roadmap with a new structural framework introduced at Cloud Next 2025, mapping 601 use cases across 11 industry sectors and six distinct AI agent types. The model groups applications into six agent types—Customer, Employee, Creative, Code, Data, and Security—each tied to specific enterprise functions.
The structure aims to streamline GenAI integration across customer support, internal operations, and cybersecurity.
Sector Case Studies Highlight Tangible Outcomes
Automotive and Logistics
Automakers and logistics companies are increasingly embedding GenAI into user experiences and operations. Volkswagen of America integrated a multimodal assistant into its myVW app using Google’s Gemini models, allowing users to simply point their phone at a dashboard light for real-time explanations.
Mercedes-Benz brought natural language AI into its vehicles, enabling in-car navigation and e-commerce directly through voice interactions. Meanwhile, UPS is developing a digital twin of its global package network to track and optimise delivery in real time.
Financial Services
Financial institutions are pushing AI from the back office to the core of business operations. Citi is using Vertex AI to power developer tools and digitise complex financial documents.
Deutsche Bank’s “DB Lumina” tool, powered by Gemini, has cut research report preparation time from hours to minutes. Discover Financial has also deployed GenAI assistants for both customers and employees, improving service delivery and internal workflows alike.
Healthcare and Life Sciences
Healthcare organisations are using GenAI to improve diagnostics and expand access. Freenome is combining AI with blood samples to build early detection tools for cancer.
The Mayo Clinic is utilising Vertex AI Search to sift through 50 petabytes of clinical data, unlocking faster access to medical insights.
Apollo Hospitals has applied AI to scale cancer and tuberculosis screening to over 3 million people, using radiology workflows enhanced by machine learning.
Manufacturing and Electronics
Manufacturers are integrating GenAI directly into product ecosystems. Samsung now features Gemini-powered AI tools like text summarisation and image editing in the Galaxy S24.
Engineering firms such as Trimble and Honeywell are using Gemini in Google Workspace to improve productivity through automated document generation and planning tools.
Media, Retail, and Hospitality
AI is also changing how brands engage customers. Papa John’s, Wendy’s, and Uber are leveraging predictive ordering systems powered by GenAI to anticipate customer needs. Radisson Hotel Group reported “a 50% gain in marketing productivity and over 20% revenue lift” after implementing AI-driven ad personalisation via Vertex AI.
Adobe’s integration of Imagen 3 and Veo 2 into Adobe Express has dramatically accelerated the pace of campaign creation for creatives.
AI Platform Capabilities Strengthen Enterprise Deployment
Google is reinforcing its AI ecosystem with tools built for enterprise-scale deployment. Vertex AI underpins training and retrieval-augmented generation, while Gemini models handle tasks involving multiple inputs—ranging from language to images and code.
Imagen and Veo support generative media, and BigQuery ML allows businesses to run machine learning models directly within analytics workflows. In the cybersecurity domain, Security AI provides tailored intelligence for threat monitoring.
Enterprise AI Maturity Reaches an Inflection Point
The expansion in use case diversity reflects a fundamental shift: generative AI is now considered essential to enterprise operations. Hybrid models that integrate multiple data types, including language, images, and structured inputs, are powering new application categories.
Organisations are developing industry-specific agents to meet targeted needs, signalling a move toward specialised AI architectures. Alongside this trend, greater accessibility is redefining user engagement with AI.
AI tools are no longer limited to developers, these tools are reaching a broader range of professionals—from doctors and sales teams to factory-floor workers.
Conclusion
The growing number of enterprise applications—now totalling 601—illustrates how generative AI is becoming embedded in core business infrastructure. Google Cloud’s newly released examples span sectors and functions, pointing to AI’s operational significance. “This is just scratching the surface of what’s becoming possible with AI across the enterprise,” said Matt Renner.