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700+ battle-tested AI case studies to supercharge your strategy
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Fast content creation
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Cox Automotive integrated Claude via Amazon Bedrock into its portfolio by first creating a sandbox environment to evaluate performance metrics and then selecting Claude 3.5 Sonnet for complex tasks and Claude 3.5 Haiku for high-volume content generation. They automated personalized dealer-consumer communications, generated engaging vehicle listing descriptions, and produced SEO-optimized blog posts, while also streamlining internal data governance through automated metadata generation. This integration optimized operational efficiency across marketing and internal data processes.
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Over 2x increase in consumer lead responses, 80% positive seller feedback, and same-day content delivery with 9,000+ client outputs.
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15
AI use cases in
Automotive
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BMW Group implemented a cloud-based mobile data recorder (MDR) system by installing IoT devices in development cars to automatically capture and transmit extensive vehicular telemetry to Microsoft Azure. They built a comprehensive platform using Azure IoT Hub, Azure App Service, and Azure Kubernetes Service, and integrated Azure OpenAI Service with GPT-4o via Azure AI Foundry to create an MDR copilot that converts natural language queries into Kusto Query Language (KQL). This solution streamlined real-time data capture, analysis, and troubleshooting, accelerating vehicle prototyping and enhancing development quality.
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Mercedes-Benz expanded its strategic partnership with Google Cloud to integrate an AI-driven conversational search capability into its MBUX Virtual Assistant. They implemented Google Cloud’s Automotive AI Agent built on Gemini on Vertex AI to access real-time navigation data from Google Maps Platform, enabling multi-turn, natural language dialogue and personalized recommendations that transform in-car navigation and user interaction.
Localiza, a leading mobility company in Latin America, implemented Microsoft 365 Copilot to automate processes and improve efficiency. By integrating AI into their workflows, they enhanced employee productivity, optimized repetitive manual tasks, and improved inclusivity. They conducted training and hackathons to help employees effectively use Copilot, resulting in significant productivity gains across the company.
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321
companies using
Employee Agents
Quillit integrated Anthropic’s Claude to automate qualitative research tasks by summarizing interview transcripts, generating contextual citations, and threading conversation data into comprehensive reports. They implemented the AI tool into their existing research workflow within three months, streamlining report writing, transcription, and analysis while ensuring data security and high precision.
TCS partnered with Google Cloud to integrate advanced AI and generative AI capabilities into retail service offerings. They launched the Google Cloud Gemini Experience Center at their Retail Innovation Lab in Chennai, enabling retail clients to ideate, prototype, and co-develop tailored AI solutions that optimize supply chain, warehouse receiving, customer insights, and content creation. This approach automated processes using tools like Vertex AI Vision for warehouse receiving and leveraged Vertex AI with Gemini 1.5 Pro and speech-to-text to transform service centers.
Deutsche Bank developed DB Lumina, an AI-powered research agent built on Gemini and Vertex AI through a partnership with Google Cloud. The solution automates the creation of financial research reports by rapidly condensing extensive market data—such as converting a 400-page report into a three-page summary—thereby streamlining analysis workflows while maintaining rigorous data privacy standards.
104
solutions powered by
Anthropic
Quillit integrated Anthropic’s Claude to automate qualitative research tasks by summarizing interview transcripts, generating contextual citations, and threading conversation data into comprehensive reports. They implemented the AI tool into their existing research workflow within three months, streamlining report writing, transcription, and analysis while ensuring data security and high precision.
Block implemented Anthropic’s Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) on its Databricks platform to power its internal AI agent, codename goose. They integrated the LLM using secure OAuth-enabled connections and a custom MCP server to connect internal databases and tools, enabling employees across all roles to auto-generate SQL queries, analyze complex data, and automate workflows. This agentic integration streamlined software development, design prototyping, and data analysis by translating user intents into actionable insights.
Quantium deployed Anthropic's Claude across its organization to empower over 1200 employees in functions such as coding, proposal drafting, training development, and leadership coaching. They implemented the AI solution by launching an "ALL IN on AI" strategy with clear guidelines, practical guardrails, and comprehensive hands-on training programs integrated into daily workflows. This approach streamlined routine tasks and enabled teams to focus on strategic initiatives.
284
AIÂ use cases in
North America
Intuit integrated Google Cloud’s Document AI and Gemini models into its GenOS platform to automate the autofill of ten common U.S. tax forms, including complex 1099 and 1040 forms. The solution extracts and categorizes data from uploaded documents, drastically reducing manual data entry for TurboTax customers. This integration streamlines tax preparation workflows and improves speed and accuracy.
Block implemented Anthropic’s Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) on its Databricks platform to power its internal AI agent, codename goose. They integrated the LLM using secure OAuth-enabled connections and a custom MCP server to connect internal databases and tools, enabling employees across all roles to auto-generate SQL queries, analyze complex data, and automate workflows. This agentic integration streamlined software development, design prototyping, and data analysis by translating user intents into actionable insights.
Notion reimagined its platform by deeply integrating OpenAI’s GPT‑4o, GPT‑4o mini, and embeddings across its core features. They prototyped an AI writing assistant during a hackathon and then built internal tools to rapidly evaluate and deploy new models, transforming workflows in search, note-taking, and knowledge management from static content to interactive, actionable insights.
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