AI case study

Freeing employee time

by
SACE
Context

SACE, an Italian finance and insurance firm, uses Microsoft Copilot and Viva to streamline workflows and empower employees. Copilot reduces routine tasks like document sifting and email management, halving time spent on emails and speeding up loan application reviews. Viva supports Copilot adoption, helping reveal collaboration patterns and enabling initiatives like a flexible workweek.

Results

Reduced email management time from 7.2 to 3.7 hours per week; decreased weekend work from 27% to 15%; tasks that once took 6 hours now take 6 minutes; 91% employee adoption of Copilot.

Results not reported in the source
Industry
Insurance
Region
Europe
Published
December 3, 2024
Agent type
Employee Agents
AI provider
Microsoft
Models/tools
Not disclosed
ICE score
432
The ICE framework in this database provides a quick way to assess the feasibility and potential impact of AI use cases, with higher scores signaling more actionable opportunities.

Impact: Potential benefits to the business.

Confidence: Likelihood of achieving expected results.

Ease: Simplicity of implementation in terms of resources and time.

ICE Score: Calculated by multiplying the component scores.

Note:
Each score is AI-generated based on available data and should be viewed merely as a general guideline for deeper exploration of the use cases.
Impact
9
Confidence
8
Ease
6

10

AI use cases in

Insurance

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legal-i

Insurance
Data Agents
Quick win
Use case
Faster unstructured data processing
Context

Developed a GenAI solution leveraging Azure OpenAI Service to analyze, classify and structure unstructured medical records into interactive patient histories and a case DNA for improved decision support.

Models/tools

Newfront

Insurance
Use case
Making insurance processes faster
Context

Newfront, a modern insurance platform serving 20% of US startups with unicorn status, uses Claude from Anthropic to automate tedious insurance tasks. They have deployed Claude across their workflows to create a benefits assistant that provides employees with instant answers about coverage limits and eligible expenses, a contract review tool for legal teams, and automated processing of complex insurance documents, allowing brokers to focus on strategic guidance and problem-solving for clients.

Models/tools
...
1

Zurich Insurance Group

Insurance
Use case
Faster processing of unstructured data
Context

Zurich Insurance Group uses Azure OpenAI Service to develop advanced AI applications in underwriting, improving risk assessments and accelerating the underwriting process. By leveraging Azure OpenAI Service's advanced language AI and text-to-speech models, Zurich can process unstructured data like reports, images, and emails in various languages across its global operations.

Models/tools
Explore industries

321

companies using

Employee Agents

See All
Use case
Fast content creation
Context

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.

Models/tools
...
2
Use case
Reduce report writing burden
Context

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.

Models/tools
...
2
Use case
Faster retail transformation
Context

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.

Models/tools
...
4
Explore agents

251

solutions powered by

Microsoft

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Use case
High-volume student queries
Context

Physics Wallah developed 'Gyan Guru', a hyperpersonalized conversational study companion to address the unique academic and support needs of its 2 million daily users. The system was implemented by indexing over one million Q&As and ten million solved doubts in a vector database, then leveraging a Retrieval-Augmented Generation (RAG) approach integrated with Azure OpenAI to deliver individualized, context-aware responses. This integration streamlined various student interactions including academic queries, product-related issues, and general support, reducing reliance on human subject matter experts.

Models/tools
...
1
Use case
Streamlined executive operations
Context

Brandix adopted the Microsoft 365 Copilot suite via the Early Access Program to integrate AI into key executive workflows, automating meeting transcript-based action tracking in Teams, accelerating pitch deck creation in PowerPoint, and streamlining document generation in Word while leveraging AI-enhanced querying in Power BI and efficient information retrieval via Copilot Chat. This implementation transformed internal communications, reporting, and presentation preparation processes by significantly reducing manual effort.

Models/tools
...
2
Use case
Future-proof IT operations
Context

University of Oxford’s IT Services department deployed Microsoft 365 Copilot across its 400+ staff as part of a pilot program aimed at embedding generative AI into research, teaching, and administrative workflows. They implemented extensive onboarding sessions, community engagement via Microsoft Teams, and established an acceleration team to integrate Copilot with other business applications. This deployment streamlined routine tasks such as document generation, summarization, and meeting support, fostering innovation within the department.

Models/tools
...
1
Explore AI providers

159

AI use cases in

Europe

See All
Use case
Faster research reports
Context

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.

Models/tools
...
2
Use case
Optimized CX workflows
Context

Capgemini partnered with Google Cloud to develop industry-specific agentic AI solutions that automate customer request handling across multiple channels such as web, social, and phone. The implementation integrates Google Agentspace, Customer Engagement Suite, and Agent2Agent interoperability protocol into existing customer service infrastructures to enhance personalized support, call routing, and workflow automation. This advanced solution transforms customer experience by streamlining communications and enabling proactive engagement.

Models/tools
...
3
Use case
Scalable contract detection
Context

wealthAPI implemented a next‐gen contract detection solution by integrating DataStax Astra DB on Google Cloud and leveraging Google Gemini models for AI‐powered analysis. They deployed DataStax’s vector search and real‐time insights capabilities to scale contract detection across millions of users in less than three months, streamlining wealth management workflows by dramatically reducing response times and efficiently handling massive data volumes.

Models/tools
...
1
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Thoughts & ideas