Use case type
Uses data models to anticipate outcomes and recommend actions for operational or strategic decisions. It helps organizations respond earlier to risk, demand, or performance changes.
20
20
9
11 mo
Adoption over time
By case publish month · completed months only
18 cases documented across 37 months (Jul 23 – Jul 26), peaking at 4 in May 2026.
1 earlier case before Jul 23 not shown
Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.
Company examples
10 shown from 20 use cases
The Met Office built a prototype to turn raw weather data into readable maritime forecasts using Amazon Nova Foundation Models.The project explores automated text generation for the Shipping Forecast and broader weather services to improve scalability and consistency.
Yassir is the leading superapp in the Maghreb region, operating in Algeria, Morocco, and Tunisia and expanding into additional countries.The company uses Vertex AI on Google Cloud to streamline machine learning workflows from design to production and to support predictive operations and personalized recommendations.
OtherInnovaccer’s AI-powered healthcare data platform unifies patient data across systems and care settings to support population health management analytics.The company built Population Health Copilot 2.0 to help analysts convert natural-language questions into SQL and extract population health insights from multiple data sources faster and more reliably.
The UK Ministry of Justice (MoJ) works to protect and advance the principles of justice, with a vision to deliver a world-class justice system for everyone in society.To support these goals, the MoJ turned to Amazon Web Services (AWS) to reduce operational complexity, enhance collaboration within the ministry, and reduce reliance on older monolithic systems.The ministry's Analytical Platform is built on AWS and serves over 500 data and analytics professionals daily. It powers ingestion and management of large data flows from legacy databases and modern digital microservices, and the MoJ is exploring AWS AI and LLM capabilities including Amazon Bedrock.
Quantum Capital Group supports a portfolio company operating in the Piceance Basin of western Colorado, where energy exploration and field development planning are constrained by difficult terrain, land restrictions, and existing infrastructure.The company replaced a manual geospatial planning workflow that took about three weeks for a single development scenario and about six weeks to compare scenarios with an automated AI-driven tool built on Microsoft Azure. The tool uses an embedded Copilot Studio agent as a conversational interface for engineers and business stakeholders.
Major League Baseball (MLB) uses Google Cloud to process and analyze massive real-time game data and fan data at scale.The organization updated Statcast, its data capture system, to transform ball, player, and pose data into predictive models for baseball analytics.MLB is also using Vertex AI to analyze fan data and improve personalized content recommendations and live content delivery.
OtherCelebal Technologies, an India-based AI and Data partner, collaborates with Microsoft to empower enterprises globally, including in Germany and the US, to integrate AI-driven domain-specific agentic solutions within legacy ERP and MES systems.By leveraging Microsoft Azure AI Foundry, Microsoft 365 Copilot, and Azure Cloud technologies, Celebal Tech has developed persona-based AI agents that deliver real-time insights and decision support for manufacturing operations roles such as plant and supply chain managers.Their solution combines AI Foundry's orchestration, observability, and governance capabilities to ensure traceability and efficacy, providing a governed, explainable agentic economy rather than commoditized AI.
S-Bank, a leading Finnish retail bank, faced intense pressure in a hyper-competitive market characterized by low interest rates and growing regulatory complexity. To stay ahead, S-Bank modernized its analytics and loan processing by migrating workloads to Microsoft Azure and adopting SAS Viya for scalable, automated machine learning. Using this approach, S-Bank enabled real-time decision-making, improved the speed and accuracy of loan approvals, and allowed business analysts to focus on value rather than IT maintenance. The partnership with SAS and Microsoft provided standardized processes, increased compliance, and empowered analysts across the business. These changes enhanced customer experience and significantly reduced operational silos. S-Bank continues to innovate by expanding data science adoption among its analysts and delivering more personalized experiences for clients.
Kraft Heinz developed an internal AI engine called KHAI integrating generative AI for summarizing documents, optimizing factory floor procedures, automating financials, and streamlining SAP rollouts.PlantChat, an AI tool within KHAI, aids manufacturing strategic decision-making.The initiatives include AI-driven supply chain optimizations and data governance.
Microsoft Copilot 365 redefines business interactions with AI-driven automation, intelligent insights, and predictive analytics integrated into Microsoft business applications, such as Dynamics 365 and Power Platform.Copilot automates repetitive tasks like data entry, report generation, email responses, and approvals thus boosting productivity across CRM, ERP, finance, supply chain, customer service, and low-code application development.It expands decision making by analyzing data to uncover trends, predict outcomes, and offer actionable recommendations, helping finance and operations teams make data-driven decisions.The customer service experience is transformed through AI-generated case summaries, suggested responses, intelligent knowledge retrieval, and AI chatbots providing 24/7 support, improving response times and satisfaction.Sales teams gain efficiency through predictive lead scoring, customer interaction summaries, and recommended follow-ups, helping close deals faster.AI-driven forecasting optimizes supply chain management by predicting inventory needs, supplier risks, and logistics bottlenecks, reducing waste and improving resilience.Financial operations benefit from automated financial forecasting, expense tracking, anomaly detection, streamlined budgeting, and enhanced compliance.Copilot integrates with Power BI for natural language report generation and analysis, enabling instant AI-generated insights.Low-code and app development are accelerated with AI assistance in app design, workflow automation using Power Automate, and AI agents built via Copilot Studio to automate approvals and monitor operations.
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