Finance AI Use Case Ranking

Microsoft has transformed its supply chain by consolidating over 30 systems into a single data lake on Azure enabling AI-driven autonomous workflows. Over 25 AI agents handle tasks such as demand planning, spare-part space optimization, transport optimization, and invoice analysis. The system integrates simulations, digital twins, and AI-powered robotics to optimize warehouse and logistics operations.,The platform uses technologies including Azure Machine Learning, Microsoft Fabric, Azure IoT Operations, Microsoft 365 Copilot, Microsoft Foundry, NVIDIA Isaac Sim, Azure Kubernetes Services, Microsoft Power Automate, and Celonis Process Intelligence Graph. It hosts AI agents able to reason, plan, and act, improving operational KPIs and saving hundreds of work hours monthly across Microsoft and partner warehouses.,Physical AI robotics like humanoid robots are deployed for warehouse tasks and last-mile deliveries enhancing operational agility. Partners such as SoftServe and Celonis have implemented agentic AI and digital twin solutions, achieving significant productivity gains in pharmaceutical logistics and warehouse automation.

Forvis Mazars, a global business advisory firm, implemented agentic AI and automation to drive digital transformation across industries, notably real estate, healthcare, legal, and biotech.,Leveraging Microsoft technologies including Azure Functions, Azure Logic Apps, Copilot Studio, Power Platform, Microsoft 365 Copilot, Microsoft Fabric, Purview, Defender, and Entra ID, the firm enabled AI agents to autonomously execute business processes with minimal human intervention.,Their maturity journey spanned from rules-based RPA pilots to multi-step agentic automation, embedding business intelligence, compliance, and responsible AI principles throughout.,A flagship implementation automated payroll auditing for real estate clients, reducing processing time from three weeks to one hour, and ensured compliance with local regulations.,Modernization efforts included secure cloud migration and automatic incident response in healthcare, real-time dashboards for legal contract analytics, and personalized member engagement for biotech organizations.,Governance frameworks and an AI Center of Excellence ensured safe roll-out, with metrics/measurable ROI tracked via Microsoft Fabric dashboards.,The project is a leading example of large-scale enterprise agentic AI delivering dramatic productivity, compliance, and operational resilience gains via the Microsoft AI stack.

Fastagger, an African deep-tech startup, has developed a mobile AI business assistant to empower small and medium businesses (SMBs) in Africa. Addressing the challenge of unreliable internet and limited digital infrastructure, Fastagger’s solution runs AI models efficiently on affordable smartphones without requiring a continuous connection. The AUNI system is embedded into Safaricom’s M-PESA Business App, supporting over 2,500 MSMEs in Kenya. This on-device agent enables customer engagement automation, loyalty management, and business coaching.,The AI assistant reduces previously manual processes from eight steps to just two, driving operational efficiency and customer retention. Microsoft’s Africa Transformation Office and NVIDIA have supported Fastagger with mentorship and resources, accelerating the deployment of this mobile-based AI. Key partnerships and the integration with tools like Azure AI, Azure IoT, and GitHub enable robust on-device machine learning. Real-world results underscore substantial improvements in SMB engagement, financial tracking, and growth opportunities, enhancing digital access for underserved populations.,By decentralizing access to AI, Fastagger brings business intelligence and automation to bandwidth-constrained and rural environments—making it easier for SMBs to track customer data, streamline marketing, and make data-driven decisions. The SaaS product costs just $1 to $5 per month, making advanced technologies affordable for local entrepreneurs.,The project illustrates how Microsoft technologies and strategic partnership can close Africa’s digital divide, offering repeatable digital business models to other regions. Fastagger’s infrastructure is available globally via Azure, expanding its impact beyond Africa. Participant feedback validates the significant value of democratized, mobile-first AI for emerging markets.

A leading Canadian commercial real estate capital firm partnered with ALIANDO to overhaul its underwriting, compliance, and finance operations. Facing significant manual processing bottlenecks and siloed data, the firm worked with ALIANDO, a Microsoft partner, to develop a unified AI strategy centered on coordinated copilots. This project leveraged Microsoft Fabric, Azure AI, Power Platform, Azure OpenAI Service, and Copilot Studio to automate document summarization, risk scoring, regulatory validations, audit preparation, and provide real-time analytics. The solution integrated multiple departments’ workflows, increased collaboration, and positioned the company for scalable future innovation. The immediate outcomes were notable improvements in speed, throughput, and revenue, showcasing the value of AI-driven modernization in the finance industry.

Tata Consultancy Services (TCS) provides an AI-native platform for insurance claims processing that transforms a linear claims workflow into an agent-driven ecosystem.,The solution uses Amazon Bedrock Agents with specialist agents to handle document and image ingestion, data extraction, NIGO checks, triage, anomaly detection, and auto-adjudication across workers compensation and disability claims, including live audio transcript generation and dynamic FNOL form filling.

Banco Bradesco, one of Brazil's largest private financial groups, built a scalable generative AI platform called BRIDGE on Microsoft Azure Red Hat OpenShift.,The platform integrates multiple AI models, supports modular multi-agent creation for business teams, and connects to Azure OpenAI while embedding governance, security, and regulatory controls.,BRIDGE serves internal support, development, operations, technology, and customer-service use cases across the bank.

Bankdata, a consortium of Danish banks, faced the challenge of modernizing their vast COBOL-based mainframe legacy systems to cloud-native platforms due to growing technical debt, rising maintenance costs, and limited access to legacy experts. The organization aimed to retain more control over project costs and intellectual property, moving away from traditional approaches heavily reliant on global system integrators. Leveraging state-of-the-art Microsoft technologies, Bankdata and partners developed a modular, agent-based migration factory that uses multiple orchestrated AI agents to analyze, convert, and test COBOL code into maintainable Java running on modern platforms. This system underpinned the transition by extracting business logic, visualizing and mapping dependencies, and ensuring that legacy business processes are accurately transformed. Sophisticated orchestration with Microsoft Semantic Kernel enabled precise management of worker agents, intelligent handling of code context, and conversion consistency. Using GPT-4, GitHub Copilot, and Azure OpenAI, the framework delivers robust code translation, dependency mapping, call chain analysis, and quality assurance through test suite automation. The project significantly reduced manual workload, improved code quality and maintainability, and accelerated transformation timelines, all managed in-house at Bankdata.

KPMG International modernized its global audit process with KPMG Clara AI, a cloud-based smart audit platform used across member firms worldwide.,The platform analyzes whole datasets instead of relying on sampling, automates documentation and substantive audit procedures, and grounds agents in enterprise data for compliant, secure use across regulated jurisdictions.,KPMG built the solution on Azure AI Foundry, Azure AI Search, Azure OpenAI in Foundry Models, Azure AI Content Understanding, Azure App Service, Azure Cosmos DB, and the Microsoft Agent Framework.

NSF, a nonprofit scientific and regulatory auditing organization, needed to organize, verify, summarize, and synthesize tens of thousands of documents across country-specific rules for medical audits.,The solution uses Azure Document Intelligence, Azure OpenAI, Azure Model Context Protocol (MCP) tools and servers, Azure Blob Storage, Azure Python SDK, Azure Cosmos DB, Microsoft Entra ID, and Azure RBAC to automate document validation, structured sorting, version tracking, and summary drafting.,Staff review and refine the AI-generated summaries, while the workflow remains inside Azure cloud controls and private tenant security.,The implementation reduced audit turnaround time from 4–6 weeks to about 2 weeks and was reported to deliver near-perfect accuracy for the proof of concept.

TrueLook built an AI-powered construction safety monitoring system on Amazon SageMaker AI that automatically detects PPE and unsafe conditions from jobsite camera images.,The workflow uses SageMaker Processing, SageMaker Training, SageMaker Model Registry, SageMaker Pipelines, MLflow, TensorBoard, Amazon S3, and real-time endpoints to support a multi-stage fine-tuning and active-learning loop.

IKS Health modernized its healthcare delivery platform with Google Cloud, leveraging AI and DORA principles to improve operational efficiency, clinician satisfaction, and financial resilience for over 850 healthcare enterprises.,The IKS Care Enablement Platform combines intelligent automation, data intelligence, and human expertise to offload healthcare chores across clinical documentation, revenue cycle, care navigation, and operational intelligence.

Enterprises have long relied on Microsoft Entra’s Conditional Access policies to safeguard organizational resources, but manually managing these policies has proven complex and error-prone due to overlapping rules, legacy authentication risks, and rapid environmental changes. The Conditional Access Optimization Agent (CAOA), powered by Security Copilot and integrated within Microsoft Entra, addresses these challenges by continuously scanning user and app inventories, sign-in logs, and existing policies to identify unprotected users, risky applications, and policy gaps. The AI-driven agent analyzes data against Zero Trust principles and provides actionable recommendations with one-click remediation, reducing manual workload while empowering administrators with full oversight. Pilot organizations have already reported freeing up security team hours and discovering over 900 unprotected users not identified through manual audits. CAOA complements existing tools—such as the What If tool and Gap Analyzer—by automating policy reviews while maintaining robust audit trails for transparency. The tool requires Microsoft Entra ID P1+ and Security Copilot licenses and currently operates in private preview. Through proactive, AI-assisted policy management, organizations can both strengthen security and reduce operational overhead.

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.

Totogi automates change request processing for telecom business support systems (BSS) with its BSS Magic platform.,The solution addresses the complexity of telco stacks that include hundreds of vendor applications and require costly customizations, lengthy testing, and specialized engineering expertise.,BSS Magic uses a telco ontology and a multi-agent framework to automate the full software development lifecycle for change requests, including business analysis, technical architecture generation, code generation, automated QA, and test suite generation.,Amazon Bedrock provides the foundation models, while AWS Step Functions and AWS Lambda coordinate state, orchestration, and workflow execution.

Poloplast modernized a legacy AS/400 ERP-based planning process by integrating demand planning, business performance planning, automation, and AI agent capabilities across finance and operations.,The company uses Microsoft Dynamics 365 Supply Chain Management, Dynamics 365 Finance, Power Platform, and Microsoft Copilot Studio to improve forecasting, budgeting, reporting, and employee access to knowledge.

Aily Labs built a mobile-first decision intelligence platform for enterprise users across pharmaceutical, retail, consumer goods, and other sectors.,The platform’s AI brain coordinates hundreds of classical ML models, LLMs, and thousands of enterprise agents orchestrated by a Super Agent to surface insights and actions in real time.,Aily Labs uses AWS infrastructure including Amazon Bedrock, Amazon EKS, Amazon S3, Amazon RDS, AWS KMS, and AWS security/auditing services, and uses Bedrock Prompt Caching to reduce recomputation and latency.

FletcherTech, Fletcher Building’s technology division for its 30+ businesses, implemented Gemini Enterprise to make the company’s collective knowledge easier to access and to weave AI into daily work.,The deployment used Gemini Enterprise with data connectors and Google Cloud console configuration, and integrated with Jira, ServiceNow, and SharePoint to support contextual answers, workflow automation, and data governance checks.,Employees also used the platform to build custom agents for QA testing automation and developer coaching, and to audit data sources for sensitive items such as keys, salary, and personal data.

Junson Capital is a global investment management firm that built an AI-native data engine on Google Cloud to extract structured intelligence from high-variance, unstructured documents.,The firm uses Vertex AI, Document AI, and Gemini models to process private bank statements, inspection testing reports, and handwritten documents with a proprietary six-layer recognition framework.,The implementation also supports regional hosting for data residency and powers an AI-native digital employee workflow for operational tasks.

Verihubs is an Indonesia-based SaaS provider of digital verification and identity authentication services.,The company migrated to Google Cloud to support growing KYC demand, improve performance and cost efficiency, and prepare future AI-enabled workflows.,It also built an in-house deepfake detection capability to help identify AI-generated fraud attempts in images and videos.

Transparently.AI, based in Singapore, built a managed AI platform to detect accounting fraud and manipulation in corporate financial statements. The platform helps investors and financial institutions make more informed decisions by identifying red flags in financial data.,The solution uses Google Cloud Vertex AI, a fine-tuned Gemini 2.0 Flash model, and BigQuery for analysis. Transparently.AI trains about 200 financial models on decades of data across 85,000 companies to replicate the work of forensic accountants, short sellers, credit and equity analysts, and academics.