This category uses AI to guide new employees, customers, or partners through setup, training, and required processes. It helps reduce manual coordination and speeds up time to productivity.
Use cases
26
Examples
26
Industries
9
Timeline
13 mo
Data updated 1 day ago
Adoption over time
Documented cases per month
By case publish month · completed months only
21 cases documented across 37 months (Jul 23 – Jul 26), peaking at 4 in April 2025.
AI Use Cases Hub
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.
2Innovativeness2/5Incremental2/5 - Incremental. EKZ integrates GitHub Copilot into Azure DevOps pipelines to speed coding and infrastructure automation, but the evidence describes straightforward code-assistant adoption rather than a novel operating model or advanced orchestration.
Elektrizitätswerke des Kantons Zürich (EKZ), a prominent Swiss energy utility, adopted GitHub Copilot with the Azure cloud to boost developer productivity and streamline infrastructure automation. Facing software development bottlenecks, EKZ integrated Copilot into its DevOps pipeline, leveraging AI to automate code generation, infrastructure scripts, and application delivery. The initiative resulted in significant reductions in coding and deployment times and improved developer satisfaction. EKZ’s use of Copilot also underpinned a broader shift toward digital transformation within the Swiss energy sector, setting a benchmark for innovation, operational efficiency, and enhanced service delivery.
5Innovativeness5/5Breakthrough5/5 - Breakthrough. Combines Copilot agents with a three-layer architecture and explicit RAG over structured/unstructured quality and regulatory data, integrated into QMS/ERP/CRM with governance (Entra ID, DLP, humans-in-the-loop) for recall automation in a highly regulated domain.
RSM deploys advanced Copilot Agents in manufacturing to reduce quality risks and manage product recalls.AI-powered agents analyze real-time data, identify affected product batches, pinpoint root causes, and automate recall notifications—all with seamless integration to existing Quality Management Systems (QMS), ERPs, and CRM tools.Their technical architecture includes layering data sources, Copilot intelligence (Copilot Studio, Power Platform, Power Automate), and user interfaces in Teams, Outlook, or Dynamics 365.AI models and Copilot Studio guide agents through user prompts, system actions, and automated event triggers. Security is ensured via Entra ID authentication, data loss prevention, and role-based access for generative AI.Retrieval-Augmented Generation (RAG) capabilities allow accurate processing for both structured (quality orders, ERP records) and unstructured (documents, feedback) data.Governance processes retain humans-in-the-loop for decisions with validation, filters for sensitive topics, and performance monitoring, ensuring compliance and reliability.These innovations accelerate investigations and recalls, improve regulatory alignment, and protect corporate brands in a highly regulated environment.RSM offers custom Copilot solutions for manufacturers seeking operational transformation and competitive advantage.
1Innovativeness1/5Foundational1/5 - Foundational. The evidence is largely about broad AI/Copilot adoption and localization in Brazil with limited specifics on unique technical architecture or operational transformation.
Major Brazilian enterprises and the public sector are going beyond AI speculation, implementing Microsoft Copilot and Azure AI to increase operational efficiency, regulatory compliance, and cultural adaptability. Microsoft's expansion of local data centers—powered by renewable energy—enables enterprises to run advanced AI workloads suited for Brazil's infrastructure and climate. Early adopters among large businesses employ natural language processing in Portuguese for customer service, regulatory compliance, and localized project management. The presence of a robust partner ecosystem, with leaders like SoftwareOne, Accenture, and Capgemini among others, is fostering further AI adoption. ISG’s Provider Lens report highlights the growing maturity of Microsoft AI services in Brazil, their tailored offerings for vertical industries, and the accelerating pace of cloud-enabled transformation.Market research reveals that Brazil's technology sector is undergoing rapid digitalization, with Copilot emerging as a universal AI interface for local organizations. Enterprises leverage Copilot's linguistic and cultural adaptation capabilities to improve user engagement, compliance workflows, and project outcomes. The report also stresses the importance of hybrid device strategy and cloud sustainability in Brazil, due to variable internet infrastructure and local climate conditions.The local ecosystem recognizes the competitive differentiation gained from Copilot’s cultural customization and streamlined compliance. With enhanced computing infrastructure and strong partnerships, Brazil is emerging as a leader in cloud-based AI, with applications across agribusiness, financial services, and healthcare. The ISG report further details provider rankings and highlights the fastest-growing community of GitHub developers in the region.
5Innovativeness5/5Breakthrough5/5 - Breakthrough. The case explicitly describes a new operating model—domain-tuned AI agents with multi-agent orchestration, model integration via Azure AI Foundry, and enterprise identity/security controls—backed by multiple quantified deployments.
Microsoft announced new Copilot Tuning and multi-agent orchestration in Microsoft 365 Copilot Studio, empowering organizations to build and fine-tune AI agents using domain-specific data, workflows, and processes. The low-code tools let non-data scientists create, deploy, and rapidly update custom AI agents. The release includes multi-agent orchestration, allowing agents to collaborate on complex cross-departmental workflows, such as onboarding and support, and integration with Azure AI Foundry so users can bring their models. Noteworthy customer examples: Wells Fargo reduced bankers' search time by 95% (10 min to 30 sec) via an agent serving 35,000 staff; T-Mobile uses agents to aggregate product data from over 20 sources instantly; HCLTech accelerated case resolutions by 40% and redeployed 30% of a 500-strong support team. Security and compliance are ensured via Microsoft Entra Agent ID and Microsoft Purview Information Protection. The ecosystem includes an Agent Store for discovery, a Teams AI library for multi-agent communications, and pro-code/low-code developer tools.
2Innovativeness2/5Incremental2/5 - Incremental. A Copilot for manufacturing provides real-time actionable insights and team analytics to improve productivity, but the case lacks evidence of novel technical integration beyond using Copilot-style capabilities.
Avanade introduced a Manufacturing AI Copilot powered by Microsoft technologies. This tool provides frontline manufacturing employees with advanced, actionable insights. It incorporates real-time data for enhanced decision-making and ties comprehensive team analytics to build a more synchronized production system. Additionally, operational productivity is transformed into an agile workflow.
2Innovativeness2/5Incremental2/5 - Incremental. The case claims Dynamics 365 + Copilot integration with AI agents automating sales tasks and personalization, but provides no detailed uncommon technical integration beyond standard copilot/CRM usage.
Microsoft significantly improved Grand & Toy's sales systems by integrating Dynamics 365 and Copilot, enabling streamlined sales and better customer service.
2Innovativeness2/5Incremental2/5 - Incremental. AvePoint integrates Microsoft 365 Copilot and GitHub Copilot to improve productivity and deploy an internal AI support agent, but the evidence does not show unusual architecture beyond standard copilots/support automation.
AvePoint, a global leader in data security, governance, and resilience, adopted Microsoft AI technologies to revolutionize its operations and customer service. By integrating Microsoft 365 Copilot and GitHub Copilot across multiple departments, the company accelerated its development lifecycle, reclaimed 1-3 hours per week per employee, and enhanced customer satisfaction. AI-powered support agents streamlined customer service, reducing response times and improving accuracy. AvePoint also focused on sustainable AI adoption through continuous employee training and automated guardrails, ensuring responsible and scalable implementation. The company's comprehensive approach established it as a trusted advisor in the digital transformation journey, exemplifying how enterprise-level AI integration can deliver remarkable operational results and a stronger customer experience.
4Innovativeness4/5Advanced4/5 - Advanced. The case evidences agentic workflow deployment via coordinated use of Copilot Studio and AI agents, plus a governance framework (SAFE) and multi-tool integration across M365, Dynamics 365, Azure AI Foundry, and Power Platform.
Forvis Mazars, a global consulting and Microsoft partner, implements AI agents and Copilot tools to automate business workflows and improve operational efficiency.The consulting team introduces agentic and micro-agent AI solutions in professional services, enabling automation of repetitive tasks and intelligent decision-making.Using Microsoft 365 Copilot, Dynamics 365, Copilot Studio, Azure AI Foundry, and Power Platform, their deployments help organizations increase productivity, drive innovation, and streamline employee experiences.Clients benefit from personalized automation for data entry, report generation, scheduling, and customer relationship management, freeing staff for strategic work.Forvis Mazars emphasizes responsible AI adoption, incorporating their SAFE AI Framework for governance—focusing on security, adaptability, fairness, and ethics.Case studies cover insurance, retail, transportation, healthcare, and manufacturing, with examples such as transforming quote systems and enhancing data quality/services.Strategic integration approaches include prompt engineering, workforce upskilling, role redefinition, and formal knowledge- and coordination-collaboration initiatives.The program highlights ethical AI, regulatory compliance, and transparent deployment, positioning clients for competitive advantage and sustainable growth.
4Innovativeness4/5Advanced4/5 - Advanced. Custom Copilot agents are connected via Graph Connectors and APIs to enterprise systems (Azure SQL, SharePoint, external sources) and orchestrate workflows that trigger actions in other tools like Trello, indicating multi-system automation beyond simple prompting.
At the Digital Workplace Conference NZ, practical implementations of advanced Copilot Agents were demonstrated for real New Zealand enterprises. The session showed how Microsoft 365 Copilot, Graph Connectors, and Azure SQL are used to build custom Copilot agents that automate domain-specific tasks by pulling data from various line-of-business systems. Use cases covered automated product inquiries from an Azure SQL warehouse and project management workflows in Trello. Unlike out-of-the-box Copilot, these agents have controlled, enterprise-specific knowledge sources (SharePoint, LOB systems, trusted external websites), providing knowledge integration, process orchestration, and automation beyond AI prompting. Enterprises now rapidly extend Copilot’s effectiveness, uniting previously siloed data and boosting business outcomes. The practical session received overwhelmingly positive feedback from enterprise leaders now considering similar AI projects for internal automation.
3Innovativeness3/5Differentiated3/5 - Differentiated. Multiple enterprises embed Copilot/Power Automate with Azure OpenAI for workflow automation, document analysis, multilingual communication, and real-time analytics, but the architecture details remain generic across examples.
This article showcases real-world examples of organizations across banking, legal, travel, manufacturing, healthcare, and marine industries implementing Microsoft 365 Copilot and Azure OpenAI to enhance productivity, streamline workflows, and improve customer engagement. For instance, Bank of Queensland automated risk analysis and training material creation, saving 2.5 to 5 hours per user weekly. ABB Group integrated Azure OpenAI with Genix Copilot for real-time data processing, achieving 35% in operational savings. Teladoc Health automated routine tasks with Copilot and Power Automate, saving thousands of hours annually. Other notable implementations include Clifford Chance's enhanced legal processes, Absa Group’s document analysis, and Capitec Bank’s improved information access for customer service. Elcome streamlined multilingual communications using Copilot. Business impacts ranged from increased employee efficiency and satisfaction to substantial operational cost reductions and improved customer experiences.
How many onboarding automation use cases are documented?
The AI Use Case Hub documents 26 real onboarding automation deployments across 9 industries, with 26 detailed company examples you can browse.
Which industries adopt onboarding automation the most?
Onboarding automation is most common in Professional Services (27%), Manufacturing (23%) and Tech & Comms (15%).
Which countries lead in onboarding automation?
United States leads documented onboarding automation deployments, followed by Switzerland and Germany.
What technologies are used for onboarding automation?
Teams most often build onboarding automation with Microsoft 365 Copilot, Copilot and Copilot Studio.
What AI capabilities power onboarding automation?
Across the documented deployments, the most common capability patterns are Copilot (100%), Agent (38%) and Multi-agent (35%).
What results do companies report from onboarding automation?
Across the 26 deployments reporting outcomes, companies most often cite speed & agility (85%), customer experience & trust (65%) and new product / capability (65%). Where impact is quantified, the strongest evidence is in cost savings: a median −35% across 3 reported metrics.