Ready to level up your automation skills without needing to code? This session is tailored for IT and business leaders eager to unlock the power of AI Builder to simplify document workflows and fine-tune AI models with your real data. Key Takeaways: • Discover no-code AI capabilities for process automation and optimization • Follow a step-by-step guide to setting up document processing automation in AI Builder—no code required • Learn techniques for implementing a feedback loop to improve model accuracy over time • Explore additional use cases to drive efficiency and innovation in document management Equip yourself with practical, no-code AI skills to streamline your processes and make a tangible impact in your work.

Ever wanted AI to handle tedious data entry into your CRM? In this session, we’ll dive into creating a custom Copilot using Copilot Studio and OpenAI services on Azure to automate data capture from unstructured text. In a live demo, you’ll see how this Copilot can take free-form text, extract essential data, and seamlessly populate CRM fields. What You’ll Learn: • How low-code simplifies building a Copilot with integrated OpenAI capabilities • Tips for crafting effective prompts to maximize accuracy • Step-by-step guidance for automating CRM data entry from unstructured text • A look at the costs involved in implementing this solution This session is packed with practical examples, focusing on hands-on AI tools that transform CRM workflows.

Legal teams are under constant pressure to handle growing workloads with limited capacity. They respond to repetitive questions, review documents, manage approvals, and track contracts, all while ensuring compliance with internal policies and regulations. In parallel, many business users already rely on public AI tools, creating risks related to data exposure, accuracy, and governance. In this session, I will share hands-on experience from building a set of AI agents for legal teams — starting with a simple compliance checker and evolving into end-to-end contract lifecycle automation. The examples are based on real production implementations for enterprise legal teams, including financial institutions. We will begin with an AI agent that supports document compliance checks during client onboarding. The agent validates submitted documents against required document lists, internal policies, and previously approved templates, automatically flagging missing or non-compliant items. Next, I will demonstrate how AI can support standard contract template processing by collecting required inputs from requestors, generating draft agreements, routing non-standard changes back to Legal, and triggering e-signature workflows using DocuSign. We will then explore a centralized AI-driven intake and tracking process for contract drafting and review, covering request logging, version tracking, approvals, and audit-ready sign-off. Finally, I will show how AI agents can support contract lifecycle management by reading signed contracts, tracking key dates, sending renewal and termination reminders, and answering business questions about the contract portfolio. The session focuses on practical patterns, architecture choices, and lessons learned that Dynamics and Power Platform professionals can apply to build governed, scalable AI solutions for legal teams.

SME loan onboarding remains one of the most operationally demanding processes in banking. Relationship managers and loan officers must review large, inconsistent document sets, extract financial data, calculate key metrics, identify gaps, and prepare cases for risk review — all under increasing volume pressure. The result is long processing times, overloaded teams, and repeated back-and-forth caused by incomplete or inconsistent client submissions. In this session, we present an AI Agent designed as an operational capability for SME banking departments, supporting loan onboarding without replacing human decision-making. The agent analyses complex, real-world SME documentation — including financial statements, business plans, cash-flow forecasts, and supporting invoices — regardless of format or structure. Triggered by new document uploads, the agent produces a structured, decision-ready case package. It summarises each document, extracts key financial data, calculates critical ratios (such as gearing, debt-to-EBITDA, efficiency ratios, and working capital metrics), flags missing documents, highlights inconsistencies or potential risks, and suggests next operational steps. All outputs are fully traceable, logged, and designed for human review and approval. Embedded into daily work tools such as Microsoft 365 and Teams, and integrated with existing loan workflows, the agent helps SME departments scale onboarding operations while keeping all final decisions firmly with the bank. During a live demo, we will show how this approach has already reduced initial case preparation time by 45%, turning document-heavy onboarding into a faster, more predictable process.