Learn how to navigate the current AI landscape and understand the SAP Business AI value story in this overview session. This session is designed for professionals seeking clarity on how SAP Business AI integrates into modern operations. We break down the complex AI landscape to help you identify where these tools provide tangible benefits for your organization. By focusing on the core SAP Business AI value story, you will gain a clearer picture of how to align these technologies with your existing business objectives. Whether you are evaluating new software solutions or simply trying to map out the current enterprise AI environment, this walkthrough provides the necessary context. We explain the foundational concepts behind SAP AI value to ensure you can communicate its utility effectively within your team.

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Chapters:
00:00 - SAP Business AI Overview
00:05:50 - SAP Business AI Portfolio & Joule
00:12:38 - Stage 1: AI Ideation & Business Value
00:13:43 - Stage 2: Feasibility, Risk & Scoping
00:15:04 - Stage 3: Prototyping & Prompt Testing
00:24:07 - Orchestration Execution Workflow
00:40:40 - Installing the Python SDK
00:59:27 - Connecting the SDK to AI Hub
01:19:24 - OCR & Structured Data Extraction

In this video, you'll learn:
SAP's "flywheel" strategy, how apps, harmonized data, and embedded AI feed into one another to eliminate silos and manual work
Real-world business impact numbers: Western Sugar's 25% faster invoice processing and Mercedes-Benz's 95% automated ESG reporting
The five-stage AI product lifecycle: ideation, feasibility and scoping, prototyping, productization, and deployment and monitoring
The full orchestration service workflow in detail: grounding, templating, input/output masking, content filtering, and translation
How to set up SAP Business Application Studio, connect a Python dev space to SAP AI Core, and configure your AI Core config file
A live, hands-on walkthrough deploying a model from the Generative AI Hub and calling it through Python using the SAP Cloud SDK for AI
How to build and run an orchestration deployment with prompt templates, including multi-modal use cases like image description and text extraction from photos

Seeing the exact same concepts from theory get typed, deployed, and debugged live, errors and all, is what actually prepares you to do this on your own project, not just recognize the terms in an interview. The next session goes deeper into content filtering, data masking, and grounding configuration in the orchestration service.

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