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Academy module

SAP AI Launchpad Operations

SAP AI Launchpad Operations — Analytics Legends section illustration for the SAP Analytics knowledge base (concepts, studies, Academy)

As of 2026-09-25

Edited by , sole editor and publication director — 27 years in the SAP ecosystem. How these pages are produced, and where automation is used.

The operating model behind SAP AI Launchpad, sourced entirely to SAP's own User Guide (help.sap.com, dated 2026-09-04): the producer/consumer audience split and the three application groups that serve it, the generative AI hub's global scenarios and executables (foundation-models, orchestration) and its four gating roles, the exact six-step generative AI deployment procedure and the Auto Upgrade versus Manual Upgrade model-lifecycle regimes, the ML Operations use-case/scenario/executable model and its four lifecycle tasks, resource-group isolation as the platform's core access boundary, and the Git repository naming and role rules inside SAP AI Core Administration. Written for the freelance consultant who will actually operate the tool, not present it.

What you will learn

  • Name the two SAP AI Launchpad audiences (AI scenario producers, AI scenario consumers) and the three application groups that serve them
  • List the generative AI hub's four gating roles and state which roles cannot save prompts
  • Execute the six-step procedure to create a generative AI deployment, including the two eligible roles and the one-resource-group-per-activity rule
  • Explain the Auto Upgrade versus Manual Upgrade model-lifecycle regimes and the modelVersion default behaviour
  • Explain the AI use case / scenario / executable model and map each ML Operations lifecycle task to its component
  • Explain resource-group isolation and diagnose a disabled-navigation ticket caused by a missing resource-group selection
  • State the Git repository naming rules and the role required to manage repositories in SAP AI Core Administration

Module overview

Who this is for. You have been asked to "set someone up in AI Launchpad" or "check why the deployment isn't showing," and you want the actual operating model, not a screenshot tour. This module pairs with M362/M363 in the next batch of this track (SAP AI Core resource groups, scenarios and executables) and assumes M333 (AI & LLM fundamentals). Everything below is sourced to SAP's own AI Launchpad User Guide (help.sap.com, PUBLIC, dated 2026-09-04).

Prerequisites

  • M333 (AI & LLM Fundamentals for SAP Consultants) or equivalent
  • Basic familiarity with SAP AI Core (service instances, service keys) is helpful but not required
  • Basic familiarity with SAP BTP role collections is helpful but not required

Outcomes

  • Triage an AI Launchpad support request to the correct application group (Generative AI Hub, ML Operations, Administration, Workspaces) before investigating further.
  • Create a generative AI deployment end to end and choose the correct model-upgrade regime for a production workload.
  • Diagnose a resource-group-related access issue without escalating a configuration gap as a product bug.
  • Set up a compliant Git repository connection for training and serving templates.

Full module available to members. The full module adds: the decision framework · the end-to-end scenario walkthrough · the KPI scorecard · the anti-patterns · the code blocks · the knowledge check · the diagrams.

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