From SAP Analytics to SAP AI — the 90-Day Reskilling Path
As of 2026-09-25
The orientation module for SAP Analytics consultants moving into SAP AI: a dependency-ordered 90-day plan built only from modules and certification codes that exist today. Days 1-20 cover AI fundamentals (M333) plus a fast SAC bridge (M335 Predictive Planning, M336 Smart Predict, M337 Just Ask) that proves AI experience the learner already has. Days 21-55 are the generative AI hub (M325) — the core of the only current SAP generative-AI exam, C_AIG_2604 (3 hours, System-Based Assessment, 76% pass mark). Days 56-75 branch into two of three tracks (Joule agents M326, SAP foundation models M329, HANA vector engine M330). Days 76-90 are exam prep (M331), the C_AIG_2604 exam itself, and a three-artefact portfolio. Closes with what the path deliberately excludes and why.
What you will learn
- Sequence the SAP AI reskilling path in the right dependency order — fundamentals, SAC bridge, generative AI hub, agents/data/models, certification — and explain why the order matters
- State the exact exam code, format and pass mark of SAP's current generative-AI certification (C_AIG_2604) and name the SAP-recommended preparation learning journey
- Distinguish which SAP Analytics Cloud features are classical machine learning (Predictive Planning, Smart Predict) and which are generative AI (Just Ask, Joule), and why that distinction matters to a buyer
- Choose, with a stated reason tied to a real or target client, which two of three branch modules (Joule agents, SAP foundation models, HANA vector engine) to take between days 56 and 75
- Build a personal 90-day calendar with parallelisable and non-parallelisable modules, and a three-artefact portfolio plan to show at the end of it
Module overview
Who this is for. You run SAC stories, BW/4HANA models or Datasphere spaces for a living, and every second client conversation now mentions Joule, an "AI agent" or a generative-AI pilot. This module is the map, not the territory: it does not teach AI itself — module M333 (AI & LLM Fundamentals for SAP Consultants) does that — it tells you, in order, which modules to take, which certification to sit, and what to be able to show a client after 90 days, using only modules and exam codes that exist on this platform today.
Prerequisites
- Working experience with at least one SAP data or analytics product (SAP Analytics Cloud, BW/4HANA, Datasphere or S/4HANA embedded analytics)
- No prior AI or machine-learning background required — this module is the map, not the technical content
- An SAP Learning account (free) to check module and certification pages as you plan
Outcomes
- Produce a dated, 90-day personal reskilling calendar that sequences existing platform modules in the correct dependency order.
- State correctly, without notes, the exam code, duration, format and pass mark of the SAP Generative AI Developer certification.
- Explain to a client, in one paragraph, the true difference between SAC's classical predictive features and its generative-AI layer.
- Justify, with a client-specific reason, which two of three branch modules to prioritise for a given engagement.
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.