The Enterprise Guide to Machine Learning

According to Gartner, most AI projects fail and about 80% never reach production. This guide is an attempt to share the experiences and learnings of ML practitioners in the enterprise sector in Germany. Here we discuss and elaborate on the challenges and best practices companies face in the real world. Maintained by the appliedAI, the guide reflects a commitment from the partners of appliedAI to share their experiences and learnings when moving beyond the PoC.

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The purpose of the guide is to build shared wisdom.

This guide consists of four topics:

  • The ML lifecycle: This topic focuses on the importance of having a well-defined ML lifecycle. It condenses ML lifecycle models from different technology players including appliedAI.
  • ML architectures: This topic focuses on the requirements and abstract solution designs for the outlined lifecycles. The discussion will largely center on a collection of approaches to solving common problems encountered along the ML lifecycle.
  • Platforms for ML: This topic finally answers which tools and platforms have been used by our partners to implement particular architectures.
  • Challenges and best practices: This topic condenses the technical and non-technical insights we received from our partners and enriched them with appliedAI internal experiences learned over the last years. It includes perspectives on the practitioner's technical challenges and best practices along the ML lifecycle, management of AI projects, AI team working, and platforms usage.

This report is the result of the appliedAI working group “Enterprise ML” and has drawn on the experience of leading experts from appliedAI partner companies.

Thank you for your contributions: Jörn Franke from the European Central Bank, Faizan Aslam and Simon-Pierre Genot from Infineon, Dilek Sezgün from IBM, Anant Nawalgaria from Google, Dirk Wacker and Into Kemmerzell from Giesecke+Devrient GmbH, Matthias Neuehofer from Baywa AG, Efrem Ghebru and Michael Ksoll from EnBW and many more.

Authors of the guide include Alexander Waldmann and Alexander Machado.

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