This document contributes to consolidated text and a risk catalogue for artificial intelligence in the automotive sector. It defines AI as a field of computer science focused on creating systems capable of performing tasks requiring human intelligence, including learning, reasoning, problem-solving, natural language processing, and decision-making. High-priority AI use cases include perception, planning, and motion-control driving functions, as well as driver assessment systems. The document identifies 14 risks organized across five lifecycle stages: AI and use case specification, model architecture and training processes, data specification and management, verification and validation, and operation and in-use monitoring. It provides detailed risk descriptions and references emergent practices for managing these risks, including ISO/PAS 8800, NIST AI RMF, and EU AIA approaches. Lower-priority use cases referenced include AI-06-09 for periodic technical inspection and AI-06-12 for cybersecurity threat detection.

Proposals for revisions to Section I including highlighted deletions, addition of two paragraphs (2.3, 2.4) in Section II with a request to add safety benefits to para. 2.6, editorial requests for text placement in Section III introducing use case content, small editorial proposals in Section IV’s introduction, merging of whole lifecycle and organizational risks, removal of para. 4.6 (systematic performance disparities) in favour of para. 4.5, revision of para. 6.2 (concept drift), removal or moving of para. 6.5 to whole lifecycle risks, and substantive suggestions in Section V for deletion, merging and restructuring of Table 2 with standard and title references only. Annex 1 critiques the need for extended descriptions.