The IWG on AI reports on three meetings held since June 2026 and future meetings scheduled through January 2027. The IWG has compiled literature on regulated automotive safety systems using AI, created terms and definitions for AI, listed AI use cases for regulated automotive safety systems, and is working on an AI reference document (latest draft AI-11-03). An AI reference document is scheduled for submission as a formal working document to the June 2027 WP.29 session, based on WP.29-199-26 with structural and conceptual improvements. Small drafting groups will propose document updates via change request forms using AI-11-04, with only updates receiving majority consensus during plenary meetings incorporated into the baseline.

This document provides a draft form for submitting AI reference document change requests. Each request requires a separate submission. The form collects information including the date, agenda item, submitter affiliation, a title of twenty-five words or less, the location of the impacted section or paragraph number, original text, revised text, rationale, and discussion notes. The form includes fields for secretariat use to record whether requests are accepted, accepted as amended, deferred for further discussion, not accepted, or withdrawn.

The agenda includes discussion of the status of the draft reference document for transformation into a formal document for the June 2027 WP.29 session, discussion of timeline for formal document submission to WP.29, and upcoming meetings including sessions planned for October 26-27 in Tokyo, November 24-25 online, and January 26-28 in Washington DC.

AI IWG 12th session will be held October 26–27, 2026, at the Zennihon Truck Sogo Kaikan, 3rd Floor, Tokyo. October 26 runs 10:00–17:30 with reception at 18:30; October 27 runs 09:30–17:00. The meeting room opens 9:30 a.m. October 26 and 9:00 a.m. October 27. In-person attendance is limited to the first 50 registrants. Participants must complete the survey by September 25. JASIC staff contact information and accommodation recommendations are provided.

Document AI-11-03 illustrates a refreshed approach to the draft reference document AI-09-06/Rev.3, based on outcomes from the 10th IWG on AI session (AI-10-04). The document addresses AI uses and potential risks in regulated automotive safety systems. It identifies AI-related risks across lifecycle stages—specification, model training, data management, verification, and operation—and describes risk management practices drawn from standards including ISO 26262, ISO 21448, ISO/PAS 8800, and UN R155/R156. Annex 1 provides illustrative AI use cases in perception, planning, motion control, driver assessment, and vehicle monitoring. Annex 3 tabulates illustrative practices for managing identified risks. The document establishes foundational concepts and terminology to support manufacturers, suppliers, and regulatory authorities in addressing safety implications of AI in automotive systems.

The 10th session of the IWG on AI was held on 23 July 2026. The agenda and the brief report of the 9th session (AI-10-02/Rev.1) were adopted. The chair briefed experts on the June 2026 WP.29 session results, noting a 1-year extension of the IWG on AI mandate to prepare a formal document for submission in June 2027, and a 12-week submission deadline for working documents. The proposed schedule (AI-10-03) covering activities until the June 2027 WP.29 session was discussed with no objections. The chairs offered support for a refresh of the draft reference document (AI-10-04), addressing structural shortcomings and separation of core concepts from implementations. Discussion focused on use case location, scope of AI in regulated automotive safety systems, drafting teams, and workflow for expert input. The 12th IWG on AI session is scheduled for 26–27 October 2026 in Tokyo, Japan and online.

The 9th session of the Informal Working Group on AI convened 3–4 June 2026 in London. Experts adopted the agenda and reviewed the consolidated draft reference document AI-09-06, which was substantially revised through two iterations (AI-09-06/Rev.1 and AI-09-06/Rev.2) before final submission to WP.29 as AI-09-06/Rev.3. Key modifications included limiting use cases in section 3 to driving functions, removing section 6 and the “other use cases” section, and incorporating lifecycle risks in sections 4 and 5. The IWG received a presentation on ISO/PAS 8800/2024 AI safety standards. A 1-year mandate extension was requested to submit a formal document for the June 2027 WP.29 session.

Proposal to reorganize the draft reference document AI-09-06/Rev.3 by moving the risk-by-risk management practices table to an annex, substantively revising Section 1 to emphasize document purpose rather than drafting history, substantively revising Section 2 to explicitly define the scope of AI uses in regulated automotive safety systems and distinguish different modes of AI use, revising Section 5 to replace risk-by-risk presentation with thematic discussion of recurring concepts in international standards and practice, and optionally adding a conclusion and further detailed annexes as needed.

The Informal Working Group on Artificial Intelligence will hold its tenth session on Thursday, 23 July 2026 from 13.30 to 15.30 CET online. The agenda includes adoption of the agenda and brief report of the ninth session, discussion of results of the June WP.29 session presentation, exchange of views on timeline for formal document submission to the June 2027 WP.29 session, discussion of status of the draft reference document in view of its transformation into a formal document, and consideration of upcoming meetings. The eleventh session is planned for Thursday, 3 September 2026.

The AI IWG held two meetings since the last WP.29 session and has virtual meetings scheduled for 23 July 2026 and 3 September 2026. The IWG compiled literature on regulated automotive safety systems using AI (AI-09-04), created Terms & Definitions for AI (AI-09-05), listed AI use cases for regulated automotive safety systems (AI-09-03), and created a draft guiding questions document (AI-08-07). A working draft AI Reference Document (AI-09-06/Rev.3) exists but is not finished. The AI IWG requests an extension of its mandate to deliver the AI Reference Document as a working document no later than June 2027.

This draft reference document consolidates input from documents AI-07-06, AI-09-03, AI-09-04, AI-08-07, and AI-09-05 to fulfill the initial deliverable of the IWG on Artificial Intelligence pursuant to WP.29/1190. The document addresses AI uses and benefits in automotive, establishes AI use cases prioritizing regulated automotive safety applications, identifies potential risks across AI lifecycle stages, and presents illustrative risk management practices informed by literature review. Seven whole-system lifecycle risks are identified, including insufficient documentation and traceability, inadequate organizational governance, and process drift. Additional risks span AI and use case specification, model architecture and training, data management, verification and validation, and in-use monitoring. Risk management practices derive from standards including ISO 26262, ISO 21448, ISO 23894, and UN Regulations 155 and 156, complemented by research and policy frameworks.

This initial consolidate draft reference document for artificial intelligence in regulated automotive safety systems, based on WP.29-195-20, AI-07-08, AI-07-11, AI-07-09, AI-07-10, and AI-07-12, establishes AI use cases and identifies potential risks across the AI lifecycle. The document addresses driving functions including perception, planning and motion control, and end-to-end systems, as well as non-driving functions such as driver assessment and occupant monitoring. It presents six major AI lifecycle risk categories: whole system risks including insufficient documentation and governance; specification risks such as improper definition of intended use; model and training risks including blackbox behaviour and lack of robustness; data management risks such as data poisoning and distribution shift; verification and validation risks including insufficient test coverage; and operational risks including concept drift and limited failure detection. Illustrative risk management practices drawn from standards, research, and regulations are provided for each identified risk to support manufacturers, suppliers, and approval authorities.

AI-Enabled Road Vehicles Managing a Complex Standards Landscape presents the current landscape of standards and regulations for AI in road vehicles, structured overview of core AI governance, engineering, organisational and data governance standards required for EU AI Act conformity and UNECE compliance, and identifies gaps and challenges in alignment. ISO 8800 (2029) Road vehicles Safety of Artificial Intelligence is proposed as a common framework providing navigation and connection across horizontal AI standards with automotive sector-specific needs, reducing fragmentation and enabling transparent, traceable evidence-based assurance for regulators, industry and society while supporting compliance with EU AI Act and future UNECE requirements.

The USA expert submitted initial red-line comments on the consolidated reference document for artificial intelligence in regulated automotive safety systems, marking areas falling outside the Informal Working Group on AI’s terms of reference and bracketing sections pending internal consultations. The USA indicated it will provide additional technical comments following stakeholder consultations.

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.

Comments on the draft consolidated reference document for AI use in regulated automotive safety systems. The comments propose editorial changes to the introduction; minor editorial modifications; and substantive contributions to AI use cases in driving functions (section 3.2) and non-driving functions (section 3.3). Canada’s contributions include additions to risk descriptions such as lack of resilience, regression or catastrophic forgetting, bias as systematic performance disparities, and degradation of AI safety processes over time; expanded guidance on risk management practices with specific automotive examples; and clarification of verification, validation, data management, and operational monitoring requirements aligned with existing standards including ISO 26262, ISO 21448, ISO 23894, and UN Regulations 155 and 156.

The IWG on AI will hold its 9th session on June 3–4, 2026 in London. The agenda includes adoption of the agenda and brief report of the 8th session (AI-09-01), consideration of AI use cases, literature review and terms & definitions proposals, guiding questions for WP.29 submission, and discussion of the consolidated draft reference document. The IWG will receive presentations from stakeholders on AI use in the automotive sector and discuss future meetings and work direction beyond the initial mandate.

This document presents AAPC comments on AI-09-06, a consolidated reference document on artificial intelligence in regulated automotive safety systems. The proposed structure consolidates AI uses, use cases, and risk management into single chapters supported by annexes containing tables and bibliographies. The document should support future regulatory deliberations without pre-empting regulatory requirements, presenting factual statements in neutral language. Considerations should address risks not captured by conventional testing. Examples to illustrate system-specific aspects that impact whether the application of AI presents new concerns and determines the nature of responses include predictive window defogging, predictive vehicle maintenance, and AI vehicle knowledge systems.