SEF-MLA7106 - AI for Automotive: Service and Diagnostics
Course Description
This workshop focuses on the highest-stakes use of AI in automotive service: diagnostics, where incorrect information can be costly. Participants learn exactly where AI can add value in the diagnostic process—primarily in research, hypothesis development, and second-opinion support—and where its role must end. AI cannot see the vehicle, perform tests, or make the diagnosis.
The workshop is built around one clear rule: AI drafts the language, the manual owns the numbers, and the technician owns the diagnosis. Participants learn how to use AI as a research and second-opinion tool, recognize risks such as fabricated specifications or bulletin numbers, turn comebacks into reusable shop knowledge, and strengthen warranty documentation. Throughout the session, AI is positioned as a tool to support professional judgment, manufacturer information, and established procedures—not replace them.
Learner Outcomes
Upon completion of this workshop, participants will be able to:
- Identify where AI belongs in the diagnostic loop, at the gather and hypothesis stages, and where it must never be.
- Use a research prompt to broaden a list of potential causes, then verify every claim before it touches a vehicle.
- Develop prompts that surface additional diagnostic questions, tests, and the cheapest way to rule each cause in or out.
- Prompt AI to challenge a diagnosis rather than confirm it, recognizing that it will otherwise tend to agree.
- Run a structured comeback post-mortem and build a searchable shop memory, so the same failure does not repeat.
- Produce warranty documentation with a complete complaint, cause, and correction narrative that survives review.
- Evaluate AI output against manufacturer procedures and professional judgment and never accept a specification or bulletin number from AI.
- Recognize the safety, accuracy, privacy, and liability considerations of AI in service work, including the fabrication risk in warranty claims.
Notes
Target Population
Automotive technicians, diagnostic technicians, shop foremen, service advisors, service managers, dealership personnel, independent repair professionals, and employees of advanced automotive service facilities.
Prerequisites
- Basic computer and internet skills are required.
- Previous completion of SEF-MLA7102 AI for Automotive: AI & Effective Prompting or equivalent basic familiarity with generative AI and prompting is required.
- Participants should have working knowledge of automotive service or repair processes. Experience interpreting diagnostic information, repair orders, technical service information, or diagnostic trouble codes is recommended.