USE OF GENERATIVE AI ARTIFACTS TO TEACH TECHNOLOGY READINESS ASSESSMENTS

The Technology Readiness Level (TRL) methodology has been widely adopted in the United States and Europe as a framework for evaluating the maturity of technologies across various sectors such as new products, manufacturing processes, software, medical devices, and pharmaceuticals. Technology Readiness Assessments (TRAs) provide a systematic methodology for identifying technology development risks, but they inherently involve a degree of subjectivity, necessitating the involvement of experienced subject matter experts. Evidence to justify a readiness level is provided through test reports and related artifact documents. This paper addresses the challenge of providing realistic TRA training in an academic setting. Starting with a hypothetical technology development and associated readiness prompts, generative artificial intelligence (AI) produces tailored artifact documents. These documents then comprise mini case studies for teaching the TRA process. Since TRAs are integrated into both industry and government processes, competency in the TRA process is an essential engineering management skill.