Current and Emerging Artificial Intelligence (AI) Tools to Accelerate Air Force Mobility Aircraft Acquisition Activities

The Air Force Materiel Command (AFMC) is seeking vendor capability information in support of market research to identify current and emerging Artificial Intelligence (AI) tools that can improve the full life cycle acquisition process. The goal is to accelerate fielding and support the best aircraft mobility capabilities to Warfighters. The AI tools should be able to deliver measurable improvements to the acquisition process in the near term, and the information gathered will inform PEO Mobility staff about which AI tools and their impact on process/methodology are available for each phase and task across the Adaptive Acquisition Framework (AAF) and their demonstrated effectiveness. Some areas of specific interest include efficiency in acquisition, AI capabilities, data handling and security, performance monitoring, knowledge sharing and automation, practical applications, costing models, and overall improvement. • Efficiency in acquisition: reducing time, manpower, and cost throughout the acquisition lifecycle • AI capabilities: exploring existing, rapidly deployable AI tools and their specific use cases in accelerating acquisitions and product support planning • Data handling and security: understanding how data is used, secured, and trained in these models, as well as data rights, development environments, and security levels supported • Performance monitoring: assessing program risks, evaluating cost, schedule, and technical performance, and gauging development progress • Knowledge sharing and automation: capturing and sharing knowledge, automating testing processes, and ultimately reducing workload for acquisition staff while improving efficiency • Practical applications: generating, reviewing, and editing acquisition-related and project support documentation, analyzing proposals, and assessing program performance • Costing models: rough order of magnitude cost model, such as enterprise or per license model, tokens, or other • Overall improvement: aiming to reduce workload, increase efficiency, and improve knowledge sharing within program offices, process improvements, and examples where the capability has accelerated acquisitions