Current and Emerging Artificial Intelligence (AI) Tools to Accelerate Air Force Mobility Aircraft Acquisition Activities FA8688-RFI-26-0001

SEE ATTACHED RFI DOCUMENTS FOR MORE INFORMATION AND SUBMISSION INSTRUCTIONS The Air Force Materiel Command (AFMC), Air Force Life Cycle Management Center/Mobility Aircraft Directorate (AFLCMC/WL) seeks vendor capability information in support of market research. This RFI is to understand (1) the current and emerging Commercial Off the Shelf (COTS), Government Off the Shelf (GOTS) high Technology Readiness Level (TRL) AI tools (ex. TRL range 7-9), and field-ready tools (e.g., Impact Level (IL) IL 5/6 certified or scheduled certification), and (2) tool impact on process/methodology that can be used independently and/or as part of a larger continuum of tools in support of upcoming PEO Mobility procurement activities across aircraft platform lifecycles that will result in accelerating fielding and supporting the best aircraft mobility capabilities to our Warfighters. PEO Mobility is seeking industry input to identify current and emerging AI tools that can improve the full life cycle Acquisition process to efficiently deliver high-quality hardware and software capabilities faster to the Warfighter. To accomplish this task, we are seeking to leverage, to the maximum extent feasible, AI capabilities for all phases of PEO Mobility s portfolio of programs, spanning the entirety of the acquisition lifecycle. PEO Mobility understand that these tools are continually maturing. PEO Mobility may use AI automation to periodically monitor vendor-provided documentation and Uniform Resource Locators (URL) for updates, changes, or new capabilities. This RFI seeks tools that can deliver measurable improvements to the acquisition process in the near term. 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, enabling recommendations for implementation across the PEO Mobility portfolio to accelerate change. To assist vendors, this RFI includes a notional scenario titled PEO Mobility Enterprise Connectivity in a Contested Environment that describes the organization s specific AI needs. Areas of specific interest include but are not limited to: 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 & 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: Assess program risks, evaluate cost, schedule, and technical performance, and gauge development progress. Knowledge Sharing & Automation: Capture/share knowledge, automate testing processes, and ultimately reduce workload for acquisition staff while improving efficiency. Practical Applications: Ability to generate, review, and edit acquisition-related and project support documentation, analyze proposals, and assess program performance. Costing Models: Rough order of magnitude cost model (i.e. 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. Integrable & Customizable: Can work with existing desktop applications, other AI platforms, and be customized to fit diverse government/program office requirements at different levels of classification and other tools available or used by the vendor. Ability to integrate into workflow automation including CI/CD pipelines (continuous integration, continuous delivery). These are also called DevOps or DevSecOps pipelines. Interaction with Existing Government Ecosystem: Interoperability with existing government data, artifacts, and toolchains via APIs/plugins; support for common data standards/formats (DoW Data Strategy); integration with existing tools for Requirements Management (RM), Application of Lifecycle Management (ALM), Product Lifecycle Management (PLM), Model Based Systems Engineering (MBSE) and DevSecOps; includes Supply Chain Management (read-only vs read-write behavior), Configuration Management (permissions/change control and traceability, audit/provenance logging), Security (operation at required classification levels), Reliability (performance/scalability and failure/rollback handling), Operability/Maintainability (cross-domain options and human-in-the-loop controls). Tool Development Maturity: Assessed TRL and is it ready for rapid or immediate use. Product Roadmap: Where is the tool now and where is it going.

UPDATE: Closing date extended to 30 April 2026. Vendors are welcome, but not required, to send additional submissions. As a reminder, this Request for Information is not a Request for Proposal. SEE ATTACHED RFI DOCUMENTS FOR MORE INFORMATION AND SUBMISSION INSTRUCTIONS The Air Force Materiel Command (AFMC), Air Force Life Cycle Management Center/Mobility Aircraft Directorate (AFLCMC/WL) seeks vendor capability information in support of market research. This RFI is to understand (1) the current and emerging Commercial Off the Shelf (COTS), Government Off the Shelf (GOTS) high Technology Readiness Level (TRL) AI tools (ex. TRL range 7-9), and field-ready tools (e.g., Impact Level (IL) IL 5/6 certified or scheduled certification), and (2) tool impact on process/methodology that can be used independently and/or as part of a larger continuum of tools in support of upcoming PEO Mobility procurement activities across aircraft platform lifecycles that will result in accelerating fielding and supporting the best aircraft mobility capabilities to our Warfighters. PEO Mobility is seeking industry input to identify current and emerging AI tools that can improve the full life cycle Acquisition process to efficiently deliver high-quality hardware and software capabilities faster to the Warfighter. To accomplish this task, we are seeking to leverage, to the maximum extent feasible, AI capabilities for all phases of PEO Mobility s portfolio of programs, spanning the entirety of the acquisition lifecycle. PEO Mobility understand that these tools are continually maturing. PEO Mobility may use AI automation to periodically monitor vendor-provided documentation and Uniform Resource Locators (URL) for updates, changes, or new capabilities. This RFI seeks tools that can deliver measurable improvements to the acquisition process in the near term. 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, enabling recommendations for implementation across the PEO Mobility portfolio to accelerate change. To assist vendors, this RFI includes a notional scenario titled PEO Mobility Enterprise Connectivity in a Contested Environment that describes the organization s specific AI needs. Areas of specific interest include but are not limited to: 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 & 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: Assess program risks, evaluate cost, schedule, and technical performance, and gauge development progress. Knowledge Sharing & Automation: Capture/share knowledge, automate testing processes, and ultimately reduce workload for acquisition staff while improving efficiency. Practical Applications: Ability to generate, review, and edit acquisition-related and project support documentation, analyze proposals, and assess program performance. Costing Models: Rough order of magnitude cost model (i.e. 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. Integrable & Customizable: Can work with existing desktop applications, other AI platforms, and be customized to fit diverse government/program office requirements at different levels of classification and other tools available or used by the vendor. Ability to integrate into workflow automation including CI/CD pipelines (continuous integration, continuous delivery). These are also called DevOps or DevSecOps pipelines. Interaction with Existing Government Ecosystem: Interoperability with existing government data, artifacts, and toolchains via APIs/plugins; support for common data standards/formats (DoW Data Strategy); integration with existing tools for Requirements Management (RM), Application of Lifecycle Management (ALM), Product Lifecycle Management (PLM), Model Based Systems Engineering (MBSE) and DevSecOps; includes Supply Chain Management (read-only vs read-write behavior), Configuration Management (permissions/change control and traceability, audit/provenance logging), Security (operation at required classification levels), Reliability (performance/scalability and failure/rollback handling), Operability/Maintainability (cross-domain options and human-in-the-loop controls). Tool Development Maturity: Assessed TRL and is it ready for rapid or immediate use. Product Roadmap: Where is the tool now and where is it going.