Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/5527
Title: AI-Infused Integrated Digital Maturity Pathway (IDMP) User-Story Framework for Defense Acquisition Transformation
Authors: Darryl Draper-Amason
Keywords: Acquisition Transformation
Mission Readiness
Maturity Modeling
Issue Date: 30-Apr-2026
Publisher: Acquisition Research Program
Citation: APA 7
Series/Report no.: Acquisition Management;SYM-AM-26-090
Acquisition Management;SYM-AM-26-178
Abstract: The 2025 Acquisition Transformation Strategy requires the Department of War to adopt faster, mission-centric, and data-enabled acquisition methods that strengthen both acquisition and mission readiness. This paper presents preliminary findings from an ongoing R&E through Systems Engineering Research Center (SERC) funded project, led by the Center for Mission Engineering at Old Dominion University, to advance this mandate using an AI-infused Integrated Digital Maturity Pathway (IDMP) User-Story Framework. The project engages government and industry stakeholders including acquisition executives, program managers, engineers, and industrial base partners through structured workshops to surface operational challenges, identify capability gaps, and develop user stories reflecting real decision needs. An AI/ML component explores how pattern detection and machine reasoning enhance user-story analysis, maturity assessment, and readiness scoring. A targeted survey supplements workshop data, capturing perspectives on readiness barriers, decision bottlenecks, workforce needs, and digital transformation opportunities. Expected findings include a validated set of acquisition executive user stories aligned with the strategy, evidence that AI-enabled analytics improve clarity and decision value, an enhanced IDMP maturity model, and a scalable, practitioner-ready method for translating policy objectives into actionable, mission-focused acquisition decisions.
Description: Presentation and Excerpt
URI: https://dair.nps.edu/handle/123456789/5527
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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