Towards an Ontology-Driven Adaptive Acquisition System

Abstract

Systems engineering has historically provided an effective framework for managing large-scale acquisitions. Yet, as systems grow in size, complexity, and timeframe, traditional approaches are becoming less effective. Accelerating rates of change and high levels of uncertainty reduce the long-term value of acquired systems, while the scale of modern programs increases costs, coordination demands, and timelines — heightening the risk of obsolescence before delivery. These pressures raise fundamental questions about the continued viability of conventional acquisition practices. In response, tools such as Model-Based Systems Engineering (MBSE), Agile Systems Engineering (AgileSE), and digital engineering have been introduced. While these provide incremental performance gains, they do not resolve the core challenge: how to manage acquisition in environments where predictability and uncertainty coexist. Doing the same things faster is not enough; a shift in mindset and method is required. This paper argues that ontology-driven approaches provide the foundation for that shift. Ontologies — machine-readable representations of concepts, relationships, and constraints — create a semantic backbone that integrates models, data, and stakeholder perspectives. By embedding ontologies into acquisition systems, organizations can simultaneously bridge predictive and adaptive paradigms, enhance traceability and interoperability across technical, financial, and operational domains, and enable automated reasoning to expose dependencies, conflicts, and opportunities. The result is an acquisition ecosystem that is not only more coherent and collaborative but also adaptive to the dynamic conditions of the 21st century. Many of the elements needed for this transformation already exist; the critical step forward is adopting ontologies as the integrative layer that unites them.